COMPOSITIONS AND METHODS FOR QUANTIFICATION OF SERUM GLYCOPROTEINS

Information

  • Patent Application
  • 20100279382
  • Publication Number
    20100279382
  • Date Filed
    March 12, 2010
    14 years ago
  • Date Published
    November 04, 2010
    14 years ago
Abstract
The invention provides compositions and methods for identifying and/or quantifying glycopolypeptides from human serum or plasma. The compositions and methods include a plurality of standard peptides containing glycosylation sites determined for human serum/plasma proteins.
Description
BACKGROUND OF THE INVENTION

The present invention relates generally to the field of proteomics and more specifically to quantitative analysis of blood, plasma or serum glycoproteins.


Complete genomic sequences and large partial (EST) sequence databases potentially identify every gene in a species. However, the sequences alone do not explain the mechanism of biological and clinical processes because they do not explain how the genes and their products cooperate to carry out a specific process or function. Furthermore, the gene sequence does not predict the amount or the activity of the protein products nor does it answer the questions of whether, how, and at what position(s) a protein may be modified.


Quantitative protein profiling has been recognized as an important approach for profiling the physiological state or pathological state of cells or organisms. Specific expectations of quantitative protein profiles include the possibility to detect diagnostic and prognostic disease markers, to discover proteins as therapeutic targets or to learn about basic biological mechanisms.


Not only do the amounts and type of proteins expressed vary in different pathological states, post-translational modifications of proteins also vary depending on the physiological or pathological state of cells or organisms. Thus, it is important to be able to profile the amount and types of expressed proteins as well as protein modifications.


Glycosylation has long been recognized as the most common post-translational modification affecting the functions of proteins, such as protein stability, enzymatic activity and protein-protein interactions. Differential glycosylation is a major source of protein microheterogeneity. Glycoproteins play key roles in cell communication, signaling and cell adhesion. Changes in carbohydrates in cell surface and body fluid are demonstrated in cancer and other disease states and highlights their importance. However, studies on protein glycosylation have been complicated by the diverse structure of protein glycans and the lack of effective tools to identify the glycosylation site(s) on proteins and of glycan structures. Oligosaccharides can be linked to serine or threonine residues (O-glycosylation) or to asparagine residues (N-glycosylation), and glycoproteins can have different oligosaccharides attached to any given possible site(s).


Among the many post-translation modifications of proteins, glycosylation is a modification that is common to proteins that are exposed to an extracellular environment. For example, proteins expressed on the surface of a cell are exposed to the external environment such as blood or surrounding tissue. Similarly, proteins that are secreted from a cell, for example, into the bloodstream, are commonly glycosylated.


Proteins secreted by cells or shed from the cell surface, including hormones, lymphokines, interferons, transferrin, antibodies, proteases, protease inhibitors, and other factors, perform critical functions with respect to the physiological activity of an organism. Examples of physiologically important secreted proteins include the interferons, lymphokines, protein and peptide hormones. Aberrant availability of such proteins can have grave clinical consequences. It is therefore apparent that the ability to precisely quantitatively profile secreted proteins would be of great importance for the discovery of the mechanisms regulating a wide variety of physiological processes in health and disease and for diagnostic or prognostic purposes. Such secreted proteins are present in body fluids such as blood serum and plasma, cerebrospinal fluid, urine, lung lavage, breast milk, pancreatic juice, and saliva. For example, the presence of increased levels of prostate-specific antigen has been used as a diagnostic marker for prostate cancer. Furthermore, the use of agonists or antagonists or the replacement of soluble secreted proteins is an important mode of therapy for a wide range of diseases.


Quantitative proteomics requires the analysis of complex protein samples. In the case of clinical diagnosis, the ability to obtain appropriate specimens for clinical analysis is important for ease and accuracy of diagnosis. As discussed above, a number of biologically important molecules are secreted and are therefore present in body fluids such as blood and serum, cerebrospinal fluid, saliva, and the like. In addition to the presence of important biological molecules, body fluids also provide an attractive specimen source because body fluids are generally readily accessible and available in reasonable quantities for clinical analysis. It is therefore apparent that a general method for the quantitative analysis of the proteins contained in body fluids in health and disease would be of great diagnostic and clinical importance.


A key problem with the proteomic analysis of serum and many other body fluids is the peculiar protein composition of these specimens. The protein composition is dominated by a few proteins that are extraordinarily abundant, with albumin alone representing 50% of the total plasma proteins. Due to the abundance of these major proteins as well as the presence of multiple modified forms of these abundant proteins, the large number of protein species of lower abundance are obscured or inaccessible by traditional proteomics analysis methods such as two-dimensional electrophoresis (2DE).


Proteins secreted and present in body fluids have in common a high propensity for being glycosylated, that is, modified post translationally with a carbohydrate structure of varying complexity at one or several amino acid residues. Thus, the analysis of glycoproteins allows characterization of important biological molecules.


Thus, there exists a need for methods of high throughput and quantitative analysis of blood, serum or plasma glycoproteins and glycoprotein profiling for diagnostic purposes. The present invention satisfies this need and provides related advantages as well.


SUMMARY OF INVENTION

The invention provides compositions and methods for identifying and/or quantifying glycopolypeptides from human serum or plasma. The compositions and methods include a plurality of standard peptides containing glycosylation sites determined for human serum/plasma proteins.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 shows oxidation of a carbohydrate to an aldehyde followed by covalent coupling to hydrazide beads.



FIG. 2 shows representative chemical reagents that have been tested and proven to be able to label amino groups of glycopeptides. The structures of labeled peptides are shown in the right column.



FIG. 3 shows the chemistry and schematic diagram of isotopically labeling the N-termini of immobilized glycopeptides by attaching differentially isotopically labeled forms of the amino acid phenylalanine (Phe) to their N-termini.



FIG. 4 shows a schematic of quantitative analysis of serum proteins.



FIG. 5 shows an exemplary analysis with the addition of a standard peptide.



FIG. 6 shows a diagram of a procedure for glycopeptide profiling of serum proteins using liquid chromatograpy-mass spetrometry (LC-MS).



FIG. 7 shows the ratio of peptides identified without NXS/T glycosylation motif as a function of peptide identification stringency. The fraction of peptides identified with (center bar) or without (right bar) glycosylation consensus motif are shown for different PeptideProphet (Keller et al., Anal. Chem. 74:5383-5392 (2002)) probabilities. The false positive error rates were estimated by PeptideProphet are indicated (left bar).



FIG. 8 shows the reproducibility of the high throughput serum analysis method. Distribution of coefficient of variance (CV) from 9 repeated LC-MS analyses of the same glycopeptide mixture (rectangles), and distribution of CV from 4 repeated sample preparations using glycopeptide capture-and-release method and LC-MS analysis (squares) are shown.



FIG. 9 shows identification of peptides exhibiting increased abundance in treated cancer-bearing mice. FIG. 9A shows normalized abundances of the peptide at m/z value of 709.7 observed in sera of normal (N1a, N1b, N2) and cancer-bearing mice (C1, C2, C3), determined by LC-MS analysis. FIG. 9B shows validation of differential abundance of the same peptide shown in FIG. 9A using isotopic labeling of N-termini.



FIG. 10 shows a schematic illustration of an offline LC-MALDI TOF/TOF based platform for proteome-screening technology.



FIG. 11 shows a search and identification of a specific spike-native peptide pair in a complex background. The native peptide was consistently identified in different runs using the spike-in stable isotope labeled peptide as a search criterion, even though the peptides were deposited on different spot positions in different runs.



FIG. 12 shows the complementary approach for peptide identification using specific mass match and peptide sequencing. The search of a specific mass resulted in more than one precursor ion locating at different spot positions. Both of the precursor ions were submitted for MS/MS analysis. The one with the higher intensity, distributing across spot 133 to 138, was identified as the targeted peptide.



FIG. 13 shows an exemplary analysis using a method of the invention. FIG. 13A shows the base peak chromatogram of a glycopeptide mixture spiked with stable isotope labeled peptides. The sample was fractionated in 192 wells on a MALD plate. Each point on the x-axis indicates a spot position. The elution of the majority of the peptides was between spot 45 and 165. FIG. 13B shows the MS spectrum of a representative spot.



FIG. 14A shows the number of precursor ions detected in each spot in MS mode. FIG. 14B shows the elution profile of the spike-in stable isotope labeled peptides extracted from the complex background. The elution profile of a spiked peptide was used to locate the spot position(s) containing the peptide.



FIG. 15 shows the identification of a targeted peptide with low abundance in a complex serum glycopeptide mixture. The pair of the spike-in and native peaks was located and identified using specific mass search against the MS data. The validation of the peptide sequence was accomplished using MS/MS analysis and database searching.



FIG. 16 shows a quantitative profile of the selected peptides detected in 4 different serum samples (1S2, 1F2, 3S1, 3F1). The x axis represents the peptide mass. The y axis indicates the abundance ratio of a native peptide to the corresponding spike-in stable isotope labeled peptide. The peptides and their corresponding proteins are listed in Table 6.



FIG. 17 shows a protein network analysis of changes in glycoprotein expression in prostate cancer tissue.



FIGS. 18A and 18B shows the amino acid preferences around N-linked glycosylation sites.



FIG. 19 shows a representative output of proteotypic N-linked glycopeptides from a database using UniPep.



FIG. 20 shows reproducible CID spectra generated from light and heavy isoforms of the same peptide sequence.





DETAILED DESCRIPTION OF THE INVENTION

The invention provides methods for quantitative profiling of glycoproteins and glycopeptides on a proteome-wide scale. The methods of the invention can be used to determine changes in the abundance of glycoproteins and changes in the state of glycosylation at individual glycosylation sites on those glycoproteins that occur in response to perturbations of biological systems and organisms in health and disease.


Because the methods of the invention are directed to isolating glypolypeptides, the methods also reduce the complexity of analysis since many proteins and fragments of glycoproteins do not contain carbohydrate, which can simplify the analysis of complex biological samples such as serum, plasma or blood. The methods of the invention are advantageous for the determination of protein glycosylation in glycome studies and can be used to isolate and identify glycoproteins from serum, plasma or blood to determine specific glycoprotein changes related to certain disease states or cancer. The methods of the invention can be used for detecting quantitative changes in protein samples containing glycoproteins and to detect their extent of glycosylation. The methods of the invention are applicable for the identification and/or characterization of diagnostic biomarkers, immunotherapy, or other diagnositic or therapeutic applications. The methods of the invention can also be used to evaluate the effectiveness of drugs during drug development, optimal dosing, toxicology, drug targeting, and related therapeutic applications.


The invention uses methods for identifying and/or quantifying glycopolypeptides in a blood, plasma or serum sample, in particular a human blood, plasma or serum sample. The methods of the invention can also be used to identify and/or quantify glycopolypeptides in other biological fluids. Methods for quantifying glycoproteins have been described previously (see, for example, Zhang et al., Nat. Biotechnol. 21:660-666 (2003); Aebersold and Zhang, U.S. publication 2004/0023306, each of which is incorporated herein by reference.


In one embodiment, the invention provides a method for identifying glycopolypeptides in a serum, plasma or blood sample. The method can include the steps of (a) derivatizing glycopolypeptides in the sample; (b) immobilizing the derivatized sample glycopolypeptides to a solid support; (c) cleaving the immobilized sample glycopolypeptides, thereby releasing non-glycosylated peptide fragments and retaining immobilized sample glycopeptide fragments; (d) labeling the immobilized sample glycopeptide fragments with an isotope tag; (e) releasing the sample glycopeptide fragments from the solid support, thereby generating released sample glycopeptide fragments; (f) adding to the released sample glycopeptide fragments a plurality of standard peptides selected from peptides containing the glycosylation sites shown in Tables 7 (SEQ ID NOS:1-3244), 8 (SEQ ID NOS:3245-3369) or 10 (SEQ ID NOS:3370-3517) and referenced as SEQ ID NOS:1-3517, wherein the standard peptides correspond to peptides derivatized as in step (a), cleaved as in step (c), and released as in step (e), and wherein the standard peptides are differentially labeled with a corresponding isotope tag as used in step (d); (g) analyzing the released sample glycopeptide fragments using mass spectrometry; and (h) identifying released sample glycopeptide fragments that correspond to standard peptides added in step (f). The method can further comprise quantifying the amount of the sample glycopeptide fragments identified in step (h).


As used herein, a plurality of standard peptides refers to a selection of 2 or more peptides containing the glycosylation sites listed in Tables 7, 8 and/or 10. A plurality of standard peptides can include, for example, 3 or more, 5 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 110 or more, 120 or more, 130 or more, 140 or more, 150 or more, 160 or more, 170 or more, 180 or more, 190 or more, 200 or more, 220 or more, 250 or more, 270 or more, 300 or more, 350 or more, 400 or more, 450 or more, 500 or more, 600 or more, 700 or more, 800 or more, 900 or more, 1000 or more or more, 2000 or more, or even up to all of the glycosylation sites listed in Tables 7, 8 and/or 10. In a particular embodiment, the plurality of standard peptides contains about 100 or more, about 110 or more, about 120 or more, about 130 or more, about 140 or more, about 150 or more, about 160 or more, about 170 or more, about 180 or more, about 190 or more, about 200 or more, about 220 or more, about 250 or more, about 270 or more, about 300 or more, about 350 or more, about 400 or more, about 450 or more, about 500 or more, about 600 or more, about 700 or more, about 800 or more, about 900 or more, or about 1000 or more peptides containing the glycosylation sites listed in Tables 7, 8 and/or 10. It is understood that when the plurality of standard peptides contains less than about 90 or about 80 peptides, the plurality of standard peptides specifically excludes peptides containing previously known glycosylation sites.


As disclosed herein, a number of N-linked glycosylated peptides have been identified in human plasma/serum, including those having the consensus N—X—S/T glycosylation motif (Table 7) and peptides that do not contain the consensus N—X—S/T motif (Table 8). It is understood that the sequences shown in Tables 7, 8 and 10 represent glycosylation sites and that the standard peptides referred to herein need only include the glycosylation sites but need not contain the exact sequences shown in Tables 7, 8 and/or 10, so long as the selected standard peptides correspond to peptides cleaved with the same cleavage reagent. For example, the first glycosylation site shown in Table 7 (SEQ ID NO:1) contains a glycosylated Asn at position 11 of the shown sequence. A standard peptide containing the glycosylation site referenced in SEQ ID NO:1 can be, for example a peptide from Glu 2 to Lys 21 or Val 9 to Lys 21 if cleaved with trypsin (trypsin peptide), which cleaves on the carboxyl side of Lys or Arg. Both peptides are potential trypsin peptides since cleavage with proteases is not be 100% efficient at every cleavage site. Additionally, a standard peptide containing the glycosylation site referenced as SEQ ID NO:1 can be, for example, Phe 2 to Glu 15 if cleaved with Staphylococcus aureus protease (sap peptide), which cleaves on the carboxyl side of Asp or Glu. Thus a plurality of standard peptides containing the glycosylation site of SEQ ID NO:1 and corresponding to trypsin cleaved peptides can contain one or both of the trypsin peptides indicated above, whereas a plurality of standard peptides containing the glycosylation site of SEQ ID NO:1 and corresponding to Staphylococcus aureus protease can contain the sap peptide indicated above. Other proteases can also be used to generate protease specific peptides as desired and disclosed herein.


As used herein, a peptide that “corresponds” to a referenced condition means that the peptide has the same chemistry as if the referenced condition had been performed on the peptide. For example, if a sample peptide is derivatized, for example, by oxidation, cleaved with a particular cleavage reagent, and released from a solid support, the standard peptide is synthesized, either by the same process or using well known chemical synthesis methods, so that the standard peptide has identical chemistry except for any differential labeling due to the incorporation of an isotope tag. Because the standard and sample peptides are generally analyzed by MS and use identical chemistry except for any differential isotope labeling, the standard peptides are synthesized so that they have identical chemistry as the sample peptides to be analyzed.


In methods of the invention, the particular cleavage reagent used for the standard peptides can be selected by one skilled in the art based on a desired use. The standard peptides are synthesized so that the peptides incorporate the same resulting cleavage chemistry as selected for the sample peptides. In the case of generating the standard peptides, the peptides can be synthesized as longer peptides and cleaved with a desired reagent or can be synthesized as a desired sequence, so long as the resulting standard peptide would have the same product as though cleaved with the reagent used to cleave the sample glycopolypeptides. In methods of the invention in which the sample peptides are to be quantified, a predetermined amount of the standard peptide can be added for comparison and quantification (see, for example, Gygi et al., Nature Biotechnol. 17:994-999 (1999); WO 00/11208).


In a particular embodiment of a method of the invention, the solid support can comprise a hydrazide moiety. In another embodiment of a method of the invention, the glycopeptides are released from the solid support using a glycosidase, for example, an N-glycosidase or an O-glycosidase. In still another embodiment of a method of the invention, the glycopeptides can be released from the solid using sequential addition of N-glycosidase and O-glycosidase. In yet another embodiment, the glycopeptides can be released from the solid support using chemical cleavage.


In one embodiment of a method of the invention, the glycopolypeptides can be oxidized with periodate. In still another embodiment of the invention, the glycopolypeptides can be cleaved with a protease, for example, trypsin.


In another embodiment, the invention provides a method for identifying glycopolypeptides in a serum sample. The method can include the steps of (a) immobilizing the sample glycopolypeptides to a solid support; (b) cleaving the immobilized sample glycopolypeptides, thereby releasing non-glycosylated peptide fragments and retaining immobilized sample glycopeptide fragments; (c) labeling the immobilized sample glycopeptide fragments with an isotope tag; (d) releasing the sample glycopeptide fragments from the solid support, thereby generating released sample glycopeptide fragments; (e) adding to the released sample glycopeptide fragments a plurality of standard peptides selected from peptides containing the glycosylation sites shown in Tables 7, 8 and/or 10 and referenced as SEQ ID NOS: 1-3482, wherein the standard peptides correspond to peptides cleaved as in step (b), and released as in step (d), and wherein the standard peptides are differentially labeled with a corresponding isotope tag as used in step (c); (f) analyzing the released sample glycopeptide fragments using mass spectrometry; and (g) identifying released sample glycopeptide fragments that correspond to standard peptides added in step (e). Such a method can further comprise quantifying the amount of the sample glycopeptide fragments identified in step (g).


In yet another embodiment, the invention provides a method for identifying and quantifying glycopolypeptides in a control serum or plasma sample. The method can include the steps of (a) derivatizing glycopolypeptides in a control serum sample; (b) immobilizing the derivatized sample glycopolypeptides to a solid support; (c) cleaving the immobilized sample glycopolypeptides, thereby releasing non-glycosylated peptide fragments and retaining immobilized sample glycopeptide fragments; (d) labeling the immobilized sample glycopeptide fragments with an isotope tag; (e) releasing the sample glycopeptide fragments from the solid support, thereby generating released sample glycopeptide fragments; (f) adding to the released sample glycopeptide fragments a plurality of standard peptides selected from peptides containing the glycosylation sites shown in Tables 7, 8 and/or 10 and referenced as SEQ ID NOS: 1-3482, wherein the standard peptides correspond to peptides derivatized as in step (a), cleaved as in step (c), and released as in step (e), and wherein the standard peptides are differentially labeled with a corresponding isotope tag as used in step (d); (g) analyzing the released sample glycopeptide fragments using mass spectrometry; (h) identifying released sample glycopeptide fragments that correspond to standard peptides added in step (f); and (i) quantifying the amount of the sample glycopeptide fragments identified in step (h). The control serum sample can be normal serum or plasma obtained from a healthy individual or individuals.


In an additional embodiment, the invention provides a method for identifying one or more diagnostic markers for a disease. The method can include the steps of (a) derivatizing glycopolypeptides in a serum sample from an individual having a disease; (b) immobilizing the derivatized sample glycopolypeptides to a solid support; (c) cleaving the immobilized sample glycopolypeptides, thereby releasing non-glycosylated peptide fragments and retaining immobilized sample glycopeptide fragments; (d) labeling the immobilized sample glycopeptide fragments with an isotope tag; (e) releasing the sample glycopeptide fragments from the solid support, thereby generating released sample glycopeptide fragments; (f) adding to the released sample glycopeptide fragments a predetermined amount of a plurality of standard peptides selected from peptides containing the glycosylation sites shown in Tables 7, 8 and/or 10 and referenced as SEQ ID NOS: 1-3482, wherein the standard peptides correspond to peptides derivatized as in step (a), cleaved as in step (c), and released as in step (e), and wherein the standard peptides are differentially labeled with a corresponding isotope tag as used in step (d); (g) analyzing the released sample glycopeptide fragments using mass spectrometry; (h) identifying released sample glycopeptide fragments that correspond to standard peptides added in step (f); (i) quantifying the amount of the sample glycopeptide fragments identified in step (h); and (j) comparing the amount of. the sample glycopeptide fragments determined in step (i) to the amount of the same glycopeptide fragments determined in a normal serum sample. It is understood that the methods disclosed herein in which a glycopolypeptide sample is derivatized can also be performed in the absence of derivatization so long as the glycopolypeptides can be captured. An example of such a capture method includes lectin, antibody or affinity chromatography. In a particular embodiment, the disease is cancer.


In still another embodiment, the invention provides a method for identifying glycopeptides in a serum sample. The method can include the steps of (a) immobilizing glycopolypeptides from a serum sample to a solid support; (b) cleaving the immobilized sample glycopolypeptides, thereby releasing non-glycosylated peptide fragments and retaining immobilized sample glycopeptide fragments; (c) labeling the immobilized sample glycopeptide fragments with an isotope tag; (d) releasing the sample glycopeptide fragments from the solid support; (e) adding to the released sample glycopeptide fragments a plurality of standard peptides selected from peptides containing the glycosylation sites shown in Tables 7, 8 and/or 10 and referenced as SEQ ID NOS: 1-3482, wherein the standard peptides correspond to peptides cleaved as in step (b) and released as in step (d), and wherein the standard peptides are differentially labeled with a corresponding isotope tag as used in step (c); and (f) analyzing the released sample glycopeptide fragments.


In one embodiment, the cis-diol groups of carbohydrates in glycoproteins can be oxidized by periodate oxidation to give aldehydes, which are reactive to a hydrazide gel with an solid support to form covalent hydrazone bonds. The immobilized glycoproteins are subjected to protease digestion followed by extensive washing to remove the non-glycosylated peptides. The immobilized glycopeptides are released from beads by chemicals or glycosidases. The isolated peptides are analyzed by mass spectrometry (MS), and the glycopeptide sequence and corresponding proteins are identified by MS/MS combined with a database search. The glycopeptides can also be isotopically labeled, for example, at the amino or carboxyl termini to allow the quantities of glycopeptides from different biological samples to be compared.


The methods of the invention are based on selectively isolating glycosylated peptides, or peptides that were glycosylated in the original protein sample, from a complex sample. The sample consists of peptide fragments of proteins generated, for example, by enzymatic digestion or chemical cleavage. A stable isotope tag can be introduced into the isolated peptide fragments to facilitate mass spectrometric analysis and accurate quantification of the peptide fragments.


In one embodiment, a sample containing glycopolypeptides is chemically modified so that carbohydrates of the glycopolypeptides in the sample can be selectively bound to a solid support. For example, the glycopolypeptides can be bound covalently to a solid support by chemically modifying the carbohydrate so that the carbohydrate can covalently bind to a reactive group on a solid support. The carbohydrates of the sample glycopolypeptides are oxidized. The carbohydrate can be oxidized, for example, to aldehydes. The oxidized moiety, such as an aldehyde moiety, of the glycopolypeptides can react with a solid support containing hydrazide or amine moieties, allowing covalent attachment of glycosylated polypeptides to a solid support via hydrazine chemistry. The sample glycopolypeptides are immobilized through the chemically modified carbohydrate, for example, the aldehyde, allowing the removal of non-glycosylated sample proteins by washing of the solid support. If desired, the immobilized glycopolypeptides can be denatured and/or reduced. The immobilized glycopolypeptides are cleaved into fragments using either protease or chemical cleavage. Cleavage results in the release of peptide fragments that do not contain carbohydrate and are therefore not immobilized. These released non-glycosylated peptide fragments optionally can be further characterized, if desired.


Following cleavage, glycosylated peptide fragments (glycopeptide fragments) remain bound to the solid support. To facilitate quantitative mass spectrometry (MS) analysis, immobilized glycopeptide fragments can be isotopically labeled. If it is desired to characterize most or all of the immobilized glycopeptide fragments, the isotope tagging reagent contains an amino or carboxyl reactive group so that the N-terminus or C-terminus of the glycopeptide fragments can be labeled (see FIGS. 2 and 3). The immobilized glycopeptide fragments can be cleaved from the solid support chemically or enzymatically, for example, using glycosidases such as N-glycanase (N-glycosidase) or O-glycanase (O-glycosidase). The released glycopeptide fragments or their deglycosylated forms can be analyzed, for example, using MS.


As used herein, the term “polypeptide” refers to a peptide or polypeptide of two or more amino acids. A polypeptide can also be modified by naturally occurring modifications such as post-translational modifications, including phosphorylation, fatty acylation, prenylation, sulfation, hydroxylation, acetylation, addition of carbohydrate, addition of prosthetic groups or cofactors, formation of disulfide bonds, proteolysis, assembly into macromolecular complexes, and the like. A “peptide fragment” is a peptide of two or more amino acids, generally derived from a larger polypeptide.


As used herein, a “glycopolypeptide” or “glycoprotein” refers to a polypeptide that contains a covalently bound carbohydrate group. The carbohydrate can be a monosaccharide, oligosaccharide or polysaccharide. Proteoglycans are included within the meaning of “glycopolypeptide.” A glycopolypeptide can additionally contain other post-translational modifications. A “glycopeptide” refers to a peptide that contains covalently bound carbohydrate. A “glycopeptide fragment” refers to a peptide fragment resulting from enzymatic or chemical cleavage of a larger polypeptide in which the peptide fragment retains covalently bound carbohydrate. It is understood that a glycopeptide fragment or peptide fragment refers to the peptides that result from a particular cleavage reaction, regardless of whether the resulting peptide was present before or after the cleavage reaction. Thus, a peptide that does not contain a cleavage site will be present after the cleavage reaction and is considered to be a peptide fragment resulting from that particular cleavage reaction. For example, if bound glycopeptides are cleaved, the resulting cleavage products retaining bound carbohydrate are considered to be glycopeptide fragments. The glycosylated fragments can remain bound to the solid support, and such bound glycopeptide fragments are considered to include those fragments that were not cleaved due to the absence of a cleavage site.


As disclosed herein, a glycopolypeptide or glycopeptide can be processed such that the carbohydrate is removed from the parent glycopolypeptide. It is understood that such an originally glycosylated polypeptide is still referred to herein as a glycopolypeptide or glycopeptide even if the carbohydrate is removed enzymatically and/or chemically. Thus, a glycopolypeptide or glycopeptide can refer to a glycosylated or de-glycosylated form of a polypeptide. A glycopolypeptide or glycopeptide from which the carbohydrate is removed is referred to as the de-glycosylated form of a polypeptide whereas a glycopolypeptide or glycopeptide which retains its carbohydrate is referred to as the glycosylated form of a polypeptide.


As used herein, the term “sample” is intended to mean any biological fluid, cell, tissue, organ or portion thereof, that includes one or more different molecules such as nucleic acids, polypeptides, or small molecules. A sample can be a tissue section obtained by biopsy, or cells that are placed in or adapted to tissue culture. A sample can also be a biological fluid specimen such as blood, serum or plasma, cerebrospinal fluid, urine, saliva, seminal plasma, pancreatic juice, breast milk, lung lavage, and the like. A sample can additionally be a cell extract from any species, including prokaryotic and eukaryotic cells as well as viruses. A tissue or biological fluid specimen can be further fractionated, if desired, to a fraction containing particular cell types. As used herein, a “serum sample” refers to the fluid portion of the blood obtained after removal of the fibrin clot and blood cells. As used herein, a “plasma sample” refers to the fluid, non-cellular portion of the blood.


As used herein, a “polypeptide sample” refers to a sample containing two or more different polypeptides. A polypeptide sample can include tens, hundreds, or even thousands or more different polypeptides. A polypeptide sample can also include non-protein molecules so long as the sample contains polypeptides. A polypeptide sample can be a whole cell or tissue extract or can be a biological fluid. Furthermore, a polypeptide sample can be fractionated using well known methods, as disclosed herein, into partially or substantially purified protein fractions. In a particular embodiment, a polypeptide sample can be a serum sample or plasma sample.


The use of biological fluids such as a body fluid as a sample source is particularly useful in methods of the invention. Biological fluid specimens are generally readily accessible and available in relatively large quantities for clinical analysis. Biological fluids can be used to analyze diagnostic and prognostic markers for various diseases. In addition to ready accessibility, body fluid specimens do not require any prior knowledge of the specific organ or the specific site in an organ that might be affected by disease. Because body fluids, in particular blood, are in contact with numerous body organs, body fluids “pick up” molecular signatures indicating pathology due to secretion or cell lysis associated with a pathological condition. Body fluids also pick up molecular signatures that are suitable for evaluating drug dosage, drug targets and/or toxic effects, as disclosed herein. The invention can advantageously be used with readily accessible samples such as blood, plasma or serum.


The methods of the invention utilize the selective isolation of glycopolypeptides coupled with chemical modification to facilitate MS analysis. Proteins are glycosylated by complex enzymatic mechanisms, typically at the side chains of serine or threonine residues (O-linked) or the side chains of asparagine residues (N-linked). N-linked glycosylation sites generally fall into a sequence motif that can be described as N—X—S/T, where X can be any amino acid except proline. Glycosylation plays an important function in many biological processes (reviewed in Helenius and Aebi, Science 291:2364-2369 (2001); Rudd et al., Science 291:2370-2375 (2001)).


Protein glycosylation has long been recognized as a very common post-translational modification. As discussed above, carbohydrates are linked to serine or threonine residues (O-linked glycosylation) or to asparagine residues (N-linked glycosylation) (Varki et al. Essentials of Glycobiology Cold Spring Harbor Laboratory (1999)). Protein glycosylation, and in particular N-linked glycosylation, is prevalent in proteins destined for extracellular environments (Roth, Chem. Rev. 102:285-303 (2002)). These include proteins on the extracellular side of the plasma membrane, secreted proteins, and proteins contained in body fluids, for example, blood serum, cerebrospinal fluid, urine, breast milk, saliva, lung lavage fluid, pancreatic juice, and the like. These also happen to be the proteins in the human body that are most easily accessible for diagnostic and therapeutic purposes.


Due to the ready accessibility of body fluids exposed to the extracellular surface of cells and the presence of secreted proteins in these fluids, many clinical biomarkers and therapeutic targets are glycoproteins. These include Her2/neu in breast cancer, human chorionic gonadotropin and α-fetoprotein in germ cell tumors, prostate-specific antigen in prostate cancer, and CA125 in ovarian cancer. The Her2/neu receptor is also the target for a successful immunotherapy of breast cancer using the humanized monoclonal antibody Herceptin (Shepard et al., J. Clin. Immunol. 11:117-127 (1991)). In addition, changes in the extent of glycosylation and the carbohydrate structure of proteins on the cell surface and in body fluids have been shown to correlate with cancer and other disease states, highlighting the clinical importance of this modification as an indicator or effector of pathologic mechanisms (Durand and Seta, Clin. Chem. 46:795-805 (2000); Freeze, Glycobiology 11:129R-143R (2001); Spiro, Glycobiology 12:43R-56R (2002)). Therefore, a method for the systematic and quantitative analysis of glycoproteins would be of significance for the detection of new potential diagnostic markers and therapeutic targets.


To selectively isolate glycopolypeptides, the methods utilize chemistry and/or binding interactions that are specific for carbohydrate moieties. Selective binding of glycopolypeptides refers to the preferential binding of glycopolypeptides over non-glycosylated peptides. The methods of the invention can utilize covalent coupling of glycopolypeptides, which is particularly useful for increasing the selective isolation of glycopolypeptides by allowing stringent washing to remove non-specifically bound, non-glycosylated polypeptides.


The carbohydrate moieties of a glycopolypeptide are chemically or enzymatically modified to generate a reactive group that can be selectively bound to a solid support having a corresponding reactive group. In the embodiment depicted in FIG. 1, the carbohydrates of glycopolypeptides are oxidized to aldehydes. The oxidation can be performed, for example, with sodium periodate. The hydroxyl groups of a carbohydrate can also be derivatized by epoxides or oxiranes, alkyl halogen, carbonyldiimidazoles, N,N′-disuccinimidyl carbonates, N-hydroxycuccinimidyl chloroformates, and the like. The hydroxyl groups of a carbohydrate can also be oxidized by enzymes to create reactive groups such as aldehyde groups. For example, galactose oxidase oxidizes terminal galactose or N-acetyl-D-galactose residues to form C-6 aldehyde groups. These derivatized groups can be conjugated to amine- or hydrazide-containing moieties.


The oxidation of hydroxyl groups to aldehyde using sodium periodate is specific for the carbohydrate of a glycopeptide. Sodium periodate can oxidize hydroxyl groups on adjacent carbon atoms, forming aldehydes for coupling with amine- or hydrazide-containing molecules. Sodium periodate also reacts with hydroxylamine derivatives, compounds containing a primary amine and a secondary hydroxyl group on adjacent carbon atoms. This reaction is used to create reactive aldehydes on N-terminal serine residues of peptides. A serine residue is rare at the N-terminus of a protein. The oxidation to an aldehyde using sodium periodate is therefore specific for the carbohydrate groups of a glycopolypeptide.


Once the carbohydrate of a glycopolypeptide is modified, for example, by oxidation to aldehydes, the modified carbohydrates can bind to a solid support containing hydrazide or amine moieties, such as the hydrazide resin depicted in FIG. 1. Although illustrated with oxidation chemistry and coupling to hydrazide, it is understood that any suitable chemical modifications and/or binding interactions that allows specific binding of the carbohydrate moieties of a glycopolypeptide can be used in methods of the invention. The binding interactions of the glycopolypeptides with the solid support are generally covalent, although non-covalent interactions can also be used so long as the glycopolypeptides or glycopeptide fragments remain bound during the digestion, washing and other steps of the methods.


The methods of the invention can also be used to select and characterize subgroups of carbohydrates. Chemical modifications or enzymatic modifications using, for example, glycosidases can be used to isolate subgroups of carbohydrates. For example, the concentration of sodium periodate can be modulated so that oxidation occurs on sialic acid groups of glycoproteins. In particular, a concentration of about 1 mM of sodium periodate at 0° C. can be used to modify sialic acid groups.


Glycopolypeptides containing specific monosaccharides can be targeted using a selective sugar oxidase to generate aldehyde functions, such as the galactose oxidase described above or other sugar oxidases. Furthermore, glycopolypeptides containing a subgroup of carbohydrates can be selected after the glycopolypeptides are bound to a solid support. For example, glycopeptides bound to a solid support can be selectively released using different glycosidases having specificity for particular monosaccharide structures.


The glycopolypeptides are isolated by binding to a solid support. The solid support can be, for example, a bead, resin, membrane or disk, or any solid support material suitable for methods of the invention. An advantage of using a solid support to bind the glycopolypeptides is that it allows extensive washing to remove non-glycosylated polypeptides. Thus, in the case of complex samples containing a multitude of polypeptides, the analysis can be simplified by isolating glycopolypeptides and removing the non-glycosylated polypeptides, thus reducing the number of polypeptides to be analyzed.


The glycopolypeptides can also be conjugated to an affinity tag through an amine group, such as biotin hydrazide. The glycopeptides can be cleaved by a protease. The affinity tagged glycopeptides can then be immobilized to the solid support, for example, an avidin or streptavidin solid support, and the non-glycosylated peptides are removed. The tagged glycopeptides can be released from the solid support by enzymatic or chemical cleavage. Alternatively, the tagged glycopeptides can be released from the solid support with the oligosaccharide and affinity tag attached.


Another advantage of binding the glycopolypeptides to the solid support is that it allows further manipulation of the sample molecules without the need for additional purification steps that can result in loss of sample molecules. For example, the methods of the invention can involve the steps of cleaving the bound glycopolypeptides as well as adding an isotope tag, or other desired modifications of the bound glycopolypeptides. Because the glycopolypeptides are bound, these steps can be carried out on solid phase while allowing excess reagents to be removed as well as extensive washing prior to subsequent manipulations.


The bound glycopolypeptides can be cleaved into peptide fragments to facilitate MS analysis. Thus, a polypeptide molecule can be enzymatically cleaved with one or more proteases into peptide fragments. Exemplary proteases useful for cleaving polypeptides include trypsin, chymotrypsin, pepsin, papain, Staphylococcus aureus (V8) protease, Submaxillaris protease, bromelain, thermolysin, and the like. In certain applications, proteases having cleavage specificities that cleave at fewer sites, such as sequence-specific proteases having specificity for a sequence rather than a single amino acid, can also be used, if desired. Polypeptides can also be cleaved chemically, for example, using CNBr, acid or other chemical reagents. A particularly useful cleavage reagent is the protease trypsin. One skilled in the art can readily determine appropriate conditions for cleavage to achieve a desired efficiency of peptide cleavage.


Cleavage of the bound glycopolypeptides is particularly useful for MS analysis in that one or a few peptides are generally sufficient to identify a parent polypeptide. However, it is understood that cleavage of the bound glycopolypeptides is not required, in particular where the bound glycopolypeptide is relatively small and contains a single glycosylation site. Furthermore, the cleavage reaction can be carried out after binding of glycopolypeptides to the solid support, allowing characterization of non-glycosylated peptide fragments derived from the bound glycopolypeptide. Alternatively, the cleavage reaction can be carried out prior to addition of the glycopeptides to the solid support. One skilled in the art can readily determine the desirability of cleaving the sample polypeptides and an appropriate point to perform the cleavage reaction, as needed for a particular application of the methods of the invention.


If desired, the bound glycopolypeptides can be denatured and optionally reduced. Denaturing and/or reducing the bound glycopolypeptides can be useful prior to cleavage of the glycopolypeptides, in particular protease cleavage, because this allows access to protease cleavage sites that can be masked in the native form of the glycopolypeptides. The bound glycopeptides can be denatured with detergents and/or chaotropic agents. Reducing agents such as β-mercaptoethanol, dithiothreitol, tris-carboxyethylphosphine (TCEP), and the like, can also be used, if desired. As discussed above, the binding of the glycopolypeptides to a solid support allows the denaturation step to be carried out followed by extensive washing to remove denaturants that could inhibit the enzymatic or chemical cleavage reactions. The use of denaturants and/or reducing agents can also be used to dissociate protein complexes in which non-glycosylated proteins form complexes with bound glycopolypeptides. Thus, the use of these agents can be used to increase the specificity for glycopolypeptides by washing away non-glycosylated polypeptides from the solid support.


Treatment of the bound glycopolypeptides with a cleavage reagent results in the generation of peptide fragments. Because the carbohydrate moiety is bound to the solid support, those peptide fragments that contain the glycosylated residue remain bound to the solid support. Following cleavage of the bound glycopolypeptides, glycopeptide fragments remain bound to the solid support via binding of the carbohydrate moiety. Peptide fragments that are not glycosylated are released from the solid support. If desired, the released non-glycosylated peptides can be analyzed, as described in more detail below.


The methods of the invention can be used to identify and/or quantify the amount of a glycopolypeptide present in a sample. A particularly useful method for identifying and quantifying a glycopolypeptide is mass spectrometry (MS). The methods of the invention can be used to identify a glycopolypeptide qualitatively, for example, using MS analysis. If desired, an isotope tag can be added to the bound glycopeptide fragments, in particular to facilitate quantitative analysis by MS.


As used herein an “isotope tag” refers to a chemical moiety having suitable chemical properties for incorporation of an isotope, allowing the generation of chemically identical reagents of different mass which can be used to differentially tag a polypeptide in two samples. The isotope tag also has an appropriate composition to allow incorporation of a stable isotope at one or more atoms. A particularly useful stable isotope pair is hydrogen and deuterium, which can be readily distinguished using mass spectrometry as light and heavy forms, respectively. Any of a number of isotopic atoms can be incorporated into the isotope tag so long as the heavy and light forms can be distinguished using mass spectrometry, for example, 13C, 15N, 17O, 18O or 34S. Exemplary isotope tags include the 4,7,10-trioxa-1,13-tridecanediamine based linker and its related deuterated form, 2,2′,3,3′,11,11′,12,12′-octadeutero-4,7,10-trioxa-1,13-tridecanediamine, described by Gygi et al. (Nature Biotechnol. 17:994-999 (1999). Other exemplary isotope tags have also been described previously (see WO 00/11208, which is incorporated herein by reference).


In contrast to these previously described isotope tags related to an ICAT-type reagent, it is not required that an affinity tag be included in the reagent since the glycopolypeptides are already isolated. One skilled in the art can readily determine any of a number of appropriate isotope tags useful in methods of the invention. An isotope tag can be an alkyl, akenyl, alkynyl, alkoxy, aryl, and the like, and can be optionally substituted, for example, with O, S, N, and the like, and can contain an amine, carboxyl, sulfhydryl, and the like (see WO 00/11208). Exemplary isotope tags include succinic anhydride, isatoic-anhydride, N-methyl-isatoic-anhydride, glyceraldehyde, Boc-Phe-OH, benzaldehyde, salicylaldehyde, and the like (FIG. 2). In addition to Phe, as shown in FIGS. 2 and 3, other amino acids similarly can be used as isotope tags. Furthermore, small organic aldehydes, similar to those shown in FIG. 2, can be used as isotope tags. These and other derivatives can be made in the same manner as that disclosed herein using methods well known to those skilled in the art. One skilled in the art will readily recognize that a number of suitable chemical groups can be used as an isotope tag so long as the isotope tag can be differentially isotopically labeled.


The bound glycopeptide fragments are tagged with an isotope tag to facilitate MS analysis. In order to tag the glycopeptide fragments, the isotope tag contains a reactive group that can react with a chemical group on the peptide portion of the glycopeptide fragments. A reactive group is reactive with and therefore can be covalently coupled to a molecule in a sample such as a polypeptide. Reactive groups are well known to those skilled in the art (see, for example, Hermanson, Bioconjugate Techniques, pp. 3-166, Academic Press, San Diego (1996); Glazer et al., Laboratory Techniques in Biochemistry and Molecular Biology: Chemical Modification of Proteins, Chapter 3, pp. 68-120, Elsevier Biomedical Press, New York (1975); Pierce Catalog (1994), Pierce, Rockford Ill.). Any of a variety of reactive groups can be incorporated into an isotope tag for use in methods of the invention so long as the reactive group can be covalently coupled to the immobilized polypeptide.


To analyze a large number or essentially all of the bound glycopolypeptides, it is desirable to use an isotope tag having a reactive group that will react with the majority of the glycopeptide fragments. For example, a reactive group that reacts with an amino group can react with the free amino group at the N-terminus of the bound glycopeptide fragments. If a cleavage reagent is chosen that leaves a free amino group of the cleaved peptides, such an amino group reactive agent can label a large fraction of the peptide fragments. Only those with a blocked N-terminus would not be labeled. Similarly, a cleavage reagent that leaves a free carboxyl group on the cleaved peptides can be modified with a carboxyl reactive group, resulting in the labeling of many if not all of the peptides. Thus, the inclusion of amino or carboxyl reactive groups in an isotope tag is particularly useful for methods of the invention in which most if not all of the bound glycopeptide fragments are desired to be analyzed.


In addition, a polypeptide can be tagged with an isotope tag via a sulfhydryl reactive group, which can react with free sulfhydryls of cysteine or reduced cystines in a polypeptide. An exemplary sulfhydryl reactive group includes an iodoacetamido group (see Gygi et al., supra, 1999). Other exemplary sulfhydryl reactive groups include maleimides, alkyl and aryl halides, haloacetyls, α-haloacyls, pyridyl disulfides, aziridines, acrylolyls, arylating agents and thiomethylsulfones.


In addition, a synthetic standard polypeptide can be tagged during the peptide synthesis process using heavy isotopic labeled residues as substitution. The heavy isotope labeled residues can be any amino acids present in the peptide sequence, such as heavy isotope tagged Leu, Val, Pro, Phe, and Asp (Underlined residues in Table 5 for synthesized stable isotope tagged standard peptides). Since the N-linked Asn residues are converted to Asp during the glycopeptide capture-and-release procedure. Asp instead of Asn was incorporated into peptide sequence in peptide synthesis of the stable isotope labeled peptides.


A reactive group can also react with amines such as the α-amino group of a peptide or the E-amino group of the side chain of Lys, for example, imidoesters, N-hydroxysuccinimidyl esters (NHS), isothiocyanates, isocyanates, acyl azides, sulfonyl chlorides, aldehydes, ketones, glyoxals, epoxides (oxiranes), carbonates, arylating agents, carbodiimides, anhydrides, and the like. A reactive group can also react with carboxyl groups found in Asp or Glu or the C-terminus of a peptide, for example, diazoalkanes, diazoacetyls, carbonyldiimidazole, carbodiimides, and the like. A reactive group that reacts with a hydroxyl group includes, for example, epoxides, oxiranes, carbonyldiimidazoles, N,N′-disuccinimidyl carbonates, N-hydroxycuccinimidyl chloroformates, and the like. A reactive group can also react with amino acids such as histidine, for example, α-haloacids and amides; tyrosine, for example, nitration and iodination; arginine, for example, butanedione, phenylglyoxal, and nitromalondialdehyde; methionine, for example, iodoacetic acid and iodoacetamide; and tryptophan, for example, 2-(2-nitrophenylsulfenyl)-3-methyl-3-bromoindolenine (BNPS-skatole), N-bromosuccinimide, formylation, and sulfenylation (Glazer et al., supra, 1975). In addition, a reactive group can also react with a phosphate group for selective labeling of phosphopeptides (Zhou et al., Nat. Biotechnol., 19:375-378 (2001)) or with other covalently modified peptides, including lipopeptides, or any of the known covalent polypeptide modifications. One skilled in the art can readily determine conditions for modifying sample molecules by using various reagents, incubation conditions and time of incubation to obtain conditions suitable for modification of a molecule with an isotope tag. The use of covalent-chemistry based isolation methods is particularly useful due to the highly specific nature of the binding of the glycopolypeptides.


The reactive groups described above can form a covalent bond with the target sample molecule. However, it is understood that an isotope tag can contain a reactive group that can non-covalently interact with a sample molecule so long as the interaction has high specificity and affinity.


Prior to further analysis, it is generally desirable to release the bound glycopeptide fragments. The glycopeptide fragments can be released by cleaving the fragments from the solid support, either enzymatically or chemically. For example, glycosidases such as N-glycosidases and O-glycosidases can be used to cleave an N-linked or O-linked carbohydrate moiety, respectively, and release the corresponding de-glycosylated peptide(s). If desired, N-glycosidases and O-glycosidases can be added together or sequentially, in either order. The sequential addition of an N-glycosidase and an O-glycosidase allows differential characterization of those released peptides that were N-linked versus those that were O-linked, providing additional information on the nature of the carbohydrate moiety and the modified amino acid residue. Thus, N-linked and O-linked glycosylation sites can be analyzed sequentially and separately on the same sample, increasing the information content of the experiment and simplifying the complexity of the samples being analyzed.


In addition to N-glycosidases and O-glycosidases, other glycosidases can be used to release a bound glycopolypeptide. For example, exoglycosidases can be used. Exoglycosidases are anomeric, residue and linkage specific for terminal monosaccharides and can be used to release peptides having the corresponding carbohydrate.


In addition to enzymatic cleavage, chemical cleavage can also be used to cleave a carbohydrate moiety to release a bound peptide. For example, O-linked oligosaccharides can be released specifically from a polypeptide via a β-elimination reaction catalyzed by alkali. The reaction can be carried out in about 50 mM NaOH containing about 1 M NaBH4 at about 55° C. for about 12 hours. The time, temperature and concentration of the reagents can be varied so long as a sufficient ÿ-elimination reaction is carried out for the needs of the experiment.


In one embodiment, N-linked oligosaccharides can be released from glycopolypeptides, for example, by hydrazinolysis. Glycopolypeptides can be dried in a desiccator over P2O5 and NaOH. Anhydrous hydrazine is added and heated at about 100° C. for 10 hours, for example, using a dry heat block.


In addition to using enzymatic or chemical cleavage to release a bound glycopeptide, the solid support can be designed so that bound molecules can be released, regardless of the nature of the bound carbohydrate. The reactive group on the solid support, to which the glycopolypeptide binds, can be linked to the solid support with a cleavable linker. For example, the solid support reactive group can be covalently bound to the solid support via a cleavable linker such as a photocleavable linker. Exemplary photocleavable linkers include, for example, linkers containing o-nitrobenzyl, desyl, trans-o-cinnamoyl, m-nitrophenyl, benzylsulfonyl groups (see, for example, Dorman and Prestwich, Trends Biotech. 18:64-77 (2000); Greene and Wuts, Protective Groups in Organic Synthesis, 2nd ed., John Wiley & Sons, New York (1991); U.S. Pat. Nos. 5,143,854; 5,986,076; 5,917,016; 5,489,678; 5,405,783). Similarly, the reactive group can be linked to the solid support via a chemically cleavable linker. Release of glycopeptide fragments with the intact carbohydrate is particularly useful if the carbohydrate moiety is to be characterized using well known methods, including mass spectrometry. The use of glycosidases to release de-glycosylated peptide fragments also provides information on the nature of the carbohydrate moiety.


Glycopolypeptides from a sample are bound to a solid support via the carbohydrate moiety. The bound glycopolypeptides are generally cleaved, for example, using a protease, to generate glycopeptide fragments. As discussed above, a variety of methods can be used to release the bound glycopeptide fragments, thereby generating released glycopeptide fragments. As used herein, a “released glycopeptide fragment” refers to a peptide which was bound to a solid support via a covalently bound carbohydrate moiety and subsequently released from the solid support, regardless of whether the released peptide retains the carbohydrate. In some cases, the method by which the bound glycopeptide fragments are released results in cleavage and removal of the carbohydrate moiety, for example, using glycosidases or chemical cleavage of the carbohydrate moiety. If the solid support is designed so that the reactive group, for example, hydrazide, is attached to the solid support via a cleavable linker, the released glycopeptide fragment retains the carbohydrate moiety. It is understood that, regardless whether a carbohydrate moiety is retained or removed from the released peptide, such peptides are referred to as released glycopeptide fragments.


After isolating glycopolypeptides from a sample and cleaving the glycopolypeptide into fragments, the glycopeptide fragments released from the solid support and the released glycopeptide fragments are identified and/or quantitified. A particularly useful method for analysis of the released glycopeptide fragments is mass spectrometry. A variety of mass spectrometry systems can be employed in the methods of the invention for identifying and/or quantifying a sample molecule such as a released glycopolypeptide fragment. Mass analyzers with high mass accuracy, high sensitivity and high resolution include, but are not limited to, ion trap, triple quadrupole, and time-of-flight, quadrupole time-of-flight mass spectrometeres and Fourier transform ion cyclotron mass analyzers (FT-ICR-MS). Mass spectrometers are typically equipped with matrix-assisted laser desorption (MALDI) or electrospray ionization (ESI) ion sources, although other methods of peptide ionization can also be used. In ion trap MS, analytes are ionized by ESI or MALDI and then put into an ion trap. Trapped ions can then be separately analyzed by MS upon selective release from the ion trap. Fragments can also be generated in the ion trap and analyzed. Sample molecules such as released glycopeptide fragments can be analyzed, for example, by single stage mass spectrometry with a MALDI-TOF or ESI-TOF system. Methods of mass spectrometry analysis are well known to those skilled in the art (see, for example, Yates, J. Mass Spect. 33:1-19 (1998); Kinter and Sherman, Protein Sequencing and Identification Using Tandem Mass. Spectrometry, John Wiley & Sons, New York (2000); Aebersold and Goodlett, Chem. Rev. 101:269-295 (2001)).


For high resolution polypeptide fragment separation, liquid chromatography ESI-MS/MS or automated LC-MS/MS, which utilizes capillary reverse phase chromatography as the separation method, can be used (Yates et al., Methods Mol. Biol. 112:553-569 (1999)). Data dependent collision-induced dissociation (CID) with dynamic exclusion can also be used as the mass spectrometric method (Goodlett, et al., Anal. Chem. 72:1112-1118 (2000)).


Once a peptide is analyzed by MS/MS, the resulting CID spectrum can be compared to databases for the determination of the identity of the isolated glycopeptide. Methods for protein identification using single peptides has been described previously (Aebersold and Goodlett, Chem. Rev. 101:269-295 (2001); Yates, J. Mass Spec. 33:1-19 (1998)). In particular, it is possible that one or a few peptide fragments can be used to identify a parent polypeptide from which the fragments were derived if the peptides provide a unique signature for the parent polypeptide. Thus, identification of a single glycopeptide, alone or in combination with knowledge of the site of glycosylation, can be used to identify a parent glycopolypeptide from which the glycopeptide fragments were derived. Further information can be obtained by analyzing the nature of the attached tag and the presence of the consensus sequence motif for carbohydrate attachment. For example, if peptides are modified with an N-terminal tag, each released glycopeptide has the specific N-terminal tag, which can be recognized in the fragment ion series of the CID spectra. Furthermore, the presence of a known sequence motif that is found, for example, in N-linked carbohydrate-containing peptides, that is, the consensus sequence NXS/T, can be used as a constraint in database searching of N-glycosylated peptides.


In addition, the identity of the parent glycopolypeptide can be determined by analysis of various characteristics associated with the peptide, for example, its resolution on various chromatographic media or using various fractionation methods. These empirically determined characteristics can be compared to a database of characteristics that uniquely identify a parent polypeptide, which defines a peptide tag.


The use of a peptide tag and related database is used for identifying a polypeptide from a population of polypeptides by determining characteristics associated with a polypeptide, or a peptide fragment thereof, comparing the determined characteristics to a polypeptide identification index, and identifying one or more polypeptides in the polypeptide identification index having the same characteristics (see WO 02/052259). The methods are based on generating a polypeptide identification index, which is a database of characteristics associated with a polypeptide. The polypeptide identification index can be used for comparison of characteristics determined to be associated with a polypeptide from a sample for identification of the polypeptide. Furthermore, the methods can be applied not only to identify a polypeptide but also to quantitate the amount of specific proteins in the sample.


The incorporation of an isotope tag can be used to facilitate quantification of the sample glycopolypeptides. As disclosed previously, the incorporation of an isotope tag provides a method for quantifying the amount of a particular molecule in a sample (Gygi et al., supra, 1999; WO 00/11208). In using an isotope tag, differential isotopes can be incorporated, which can be used to compare a known amount of a standard labeled molecule having a differentially labeled isotope tag from that of a sample molecule, as described in more detail below. Thus, a standard peptide having a differential isotope can be added at a known concentration and analyzed in the same MS analysis or similar conditions in a parallel MS analysis. A specific, calibrated standard can be added with known absolute amounts to determine an absolute quantity of the glycopolypeptide in the sample. In addition, the standards can be added so that relative quantitation is performed, as described below.


Alternatively, parallel glycosylated sample molecules can be labeled with a different isotopic label and compared side-by-side (see Gygi et al., supra, 1999). This is particularly useful for qualitative analysis or quantitative analysis relative to a control sample. For example, a glycosylated sample derived from a disease state can be compared to a glycosylated sample from a non-disease state by differentially labeling the two samples, as described previously (Gygi et al., supra, 1999). Such an approach allows detection of differential states of glycosylation, which is facilitated by the use of differential isotope tags for the two samples, and can thus be used to correlate differences in glycosylation as a diagnostic marker for a disease.


The methods of the invention provide numerous advantages for the analysis of complex biological and clinical samples. From every glycoprotein present in a complex sample, only a few peptides will be isolated since only a few peptides of a glycoprotein are glycosylated. Therefore, by isolating glycopeptide fragments, the composition of the resulting peptide mixture is significantly simplified for mass spectrometric analysis. For example, every protein on average will produce dozens of tryptic peptides but only one to a few tryptic glycosylated peptides. For example, the number of glycopeptides is significantly lower than the number of tryptic peptides or Cys-containing peptides in the major plasma proteins. Thus, analysis of glycopolypeptides or glycopeptides reduces the complexity of complex biological samples, for example, serum.


Another advantage of the methods of the invention is the use for analysis of body fluids as a clinical specimen, in particular serum. Five major plasma proteins represent more than 80% of the total protein in plasma, albumin, α1 antitrypsin, α2 macroglobulin, transferrin, and γ-globulins. Of these, albumin is the most abundant protein in blood serum and other body fluids, constituting about 50% of the total protein in plasma. However, albumin is essentially transparent to the methods of the invention due to the lack of N-glycosylation. For example, no tryptic. N-glycosylated peptides from albumin were observed when the methods of the invention were applied and a N-glycosidase was used to release the N-linked glycopeptides. This is all the more significant because more than 50 different albumin species have been detected by 2D gel electrophoresis that collectively obscure a significant part of the gel pattern and the analysis of less abundant serum proteins having clinical significance. Therefore, the methods of the invention that allow analysis of glycosylated proteins compensate for the dominance of albumin in serum and allow the analysis of less abundant, glycosylated proteins present in serum. As disclosed herein, the methods of the invention allowed the identification of many more serum proteins compared to conventional methods. The methods of the invention also allow the analysis of less abundant serum proteins. These low abundance serum proteins are potential diagnostic markers. Such markers can be readily determined by comparing disease samples with healthy samples, as disclosed herein.


Additionally, the known sequence motif for N-glycosylation (N—X—S/T) serves as a powerful sequence database search contraint for the identification of the isolated peptides. This can be used to facilitate the identification of the polypeptide from which the glycopeptide fragment was derived since a smaller number of possible peptides will contain the glycosylation motif.


The methods of the invention are also advantageous because they allow fast throughput and simplicity. Accordingly, the methods can be readily adapted for high throughput analysis of samples, which can be particularly advantageous for the analysis of clinical samples. Furthermore, the methods of the invention can be automated to facilitate the processing of multiple samples. As disclosed herein, a robotic workstation has been adapted for automated glycoprotein analysis.


As described above, non-glycosylated peptide fragments are released from the solid support after proteolytic or chemical cleavage. If desired, the released peptide fragments can be characterized to provide further information on the nature of the glycopolypeptides isolated from the sample. A particularly useful method is the use of the isotope-coded affinity tag (ICAT™) method (Gygi et al., Nature Biotechnol. 17:994-999 (1999) which is incorporated herein by reference). The ICAT™ type reagent method uses an affinity tag that can be differentially labeled with an isotope that is readily distinguished using mass spectrometry. The ICAT™ type affinity reagent consists of three elements, an affinity tag, a linker and a reactive group.


One element of the ICAT™ type affinity reagent is an affinity tag that allows isolation of peptides coupled to the affinity reagent by binding to a cognate binding partner of the affinity tag. A particularly useful affinity tag is biotin, which binds with high affinity to its cognate binding partner avidin, or related molecules such as streptavidin, and is therefore stable to further biochemical manipulations. Any affinity tag can be used so long as it provides sufficient binding affinity to its cognate binding partner to allow isolation of peptides coupled to the ICAT™ type affinity reagent. An affinity tag can also be used to isolate a tagged peptide with magnetic beads or other magnetic format suitable to isolate a magnetic affinity tag. In the ICAT™ type reagent method, or any other method of affinity tagging a peptide, the use of covalent trapping, for example, using a cross-linking reagent, can be used to bind the tagged peptides to a solid support, if desired.


A second element of the ICAT™ type affinity reagent is a linker that can incorporate a stable isotope. The linker has a sufficient length to allow the reactive group to bind to a specimen polypeptide and the affinity tag to bind to its cognate binding partner. The linker also has an appropriate composition to allow incorporation of a stable isotope at one or more atoms. A particularly useful stable isotope pair is hydrogen and deuterium, which can be readily distinguished using mass spectrometry as light and heavy forms, respectively. Any of a number of isotopic atoms can be incorporated into the linker so long as the heavy and light forms can be distinguished using mass spectrometry. Exemplary linkers include the 4,7,10-trioxa-1,13-tridecanediamine based linker and its related deuterated form, 2,2′,3,3′,11,11′,12,12′-octadeutero-4,7,10-trioxa-1,13-tridecanediamine, described by Gygi et al. (supra, 1999). One skilled in the art can readily determine any of a number of appropriate linkers useful in an ICAT™ type affinity reagent that satisfy the above-described criteria, as described above for the isotope tag.


The third element of the ICAT™ type affinity reagent is a reactive group, which can be covalently coupled to a polypeptide in a specimen. Various reactive groups have been described above with respect to the isotope tag and can similarly be incorporated into an ICAT-type reagent.


The ICAT™ method or other similar methods can be applied to the analysis of the non-glycosylated peptide fragments released from the solid support. Alternatively, the ICAT™ method or other similar methods can be applied prior to cleavage of the bound glycopolypeptides, that is, while the intact glycopolypeptide is still bound to the solid support.


The method generally involves the steps of automated tandem mass spectrometry and sequence database searching for peptide/protein identification; stable isotope tagging for quantification by mass spectrometry based on stable isotope dilution theory; and the use of specific chemical reactions for the selective isolation of specific peptides. For example, the previously described ICAT™ reagent contained a sulfhydryl reactive group, and therefore an ICAT™-type reagent can be used to label cysteine-containing peptide fragments released from the solid support. Other reactive groups, as described above, can also be used.


The analysis of the non-glycosylated peptides, in conjunction with the methods of analyzing glycosylated peptides, provides additional information on the state of polypeptide expression in the sample. By analyzing both the glycopeptide fragments as well as the non-glycosylated peptides, changes in glycoprotein abundance as well as changes in the state of glycosylation at a particular glycosylation site can be readily determined.


If desired, the sample can be fractionated by a number of known fractionation techniques. Fractionation techniques can be applied at any of a number of suitable points in the methods of the invention. For example, a sample can be fractionated prior to oxidation and/or binding of glycopolypeptides to a solid support. Thus, if desired, a substantially purified fraction of glycopolypeptide(s) can be used for immobilization of sample glycopolypeptides. Furthermore, fractionation/purification steps can be applied to non-glycosylated peptides or glycopeptides after release from the solid support. One skilled in the art can readily determine appropriate steps for fractionating sample molecules based on the needs of the particular application of methods of the invention. In the case of a blood sample, one skilled in the art can readily use well known methods for processing the blood, for example, to obtain plasma or serum.


Methods for fractionating sample molecules are well known to those skilled in the art. Fractionation methods include but are not limited to subcellular fractionation or chromatographic techniques such as ion exchange, including strong and weak anion and cation exchange resins, hydrophobic and reverse phase, size exclusion, affinity, hydrophobic charge-induction chromatography, dye-binding, and the like (Ausubel et al., Current Protocols in Molecular Biology (Supplement 56), John Wiley & Sons, New York (2001); Scopes, Protein Purification: Principles and Practice, third edition, Springer-Verlag, New York (1993)). Other fractionation methods include, for example, centrifugation, electrophoresis, the use of salts, and the like (see Scopes, supra, 1993). In the case of analyzing membrane glycoproteins, well known solubilization conditions can be applied to extract membrane bound proteins, for example, the use of denaturing and/or non-denaturing detergents (Scopes, supra, 1993).


Affinity chromatography can also be used including, for example, dye-binding resins such as Cibacron blue, substrate analogs, including analogs of cofactors such as ATP, NAD, and the like, ligands, specific antibodies useful for immuno-affinity isolation, either polyclonal or monoclonal, and the like. A subset of glycopolypeptides can be isolated using lectin affinity chromatography, if desired. An exemplary affinity resin includes affinity resins that bind to specific moieties that can be incorporated into a polypeptide such as an avidin resin that binds to a biotin tag on a sample molecule labeled with an ICAT™-type reagent. The resolution and capacity of particular chromatographic media are known in the art and can be determined by those skilled in the art. The usefulness of a particular chromatographic separation for a particular application can similarly be assessed by those skilled in the art.


Those of skill in the art will be able to determine the appropriate chromatography conditions for a particular sample size or composition and will know how to obtain reproducible results for chromatographic separations under defined buffer, column dimension, and flow rate conditions. The fractionation methods can optionally include the use of an internal standard for assessing the reproducibility of a particular chromatographic application or other fractionation method. Appropriate internal standards will vary depending on the chromatographic medium or the fractionation method used. Those skilled in the art will be able to determine an internal standard applicable to a method of fractionation such as chromatography. Furthermore, electrophoresis, including gel electrophoresis or capillary electrophoresis, can also be used to fractionate sample molecules.


The methods of the invention can be used in a wide range of applications in basic and clinical biology. The methods of the invention can be used for the detection of changes in the profile of proteins expressed in the plasma membrane, changes in the composition of proteins secreted by cells and tissues, changes in the protein composition of body fluids including blood and seminal plasma, cerebrospinal fluid, pancreatic juice, urine, breast milk, lung lavage, and the like. In a particular embodiment, the methods are used to identify and/or quantify glycopolypeptides in a blood, plasma or serum sample, in particular a human sample. Since many of the proteins in these samples are glycosylated, the methods of the invention allow the convenient analysis of glycoproteins in these samples. Detected changes observed in a disease state can be used as diagnostic or prognostic markers for a wide range of diseases, including congenital disorders of glycosylation or any disorder involving aberrant glycosylation; cancer, such as skin, prostate, breast, colon, lung, and others; metabolic diseases or processes such as diabetes or changes in physiological state; inflammatory diseases such as rheumatoid arthritis; mental disorders or neurological processes; infectious disease; immune response to pathogens; and the like. Furthermore, the methods of the invention can be used for the identification of potential targets for a variety of therapies including antibody-dependent cell cytotoxicity directed against cell surface proteins and for detection of proteins accessible to drugs.


Thus, the methods of the invention can be used to identify diagnostic markers for a disease by comparing a sample from a patient having a disease to a sample from a healthy individual or group of individuals. By comparing disease and healthy samples, a diagnostic pattern can be determined with increases or decreases in expression of particular glycopolypeptides correlated with the disease, which can be used for subsequent analysis of samples for diagnostic purposes. The methods are based on analysis of glycopolypeptides, and such an analysis is sufficient for diagnostic purposes.


Thus, the invention provides a method for identifying diagnostic glycopolypeptide markers by using a method of the invention and comparing samples from diseased individual(s) to healthy individual(s) and identifying glycopolypeptides having differential expression between the two samples, whereby differences in expression indicates a correlation with the disease and thus can function as a diagnostic marker. The invention also provides the diagnostic markers identified using methods of the invention.


Furthermore, glycopolypeptides exhibiting differential expression are potential therapeutic targets. Because they are differentially expressed, modulating the activity of these glycopolypeptides can potentially be used to ameliorate a sign or symptom associated with the disease. Thus, the invention provides a method for identifying therapeutic glycopolypeptide targets of a disease. Once a glycopolypeptide is found to be differentially expressed, the potential target can be screened for potential therapeutic agents that modulate the activity of the therapeutic glycopolypeptide target. Methods of generating libraries and screening the libraries for potential therapeutic activity are well known to those skilled in the art. Methods for producing pluralities of compounds, including chemical or biological molecules such as simple or complex organic molecules, metal-containing compounds, carbohydrates, peptides, proteins, peptidomimetics, glycoproteins, lipoproteins, nucleic acids, antibodies, and the like, are well known in the art (see, for example, in Huse, U.S. Pat. No. 5,264,563; Francis et al., Curr. Opin. Chem. Biol. 2:422-428 (1998); Tietze et al., Curr. Biol., 2:363-371 (1998); Sofia, Mol. Divers. 3:75-94 (1998); Eichler et al., Med. Res. Rev. 15:481-496 (1995); Gordon et al., J. Med. Chem. 37: 1233-1251 (1994); Gordon et al., J. Med. Chem. 37: 1385-1401 (1994); Gordon et al., Acc. Chem. Res. 29:144-154 (1996); Wilson and Czarnik, eds., Combinatorial Chemistry Synthesis and Application, John Wiley & Sons, New York (1997)). The invention additionally provides glycopolypeptide therapeutic targets identified by methods of the invention.


The methods can be used for a variety of clinical and diagnostic applications. Known therapeutic methods effected through glycopolypeptides can be characterized by methods of the invention. For example, therapies such as Enbrel™ and Herceptin function through glycoproteins. The methods of the invention allow characterization of individual patients with respect to glycoprotein expression, which can be used to determine likely efficacy of therapy involving glycoproteins.


Thus, the methods of the invention can be used in a variety of applications including, but not limited to, the following applications. The methods of the invention can be used, for example, for blood serum profiling for the detection of prognostic and diagnostic protein markers.


The methods of the invention are applicable in clinical and diagnostic medicine, veterinary medicine, agriculture, and the like. For example, the methods of the invention can be used to identify and/or validate drug targets and to evaluate drug efficacy, drug dosing, and/or drug toxicity. In such a case, the blood proteome, that is serum, can be analyzed using the methods disclosed herein to look for changes in serum glycopolypeptide profiles associated with drug administration and correlated with the effects of drug efficacy, dosing and/or toxicity, and/or validation of drug targets. Such a correlation can be readily determined by collecting serum samples from one or more individuals adminstered various drug doses, experiencing drug toxicity, experiencing a desired efficacy, and the like. In addition, a plasma or serum profile can be generated in combination with the analysis of drug targets as a way to rapidly and efficiently validate a particular target with the administration of a drug or various drug doses, toxicity, and the like. Thus, serum, plasma or blood samples provide a surrogate marker for the status of an individual and his or her ability to respond to a pharmacological intervention.


The methods of the invention can additionally be used for quantitative protein profiling in various body fluids in addition to blood plasma, including CSF, pancreatic juice, lung lavage fluid, seminal plasma, urine, breast milk, and the like. The methods of the invention can also be used for quantitative protein profiling of proteins secreted by cells or tissues for the detection of new protein and peptide hormones and other factors. Thus, the invention provides a method to generate quantitative profiles of glycoproteins. The invention also provides a method for quantifying a glycopolypeptide in a sample, as disclosed herein. The invention further provides a method for the detection of prognostic or diagnostic patterns in blood, serum or plasma and other body fluids. The invention additionally provides a method for the detection of secreted protein hormones and regulatory factors. Thus, the invention provides a method for profiling glycopolypeptides from body fluids.


The methods of the invention are also applicable to the detection of changes in the state of glycosylation of proteins based on the concurrent application of protein abundance measurement and measurement of protein glycosylation on the same sample. Thus, the invention provides a method to detect quantitative changes in the glycosylation pattern of specific proteins.


Although the methods disclosed herein have generally been described for the analysis of glycopolypeptides, similar methods are also applicable to the analysis of other carbohydrate-containing molecules. Because the methods are based on the specific binding of carbohydrate moieties, the methods of modification and/or isolation can similarly be applied to other carbohydrate-containing molecules. For example, method steps analogous to those disclosed herein can be applied to the identification and quantification of glycosylated molecules such as glycolipids, glycosphingolipids, and the like.


The invention also provides a composition comprising a plurality of peptides containing the glycosylation sites shown in Tables 7, 8 and/or 10 and referenced as SEQ ID NOS: 1-3482, wherein the peptides each correspond to peptide fragments derived by cleavage of polypeptides using the same cleavage reagent. In one embodiment, the cleavage reagent can be a protease, for example, trypsin.


The invention additionally provides a kit comprising a plurality of peptides containing the glycosylation sites shown in Tables 7, 8 and/or 10 and referenced as SEQ ID NOS: 1-3482, wherein the peptides each correspond to peptide fragments derived by cleavage of polypeptides using the same cleavage reagent. The kit can further comprise a pair of differentially labeled isotope tags. In addition, the kit can further comprise the cleavage reagent corresponding to the peptide fragments, for example, a protease such as trypsin or other proteases disclosed herein. Additionally, the kit can further comprise a hydrazide resin. Also, a kit of the invention can further comprise a glycosidase.


The contents of the kit of the invention, for example, any resins or labeling reagents, are contained in suitable packaging material, and, if desired, a sterile, contaminant-free environment. In addition, the packaging material contains instructions indicating how the materials within the kit can be employed to label sample molecules. The instructions for use typically include a tangible expression describing the reagent concentration or at least one assay method parameter, such as the relative amounts of reagent and sample to be admixed, maintenance time periods for reagent/sample admixtures, temperature, buffer conditions, and the like.


The test sample can be, for example, a specimen from an individual having a disease. The control sample can be, for example, a corresponding specimen obtained from a healthy individual, also referred to herein as a normal sample. The sample can be, for example, serum or a tissue biopsy, as described herein. Differential glycosylation can be a qualitative difference, for example, the presence or absence of a glycopolypeptide in the test sample compared to the control sample. Differential glycosylation can also be a quantitative difference. The determination of quantitative differences can be facilitated by the labeling with differential isotope tags such that the samples can be mixed and compared side-by-side, as disclosed herein and described in Gygi et al., supra, 1999. One or more glycopolypeptides exhibiting differential glycosylation are potential diagnostic markers for the respective disease. Such a method provides a glycopolypeptide disease profile, which can be used subsequently for diagnostic purposes. Accordingly, rather than using one or a few diagnostic markers, the methods of the invention allow the identification of a profile of diagnostic markers, which can provide more detailed information on the type of disease, the stage of disease, and/or the prognosis of a disease by determining profiles correlated with the type, stage and/or prognosis of a disease.


In yet another embodiment, the invention provides a method of diagnosing a disease. The method can include the steps of immobilizing glycopolypeptides from a test sample to a solid support; cleaving the immobilized glycopolypeptides, thereby releasing non-glycosylated peptides and retaining immobilized glycopeptides; releasing the glycopeptides from the solid support; analyzing the released glycopeptides; and identifying one or more diagnostic markers associated with a disease, for example, as determined by methods of the invention, as described above.


A test sample from an individual to be tested for a disease or suspected of having a disease can be processed as described for glycopeptide analysis by the methods disclosed herein. The resulting glycopeptide profile from the test sample can be compared to a control sample to determine if changes in glycosylation of diagnostic markers has occurred, as discussed above. Alternatively, the glycopeptide profile can be compared to a known set of diagnostic markers or a database containing information on diagnostic markers.


In another embodiment, the method of diagnosing a disease can include the step of generating a report on the results of the diagnostic test. For example, the report can indicate whether an individual is likely to have a disease or is likely to be disease free based on the presence of a sufficient number of diagnostic markers associated with a disease. The invention further provides a report of the outcome of a method of diagnosing a disease. Similar reports and preparation of such reports are provided for other methods of the invention.


It is understood that the methods of the invention can be performed in any order suitable for glycopolypeptide analysis. One skilled in the art can readily determine an appropriate order of carrying out steps of methods of the invention suitable for qualitative and quantitative glycopeptide analysis.


As disclosed herein, serum proteins contain enormous information about the health of an individual while blood circulates in the body, and proteomic profiling of serum proteins by mass spectrometry can be a powerful approach for biomarker identification and disease detection. Conventional total tryptic peptide analysis of serum proteins is dominated by the appearance of the 22 most abundant proteins, which represent 99% of total plasma content and produce over one thousand peptides. The dominance of the most abundant proteins makes it extremely challenging to access the low abundance proteins and makes it difficult to identify biomarkers among the low abundance proteins.


Considering that most serum proteins are N-link glycosylated at one or a few tryptic peptides but the most abundant protein, albumin, is not, profiling sera using N-linked glycopeptides and liquid chromatography mass spectrometry (LC-MS) was chosen to achieve high sensitivity and throughput for low abundance serum proteins. As disclosed herein, using this method, over 4000 peptide peaks were detected using sera from normal and carcinogen induced skin cancer mice by two-hour LC-MS analysis (see Example 2). Peptide peaks from LC-MS analysis clearly separated sera of the cancer mice from the normal untreated mice using unsupervised clustering algorithms. The glycopeptides that were elevated in cancer mice were identified using tandem mass spectrometry after isotope labeling the glycopeptides at the amino termini. The combination of glycopeptide capture and LC-MS analysis (glyMS) greatly simplifies the complexity of serum profiling and increases the sensitivity and throughput for low abundance proteins over the total tryptic peptide analysis method.


Using this method, over 4000 peptide peaks were detected using sera from normal and carcinogen induced skin cancer mice by two-hour LC-MS analysis (see Example 2). Peptide peaks from LC-MS analysis clearly separated sera of the cancer mice from the normal untreated mice using unsupervised clustering algorithms. The glycopeptides that were elevated in cancer mice were identified using tandem mass spectrometry after labeling the glycopeptides with isotope at the amino termini. The combination of glycopeptide capture and LC-MS analysis (glyMS) greatly simplifies the complexity of serum profiling and increases the sensitivity and throughput for low abundance proteins over the total tryptic peptide analysis method.


It is expected that the composition of the serum proteome can provide valuable information about the state of the human body in health and disease, and that this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to, be sensitive, reproducible and robust to detect potential biomarkers below the level of highly expressed proteins, to generate data sets that are comparable between experiments and laboratories, and have high throughput to support statistical studies. Disclosed herein is a method for high throughput quantitative analysis of serum proteins (see Example 2). It consists of the selective isolation of peptides that are N-linked glycosylated in the intact protein, the analysis of these, now de-glycosylated peptides by LC-ESI (electrospray ionization)-MS, and the comparative analysis of the resulting patterns. By focusing selectively on a few formerly N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced and the sensitivity and throughput of serum proteome analysis are increased compared with the analysis of total tryptic peptides from unfractionated samples. Data are provided that document the performance of the method and show that sera from untreated normal mice and genetically identical mice with carcinogen induced skin cancer can be unambiguously discriminated using unsupervised clustering of the resulting peptide patterns. Some of the peptides that were consistently elevated in cancer mice compared to their control littermates were identified by tandem mass spectrometry.


There is growing interest in testing the hypothesis that the serum or plasma proteome contains protein biomarkers that are useful for classifying the physiological or pathological status of an individual. Such markers are expected to be useful for the prediction, detection and diagnosis of disease, as well as to follow the efficacy, toxicology and side effects of drug treatment (Wulfkuhle et al., Nat. Rev. Cancer 3:267-275 (2003)). Reading diagnostic or prognostic signatures from human body fluids has been performed. Early attempts using high resolution two dimensional gel electrophoresis (2DE) were described more than 2 decades ago (Anderson and Anderson, Proc. Natl. Acad. Sci. USA 74:5421-5425 (1977); Merril et al., Science 211:1437-1438 (1981); Merril et al., Proc. Natl. Acad. Sci. USA 76:4335-4339 (1979)). Renewed interest in this idea has emerged due to recent advances in proteomic technologies (Aebersold and Mann, Nature 422:198-207 (2003)), intriguing initial results from analyzing serum protein patterns using mass spectrometry (Wulfkuhle et al., Nat. Rev. Cancer 3:267-275 (2003)), and the clinical validation and use of a number of diagnostic disease markers, including CA125 for ovarian cancer, prostate specific antigen (PSA) for prostate cancer and carcinoembryonic antigen (CEA) for colon, breast, pancreatic and lung cancer (Diamandis, Mol. Cell. Proteomics 3:367-378 (2004).


A number of new approaches that differ from the traditional 2DE method for the discovery of protein biomarkers in serum have recently been described (Wulfkuhle et al., Nat. Rev. Cancer 3:267-275 (2003)). These include surface enhanced laser desorption ionization mass spectrometry (SELDI-MS) (Petricoin et al., Lancet 359:572-577 (2002)), liquid chromatography tandem mass spectrometry (LC-MS/MS) of serum proteome digests (Adkins et al., Mol. Cell. Proteomics 1:947-955 (2002); Tirumalai et al., Mol. Cell. Proteomics 2:1096-1103 (2003); Shen et al., Anal. Chem. 76:1134-1144 (2004), two or three dimensional (chromatography/gel electrophoresis) protein separation analyzed by differential fluorescent staining (Wang and Hanash, J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 787:11-18 (2003); Shin et al., J. Mammary Gland Biol. Neoplasia 7:407-413 (2002)), fractionation of the serum proteome on surface-modified magnetic beads followed by matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) (Villanueva et al., Anal. Chem. 76:1560-1570 (2004)), and combinations and variations of these approaches.


Any study of the serum proteome is confronted with the peculiar properties of serum samples. First, human blood serum is assumed to consist of minimally tens of thousands of different protein species that span a concentration range of an estimated 10 orders of magnitude (Anderson and Anderson, Mol. Cell. Proteomics 1:845-867 (2002)). Second, the serum proteome is dominated by a few highly abundant proteins, that is, the 22 most abundant human serum proteins combined constitute 99% of total protein mass (Tirumalai et al., Mol. Cell. Proteomics 2:1096-1103 (2003)). Indeed, almost one half of total serum protein mass is represented by just one protein, albumin. Third, many of the serum proteins show complex 2D electrophoretic patterns, suggesting that they are extensively post-translationally modified, with glycosylation apparently being the major source of protein heterogeneity (Anderson and Anderson, Mol. Cell. Proteomics 1:845-867 (2002)). In fact, when protein spots from 2D electropherograms of serum were systematically identified by mass spectrometry, 5-7 protein spots on average were identified as products of the same gene (Pieper et al., R., Proteomics 3:1345-1364 (2003). Fourth, the serum proteome varies over time in an individual and among individuals in a population.


Useful platforms for serum proteome analysis should thus have minimally the following properties: first, sufficient analytical depth to reliably detect relatively low abundance proteins; second, quantitative accuracy to determine changes in the proteome pattern; third, reproducibility and robustness to detect disease-specific changes in a background of pattern changes unrelated to disease; fourth, the ability to identify distinct peptides for their cross-validation on different analytical platforms and comparison of results obtained from different research groups, studies and diseases; and fifth, high sample throughput to support studies with sufficient statistical power.


Disclosed herein (Example 2) is a method for quantitative serum proteome analysis. It is based on the selective isolation of those peptides from serum proteins that are N-linked glycosylated in the native protein, and the analysis of the complex peptide mixture representing the now de-glycosylated forms of these peptides by liquid chromatography mass spectrometry (LC-MS) and tandem mass spectrometry (MS/MS). By selectively isolating this subset of peptides, the procedure achieves a significant reduction in analyte complexity at two levels: first, a reduction of the total number of peptides due to the fact that every serum protein on average only contains a few N-linked glycosylation sites, and second, a reduction of pattern complexity by removing the oligosaccharides that contribute significantly to the peptide pattern heterogeneity. The method is reproducible, achieves increased analytical depth and higher throughput compared to the analysis of samples without selective analyte enrichment. Furthermore, in a controlled experiment, peptide patterns distinguishing the serum proteome of cancer-bearing mice from genetically identical untreated normal mice could be detected and discriminatory peptides could be subsequently identified. At present, this method affords one of the most comprehensive routine and high throughput analyses of the serum proteome. The methods are useful in a broad application in serum marker discovery research.


Mass spectrometry based proteomics is becoming one of the most important approaches for quantitative characterization of the function of biological systems. Due to the enormous complexity of the proteomes, the development of high throughput technologies capable of detecting and quantifying specific information-rich proteins is crucial for its applications in biotechnology, such as clinical diagnostics, drug metabolism studies, and improving the knowledge of fundamental biological processes. Disclosed herein is a novel approach for quantitative proteomics that builds on the extensive knowledge of proteomes, and a platform for the implementation of the concept (see Example 4). The disclosed analysis is related to serum analysis. The highly selective, high throughput platform is built based on a MALDI (matrix assisted laser desorption/ionization) TOF/TOF (time-of-flight) spectrometer and using stable isotope labeled peptides as internal standards. For each targeted protein, one (or more) peptide sequence that uniquely identifies the protein is selected, chemically synthesized and labeled with heavy stable isotope. The synthesized stable isotope labeled peptides were used as definitive signatures to represent the corresponding targeted proteins and spiked in the serum sample with known amounts. The detection and quantification of targeted proteins was accomplished using a complementary approach of specific mass matching, selective peptide sequencing and peptide quantification. The study has experimentally demonstrated the concept and feasibility of using mass spectrometry based proteomics as a screening technology for systematic detection and quantification of targeted proteins in a complex system at high throughput.


The comprehensive, quantitative analysis of proteomes is informative and challenging. It is informative because the comparative analysis of proteomes or fractions thereof identifies proteins that are present at different quantities in the samples compared. Such differences in turn have been used to identify cellular functions and pathways affected by perturbations and disease (Wright et al., Genome Biol. 5:R4 (2003); Flory and Aebersold, Prog. Cell Cycle Res. 5:167-171 (2003); Guina et al., T., Wu, M., Miller, S. I., Purvine, S. O., Yi, E. C., Eng, J. et al. J. Am. Soc. Mass Spectrom. 14:742-751 (20.03); Aebersold, Nature 422:115-116 (2003); Flory et al., M. R., Griffin, T. J., Martin, D. and Aebersold, Trends Biotechnol. 20:S23-29 (2002); Shiio, Y., Donohoe, S., Yi, E. C., Goodlett, D. R., Aebersold, R. and Eisenman, R. N. EMBO J. 21:5088-5096 (2002); Rabilloud et al., J. Biol. Chem. 277:19396-19401 (2002)), identify new components and changes in the composition of protein complexes and organelles (Brand et al., Nat. Struct. Mol. Biol. 11:73-80 (2004); Himeda et al., Mol. Cell. Biol. 24:2132-2143 (2004); Ranish et al., Nat. Genet. 36:707-713 (2004); Ranish, J. A., Yi, E. C., Leslie, D. M., Purvine, S. O., Goodlett, D. R., Eng, J. et al. Nat. Genet. 33:349-355 (2003); Aebersold, J. Am. Soc. Mass Spectrom. 14:685-695 (2003); Aebersold, J. Infect. Dis. 187 Suppl 2:S315-320 (2003); Patterson and Aebersold, Nat. Genet. 33 Suppl, 311-323 (2003); Griffin et al., Anal. Chem. 75, 867-874 (2003)) and have led to the detection of putative disease biomarkers Hale et al., Brief Funct. Genomic Proteomic 2:185-193 (2003); Shau et al., Brief Funct Genomic Proteomic 2:147-158 (2003)). Comprehensive proteome analysis is challenging because of the enormous complexity of the proteome. In comparison to the number of open reading frames in a genome the number of unique protein species expressed by it is vastly expanded by the action of post transcriptional processing mechanisms including protein modifications, alternative splicing and proteolytic processing. Consequently, to date, neither the complexity of a proteome nor its actual composition has been determined for any species.


Over the last few years a number of mass spectrometry-based quantitative proteomics methods have been developed that identify the proteins contained in each sample and determine the relative abundance of each identified protein across samples (Flory et al., Trends Biotechnol. 20:S23-29 (2002); Aebersold, J. Am. Soc. Mass Spectrom. 14:685-695 (2003); Aebersold, J. Infect. Dis. 187 Suppl 2:S315-320 (2003); Patterson and Aebersold, Nat. Genet. 33 Suppl, 311-323 (2003); Aebersold and Mann, Nature 422:198-207 (2003); Aebersold, R. and Cravatt, Trends Biotechnol. 20:S1-2 (2002); Aebersold and Goodlett, Chem. Rev. 101, 269-295 (2001); Tao and Aebersold, Curr. Opin. Biotechnol. 14:110-118 (2003)). Generally, the proteins in each sample are labeled to acquire an isotopic signature that identifies their sample of origin and provides the basis for accurate mass spectrometric quantification. Samples with different isotopic signatures are then combined and analyzed, typically by multidimensional chromatography tandem mass spectrometry. The resulting collision induced dissociation (CID) spectra are then assigned to peptide sequences and the relative abundance of each detected protein in each sample is calculated based on the relative signal intensities for the differentially isotopically labeled peptides of identical sequence. Therefore, in a single operation the identity of the proteins contained in the samples and their relative abundance are determined. While the methods differ in the way the stable isotopes are incorporated into the polypeptides and the precise analytical (separation; mass spectrometry; data processing) methods used, they have in common that in every experiment results are only obtained from those peptides for which in the tandem mass spectrometry (MS/MS) experiment precursor ions are selected, successfully fragmented and conclusively assigned to a peptide sequence. Therefore, in every proteomics experiment of this kind the proteome is rediscovered without the benefit of the data collected from prior experiments. Furthermore, it has previously been shown that this type of proteomic analysis is quite inefficient in that the number of successfully identified and quantified peptides is about an order of magnitude lower than the number of detectable peptides present in the sample (Li et al., Anal. Chem. 76:3856-3860 (2004)) and that it is biased towards the proteins of higher abundance Nesvizhskii and Aebersold, Drug Discov. Today 9:173-181 (2004); Nesvizhskii et al., Anal. Chem. 75:4646-4658 (2003); Keller et al., Anal. Chem. 74:5383-5392 (2002)).


In many studies it is necessary to analyze a large number of proteomes and to compare the results obtained from each analysis. In biomarker discovery studies for example, large numbers of samples are required to detect protein patterns that consistently associate with a specific condition within a large background of proteins that may randomly fluctuate within the population tested (Aebersold, Nature 422:115-116 (2003); Domon and Broder, J. Proteome Res. 3:253-260 (2004)). In the emerging field of systems biology, a key element is the quantitatively accurate and comprehensive measurement of the components that constitute the system in differentially perturbed states and the synthesis of these data into a model describing the system (Adv. Exp. Med. Biol. 547:21-30 (2004)). Therefore, it is essential that quantitative proteomics experiments can be carried out at high throughput.


Genomics-style biology can be separated into two distinct phases, a discovery phase in which all the possible elements of one type are discovered, and a browsing or screening phase, in which the list of all possible or known elements is searched for those that may be of interest in a particular study (Aebersold, Nature 422:115-116 (2003)). The transition from a discovery to a browsing mode of operation has been already implemented for genomic sequencing, gene expression array analysis and the analysis of single nucleotide polymorphisms (SNPs) (Aebersold, Nature 422:115-116 (2004)). Disclosed herein (see Example 4) is a method and its implementation in a platform to also transform quantitative proteomics from a discovery into a browsing mode of operation. The performance of the system was demonstrated by analyzing proteins contained in human blood serum. Based on the characteristics of the method which include vastly simplified data analysis, high throughput, absolute quantification of proteins in complex samples, reduced redundancy, the ability to search for and quantify specific protein isoforms and the potential for standardization of results between laboratories, the method is expected to become widely applicable in quantitative proteomics studies.


Serum proteins have been the focus for biomarker identification and disease detection. Currently, most current serum proteomic analyses focus on discovery and annotation of serum proteins due to the enormous complexity of the serum proteome as well as individual variations over time and within a population. However, the serum proteins and peptides identified from discovery phased studies define the boundary of the serum proteome and can identify so-called proteotypic peptides which uniquely identify a given protein and are consistently observed by a mass spectrometer. These proteotypic peptides can be used to screen the proteome to reveal constellations associated with specific biological processes or physiological conditions. Since most serum proteins are N-linked glycosylated at one or several tryptic peptides, it was therefore proposed to identify proteotypic N-linked glycopeptides for serum proteome analysis using a recently developed solid-phase extraction of glycopeptides (SPEG) method (see Example 7). First, over three thousand unique N-linked glycosylation sites representing over two thousand unique serum proteins were experimentally identified. These identified glycopeptides were then used to calculate the frequency of each amino acid at each position surrounding the N-linked glycosylation sequon (NX(T/S) and physico-chemical properties of peptides that can be detected by mass spectrometry. The refined glycosylation motif and peptide properties were then used to predict all potential N-linked proteotypic glycopeptides from a database of candidate proteins. Quantitative analysis of serum proteins using these identified and predicted proteotypic N-linked glycopeptides increases the throughput and sensitivity of serum analysis for biomarker discovery research.


Physiologists believe that individual genetic backgrounds and pathological changes in organs affect serum protein composition. This allows for a systematic and quantitative analysis of serum proteins for identifying disease biomarkers. This explains the current focus of numerous studies on serum proteome annotation for biomarker identification (Shen et al., Anal. Chem. 76:1134-1144 (2004); Anderson et al., Mol. Cell. Proteomics 3:311-326 (2004)). Two methods have been used preferentially to profile serum proteins. The first and most commonly used is protein/peptide patterns analysis. This is exemplified by two-dimensional gel electrophoresis (2DE), surface enhanced laser desorption ionization mass spectrometry (SELDI-MS), and liquid chromatography mass spectrometry (LC-MS). The limitations of this approach are that the molecules are not identified and that limited depth is achieved. The second is a more recently developed technique based on stable isotope tagging of proteins and automated peptide tandem mass spectrometry (MS/MS) (Shen et al., Anal. Chem. 76:1134-1144 (2004); Anderson et al., Mol. Cell. Proteomics 3:311-326 (2004); Pieper et al., Proteomics 3:422-432 (2003)). Due to the enormous complexity and high dynamic range of the plasma proteome, using the current abundance dependent proteomic approach, the MS/MS based method can only identify a small subset of the peptides, presumably the highly abundant peptides present in plasma proteome, and it is very difficult to access low-abundance proteins that represent new biomarkers.


In response to this challenge, some researchers have devised a “divide and conquer” strategy for analyzing subsets of the serum proteome to reduce complexity and to increase the detection limits of serum proteins by avoiding repetitive analyses of the most abundant proteins. Specifically, the most abundant serum proteins, for example, albumin and immunoglobulin, are removed by affinity depletion (Pieper et al., Proteomics 3:422-432 (2003); Pieper et al., Proteomics 3:1345-1364 (2003); Adkins et al., Mol. Cell. Proteomics 1:947-955 (2002)). In the second part of the “divide and conquer strategy,” proteins or peptides are fractionated according to physico-chemical properties, for example, size, charge, or hydropathy, prior to mass spectrometric analysis. Specific implementations include two- or three-dimensional peptide chromatography (Shen et al., Anal. Chem. 76:1134-1144 (2004); Adkins et al., Mol. Cell. Proteomics 1:947-955 (2002); Tirumalai et al., Mol. Cell. Proteomics 2:1096-1103 (2003); and size fractionation prior to protein digestion and analysis by LC-MS/MS 66. Tirumalai et al., Mol. Cell. Proteomics 2:1096-1103 (2003). Alternatively, proteins that contain common distinguishing structural features in plasma proteins, such as carbohydrate groups or cysteine residues (Pieper et al., Proteomics 3:422-432 (2003); Guppy et al., Oncologist 7:437-443 (2002). have been selectively enriched prior to MS analysis.


In every study, extensive efforts have been used to discover new serum proteins and annotate a serum protein database. This discovery phase of serum protein analysis normally does not contain quantitative information about individuals related to disease because it is not sufficiently reproducible, but it does define the boundary of the serum proteome. Analogous to trends seen in genomic studies, where a discovery phase marked by high-throughput DNA sequencing was followed by a scoring phase using microarrays, this extensive discovery based proteomic analysis of serum proteins is extremely useful to transverse this discovery phase of serum protein analysis to scoring phased analyses using the peptides and proteins identified in these data sets. This was demonstrated using synthetic stable isotope labeled peptides and ordered array as example 77. Pan et al., Mol. Cell. Proteomics 4:182-190 (2005). In that study, quantitative analysis of the serum proteome using prior identified proteotypic peptides was determined. The method included the selection and chemical synthesis of isotopically labeled reference peptides that uniquely identify a particular protein, and the addition of a panel of such peptides to the sample mixture consisting of tryptic peptides from the proteome in question. The combined peptide samples were then separated by chromatography to generate ordered peptide arrays on the sample plate of a matrix-assisted laser desorption/ionization (MALDI) mass spectrometer, and detected by MALDI-TOF/TOF mass spectrometer.


To identify the proteotypic peptides that are the basis for a high throughput plasma proteome screening, a large scale isolation of formerly N-linked glycopeptides was performed using the recently developed method, SPEG (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)). The isolated peptides were fractionated by strong cation exchange (SCX) and identified by a combination of liquid chromatography, tandem mass spectrometry (LC-MS/MS), and a suite of software to determine the peptide sequence and statistical analysis of identification confidence (Eng et al., J. Am. Soc. Mass. Spectrom. 5:976-989 (1994); Keller et al., Anal. Chem. 74:5383-5392 (2002). With a minimum peptide probability score of 0.5, 3244 nonredundant N-linked glycosylation sites were identified, representing 2585 unique proteins. 2106 peptides are unique to single database entry, and selected as proteotypic peptides, representing 1671 proteins. Using the identified N-linked glycosylation sites, the amino acid composition surrounding the consensus N-linked glycosylation sites was further determined and generated a predictor for physico-chemical properties of peptide that were likely to be detected by mass spectrometry. The refined NXT/S motif and peptide properties were then used to predict potential N-linked glycopeptides as proteotypic peptides by scanning the human IPI protein database. The experimentally identified and computationally predicted N-linked proteotypic peptides resulting from the database can be interrogated via a World Wide Web interface, UniPep, (db.systemsbiology.net/devPM/sbeams/cgi/PeptideAtlas/Glyco_prediction.cgi). This is intended to provide a fast and accurate way to screen the plasma proteome for biomarkers using proteotypic peptides as heavy isotopic standards in conjunction with mass spectrometry, and is expandable as more peptides are discovered and added.


It is understood that modifications which do not substantially affect the activity of the various embodiments of this invention are also provided within the definition of the invention provided herein. Accordingly, the following examples are intended to illustrate but not limit the present invention.


Example 1
Isolation of Tryptic Peptides of Glycoproteins from Serum and N-linked Glycopeptides from Plasma

The isolation method was described previously (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)). In detail, proteins from 0.75 ml of serum or 1 ml of plasma were changed to buffer containing 100 mM NaAc, 150 mM NaCl, pH 5.5 (coupling buffer). Sodium periodate solution at 15 mM was added to the samples. The samples were rotated in dark at room temperature for 1 hour. The sodium periodate was removed from the samples using a desalting column (Bio-Rad; Herculed, Calif.). Eight ml of hydrazide resin (Bio-Rad; Hercules, Calif.) equilibrated in coupling buffer was added to the sample. The sample and resin were capped securely and rotated end-over-end for 18 hours at room temperature. The non-glycoproteins were removed, and resin was washed 3 times with 20 ml of 8M urea/0.4M NH4HCO3. The proteins on the resin were denatured in 20 ml of 8M urea/0.4M NH4HCO3 at 37° C. for 30 min, followed by 3 washes with the urea solution. After the last wash and removal of the urea buffer, the resin was diluted 4 times with water. 200 μg of trypsin in 24 ml of water was added to digest the bound proteins at 37° C. overnight. Peptides were reduced by adding 8 mM TCEP (Pierce, Rockford Ill.) at room temperature for 30 min, and alkylated by adding 10 mM iodoacetamide at room temperature for 30 min. For serum sample, the trypsin released peptides were collected and further analysed by mass spectrometry. The resin was washed with 20 ml of 1.5 M NaCl 3 times, 80% acetonitrile 3 times, 100% methanol 3 times, and 0.1 M NH4HCO3 6 times. N-linked glycopeptides were released from the resin by digestion with 6 μl of peptide-N-glycosidase F (New England Biolabs; Beverly, Mass.) overnight. The peptides were dried and resuspended in 0.4% acetic acid for LC-MS/MS analysis.


For separation of peptide by chromatography and analysis of peptides by mass spectrometry, the resulting peptide mixture was fractionated by two-dimensional chromatography (Han et al., Nat. Biotechnol. 19:946-951 (2001): (1) cation-exchange chromatography using a 2.1 mm 20 cm Polysulfoethyl A column (Poly LC Inc., Columbia, Md.) at a flow rate of 200 μl/min using 1-hour gradient from buffer A (20 mM KH2PO4, 25% acetonitrile, pH 3.0) to buffer B (20 mM KH2PO4, 350 mM KCl, 25% acetonitrile, pH 3.0); and (2) reverse-phase capillary chromatography using a 75 μm 10 cm self-packed C18 column at a flow rate of 250 nl/min using 1-hour gradient from buffer A (5% acetonitrile and 0.1% formic acid) to buffer B (35% acetonitrile). The peptide identification by collision-induced-dissociation (CID) was carried out in an automated fashion using the dynamic-exclusion option on Finnigan LCQ ion trap mass spectrometer (Finnigan, San Jose, Calif.) or ESI-QqTOF (Macromass, Beverly, Miss.).


For data analysis, CID spectra was searched using SEQUEST (Eng et al., J. Am. Soc. Mass Spectrom. 5:976-989 (1994)) against the human International Protein Index sequence database (version 2.21, downloaded from the European Bioinformatics Institute ftp.ebi.ac.uk/pub/databases/IPI/current/ipi.HUMAN.fasta.gz). The database search results were analysed by a suit of software tools including INTERACT (Han et al., supra, 2001), peptide probability (Keller et al., Anal. Chem. 74:5383-5392 (2002)), and protein prophet (Nesvizhskii et al., Anal. Chem. 75:4646-4658 (2003)) to sign the probability and confidence score for each identified peptides and proteins.


The protocol is illustrated in FIGS. 4 and 5. FIG. 4 shows a schematic of quantitative analysis of serum proteins. FIG. 5 shows an exemplary analysis with the addition of a standard peptide.


Example 2
High Throughput Quantitative Analysis of Serum Proteins Using Glycopeptide Capture and LC-MS

This example describes analysis of serum proteins by capturing glycopeptides and analyzing by mass spectrometry. The analysis was performed on normal and cancer mice to identify differentially expressed glycopeptides associated with a cancer condition.


It is expected that the composition of the serum proteome can provide valuable information about the state of the human body in health and disease, and this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to be sensitive and capable of detecting potential biomarkers below the level of highly expressed proteins, to be reproducible and robust, to generate data sets that are comparable between experiments and laboratories, and to have high throughput to support studies with sufficient statistical power. High throughput quantitative analysis of serum proteins has been performed. Peptides that are N-glycosylated in the intact protein were selectively isolated and analyzed by LC-ESI-MS. A comparative analysis was performed to determine any resulting patterns indicating differential expression of glycopeptides between normal and cancer mice as potential biomarkers for the cancer condition. By focusing selectively on the few N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced and the sensitivity and throughput of serum proteome analysis are increased. The results show that sera from normal mice and genetically identical mice with carcinogen induced skin cancer can be unambiguously discriminated using unsupervised clustering of the resulting peptide pattern. It was further determined by tandem mass spectrometry that some of the glycopeptides were consistently elevated in cancer mice compared to their healthy littermates.


Serum from normal mice and mice with carcinogen induced skin cancer were analyzed essentially as described previously (Zhang et al., Nat. Biotechnol. 21:660-666 (2003) and essentially as described in Example 1. FIG. 6 shows a schematic outline of the procedure for glycopeptide profiling of serum proteins using LC-MS. Serum samples were obtained from normal mice and mice having carcinogen induced skin, and N-linked glycopeptides were isolated essentially as described in Example 1. Peptides were analyzed by LC-MS, and peptides that discriminated between normal and cancer mice were determined. LC-MS/MS analysis was then performed on selected precursor ions.


Table 1 shows that the glycopeptide capture-and-release method reduces the number of peptides to be analyzed from each serum protein and reduces sample complexity for serum profiling.









TABLE 1







Reduction of sample complexity for serum profiling using


glycopeptide capture and release.












A
B
C
D















Total number of peptides
2889
355
338
166


Number of peptides for each protein
29.8
3.66
3.48





A: Number of tryptic peptides


B: Number of glycopeptides


C: Number of identified glycopeptides


D: Number of N-linked glycosylation sites






The use of the glycopeptide capture method greatly reduces sample complexity, thereby increasing the sensitivity of analysis, particularly of less abundant serum proteins. A comparison of the analysis of glycopeptides from 5 μl of serum (left panel) and tryptic peptides from 0.05 μl of serum was performed. Proteins were analyzed in 100 min LC-MS. It was found that 100 times the amount of serum can be analyzed due to the reduction in complexity from isolating glycopeptides and omitting analysis of abundant non-glycosylated proteins, thus allowing the analysis of less abundant serum proteins.


The high throughput serum analysis method was highly reproducible. The distribution of CV (coefficient of variance) from 9 repeated LC-MS analysis of the same sample was determined. The distribution of CV from 4 repeated sample preparations using the glycopeptide capture method and LC-MS analysis was also determined. The distribution of CV obtained from 5 normal male mice of the same litter was additionally determined.


Unsupervised hierarchical clustering analysis of N-linked glycopeptides can separate carcinogen induced cancer mice from normal mice. Both increased and decreased abundance was observed for various peptides in comparison of cancer mice with normal mice. In some cases, peptide abundance was higher than the mean peptide intensity of normal mouse sera. In other cases, peptide abundance was lower compared to the mean of this peptide in different, that is, normal mouse sera.


The method of glycopeptide capture allows the identification of peptides that are elevated in carcinogen induced cancer mice. The abundance of an identified peptide from serum amyloid P-component with m/z value of 709.7 in sera of normal and cancer mice was determined by highly reproducible LC-MS analysis.


These results demonstrate that selectively isolating those peptides that are N-glycosylated serum proteins has a number of favorable consequences for the analysis of the serum proteome. Together with the high reproducibility of the method, the unprecedented serum proteome coverage achieved at a moderate throughput indicates that the method is useful for the detection of proteins or protein patterns that distinguish individuals in different physiological states. These studies were extended and are described below.


Materials and Reagents. For all chromatographic steps, HPLC grade reagents were purchased from Fisher Scientific (Pittsburgh, Pa., USA). PNGase F was from New England Biolabs (Beverly, Mass.). Hydrazide resin was from Bio-Rad (Hercules Calif.). All other chemicals and the human serum sample used in this study were purchased from Sigma (St. Louis, Mo., USA).


Chemical induction of mouse skin tumors. Male mice of strain NIHO1a were subjected to the two-stage skin carcinogenesis protocol (Kemp et al., Cell 74:813-822 (1993)). Five littermates were used; 2 untreated and 3 treated with carcinogen. The shaved backs of three 8-week old mice were treated with a single dose of the carcinogen 7,12 dimethylbenz[a]anthracene (DMBA) (Sigma; 25 mg in 200 ml acetone). Initiated cells were promoted with 12-O-tetradecanoylphorbol-13-acetate (TPA) twice a week for 15 weeks, giving rise to papillomas that were hyperplastic, well-differentiated, benign lesions consisting of keratinocytes together with stromal tissue. Papillomas appeared as early as 8 weeks after DMBA initiation and continued to grow for the next several months. A small percentage of these benign papillomas progressed to squamous cell carcinomas (SCC). At week 22 after DMBA initiation, all mice were sacrificed and whole blood collected by heart puncture with a 21 G needle and 1 cc syringe. Blood was allowed to clot for 1 hr at room temperature. Sera were collected by centrifugation at 3000 rpm. The untreated mice contained no tumors, while the DMBA/TPA treated mice each had at least one carcinoma as confirmed by histological analysis.


Preparation of peptide samples for mass spectrometry analysis. Formerly N-linked glycosylated peptides were isolated and labeled using N-linked glycopeptide capture procedure as described previously (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)). Proteins from 100 μl of serum were used in isolation and isotope labeling of formerly N-linked glycopeptides, and peptides from 5 μl of original serum were used in each mass spectrometry analysis.


To prepare tryptic peptides from serum proteins, proteins from 1 μl (80 μg) of mouse serum were denatured in 20 μl of 8M urea/0.4M NH4HCO3 for 30 min at room temperature. The proteins were diluted 4 times with water, after which 1 μg of trypsin was added and the proteins were digested at 37° C. overnight. The peptides were then reduced by adding 8 mM Tris(2-carboxyethyl)phosphine (TCEP) (Pierce, Rockford Ill.) at room temperature for 30 min and alkylated by adding 10 mM iodoacetamide at room temperature for 30 min. The peptides were dried and resuspended in 0.4% acetic acid. Peptides from 0.05 μl of original serum (4 μg original serum proteins) were used for each LC-MS analysis.


Analysis of peptides by mass spectrometry. The peptides and proteins were identified using MS/MS analysis using an LCQ ion trap mass spectrometer (Thermo Finnigan, San Jose, Calif.) as described previously (Gygi et al., Nat. Biotechnol. 17:994-999 (1999)). For quantitative analysis of peptides using LC-MS, an ESI-QTOF (liquid chromatography electrospray ionization quadrupole-time-of-flight) mass spectrometer (Waters, Beverly, Mass.) was used. In both systems, peptides isolated from 5 μl of serum sample using the glycopeptide capture method were injected into a homemade peptide cartridge packed with Magic C18 resin (Michrome Bioresources, Auburn, Calif.) using a FAMOS autosampler (DIONEX, Sunnyvale, Calif.), and then passed through a 10 cm×75 μm inner diameter microcapillary HPLC (μ-LC) column packed with Magic C18 resin (Michrome Bioresources, Auburn, Calif.). The effluent from the μ-LC column entered a homebuilt electrospray ionization source in which peptides were ionized and passed directly into the respective mass spectrometer. The C18 peptide trap cartridge, μ-ESI-emitter/μ-LC pulled tip column combination, a high voltage line for ESI and the waste line were each connected to separate ports of a four port union (Upchurch Scientific, Oak Harbor, Wash.) constructed entirely out of polyetheretherketone (PEEK) (Yi et al., Rapid Commun. Mass Spectrom. 17:2093-2098 (2003)). A linear gradient of acetonitrile from 5%-32% over 100 min at flow rate of ˜300 nL/min was applied. During the LC-MS mode, data was acquired with a profile mode in the mass range scan between m/z, 400 and 2000 with 3.0 sec scan duration and 0.1 sec interscan. After completion of the LC/MS runs, inclusion peptide mass lists were created from data analysis software. The inclusion lists were then used for targeted LC/MS/MS analysis for peptide/protein identifications with the remaining of samples.


ESI-QTOF data analysis: A suite of software tools were developed or optimized in house to analyze LC-MS data for this project and will be published separately (Li et al. manuscript in preparation). The software tools use LC-MS data generated by ESI-QTOF analysis of formerly N-linked glycopeptides from serum samples and sequentially perform the following tasks to determine peptides that are of different abundance in cancer and normal mice, respectively.


1. Peptide list: A list of peptide peaks was generated from each LC-ESI-MS run. The tool performing this operation was a straightforward extension of a previous tool for the analysis of LC-MALDI-MS data (Griffin et al., Anal. Chem. 75:867-874 (2003)). That tool was modified to take into account the fact that, in ESI-MS, peptides are observed in different charge states. Peaks were selected if the signal to noise ratio exceeded 2.


2. Peptide alignment: Peptides detected in individual LC-MS patterns were aligned mainly based on peptide mass. The retention time was then used to align peptides with the same m/z value. The software tool accounted for shifts in the retention time, in different LC-MS analyses during peptide alignment. Peptide alignment was facilitated by the following factors: i) the glycopeptide capture procedure significantly simplifies the sample complexity, ii) the high mass accuracy achieved in ESI-QTOF instrument, and iii) the optimized HPLC system that produced highly consistent and reproducible peptide patterns. In the mouse studies, peptides that appeared at least in two of three analyses in either group were selected for further quantitative analysis.


3. Peptide abundance ratio: An abundance ratio of matched peptides in different samples was determined for each peptide peak using the same method as described in the ASAPRatio software tool developed for LC-ESI-MS/MS data (Li et al., Anal. Chem. 75:6648-6657 (2003)). Briefly, the software uses spectra from multiple LC-MS analyses of a peptide peak (with same mass-to-charge ratio (m/z), charge state, and close retention time) and calculates one ratio for each peptide peak. In the present study, ratios calculated for different charge states of the same peptide were not combined. The algorithm also estimated a noise background level in each spectrum and subtracts that value from the signal intensities when calculating the peak area.


4. Clustering analysis: The lists of matched peptides with their relative signal intensities were subjected to unsupervised hierarchical clustering (Eisen et al., Proc. Natl. Acad. Sci. USA 95:14863-14868 (1998)) to identify peptides distinguishing cancer samples from normal samples. Prior to clustering, the data was transformed to log value and the mean intensity of each peptide cross all samples was normalized; Peptides present at least in 50% of the total samples were used for clustering analysis.


The objective of the method is the generation of reproducible peptide patterns representing the serum proteome, leading to the detection of peptides that discriminate between related groups of proteomes and the subsequent identification of these discriminatory peptides. The method is schematically illustrated in FIG. 6 and consists of four steps. (1) Sample preparation. Peptides that contain N-linked carbohydrates in the native protein were isolated in their de-glycosylated form using a recently described solid-phase capture-and-release method (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)). (2) Pattern generation. Isolated peptides were analyzed by LC-MS to generate three-dimensional (retention time, m/z, and intensity) patterns. (3) Pattern analysis. Peptide patterns obtained from different samples were compared and the discriminatory peptides determined. (4) Peptide identification. Discriminatory peptides and the proteins from which they originated were identified by tandem mass spectrometry and sequence database searching.


To determine the selectivity of the glycopeptide capture method for serum protein analysis, serum samples from four genetically identical mouse littermates were individually processed using the N-linked glycopeptide capture-and-release method and the isolated peptides were analyzed by LC-MS/MS. The resulting collision induced dissociation (CID) spectra were searched against the mouse International Protein Index sequence database (version 1.24) and the database search results were further statistically analyzed using the PeptideProphet software tool (Keller et al., Anal. Chem. 74:5383-5392 (2002)). From four LC-MS/MS analyses of the mouse sera, 1722 CID spectra resulted in peptide identifications from database search with peptide probability scores of at least 0.99 (corresponding to a false positive error rate of 0.0007 (Keller et al., Anal. Chem. 74:5383-5392 (2002)). The identified sequences were then examined for the presence of the known consensus N-linked glycosylation motif (N—X-T/S, where X=any amino acid except proline). The number of proteins represented by the selected peptides were determined using INTERACT (Han et al., Nat. Biotechnol. 19:946-951 (2001)). The number of identified proteins and peptides are summarized in Table 2. A total of 319 unique peptides were identified, representing 93 unique proteins. 93.6% of the identifications, 81.8% of unique peptides, and 93.5% of identified proteins contained the consensus N-linked glycosylation motif (Table 2).









TABLE 2







Total number of peptide identifications, unique peptides, and unique


proteins, and the proportion of each that contain N-X-T/S motif.












Peptides
Percentage




containing
of motif



Total
N-X-T/S
containing



peptides
motif
peptides














Number of identifications
1722
1611
93.6%


Number of unique peptides identified
319
261
81.8%


Number of unique proteins identified
93
87
93.5%









The peptide identified as not containing the consensus N-linked glycosylation motif can be grouped into two pools. The first contains peptides that are correctly identified and the second is peptides that are incorrectly identified by SEQEST search (false positives). In the present analysis, the false positive error rate was estimated by the PeptideProphet statistical model. To further estimate the selectivity of the isolation method, the fraction of peptides identified without consensus N-linked glycosylation motif was calculated as a function of the PeptideProiphet probability values. The data are shown in FIG. 7. It is apparent that the fraction of peptides without N—X—S/T motif decreases as the stringency of the identification criteria increases. Concurrently, as expected, the number of false positive peptide identifications also decreases. Significantly, and consistent with the data in Table 2, the percentage of peptides without N—X—S/T motif plateaus out at approximately 6.4%, as the false positive error rate approaches 0. It is therefore concluded that the peptide isolation method used has a selectivity that is not lower than 93.6%.


Reduction in the complexity of serum-derived peptide mixtures obtained via the glycopeptide capture-and-release method. The data described above was used to estimate the reduction in sample complexity achieved via the glycopeptide capture-and-release method. A total of 93 proteins were identified collectively from the four serum samples analyzed. Disregarding the complexity caused by protein post-translational modifications, the 93 identified proteins were expected to generate an average of 28.8 of tryptic peptides per protein. Of these, 3.6 peptides on average contained the N—X—S/T motif and were therefore designated potentially N-linked glycosylated peptides. Among the 93 identified proteins in this study, an average of 3.6 peptides representing 1.8 unique N-linked glycosylation sites per protein were actually identified. By comparing the number of unique N-linked glycosylation sites identified with the number of predicted peptides containing consensus N-linked glycosylation motif, it was found that 50% of the predicted glycosylated peptides had been detected. Interestingly, an analysis of the actual occupancy rate of potential N-linked glycosylation sites in glycoproteins in the crystallographic database showed approximately 65% site occupancy (Petrescu et al., Glycobiology 14:103-114 (2004)). Collectively, these data indicate that the glycopeptide capture-and-release from serum proteins, significantly reduces sample complexity and that the method captured a significant fraction of the potentially available N-linked glycosylated peptides.


To determine whether the increased sensitivity achieved by reducing sample complexity was sufficient to detect serum protein biomarkers of clinical relevant concentration, we related data obtained in this study to the concentrations of human serum marker proteins (Putnam, The plasma proteins: Structure, Function, and Genetic Control, 2nd ed. Academic Press, New York, N.Y. (1975); Lum and Gambino, Am. J. Clin. Pathol. 61:108-113 (1974)). A direct comparison of the protein compositions between the human and mouse serum proteomes has not previously been determined. However, the serum two-dimensional (2-D) maps of human and mouse are sufficiently similar to allow an approximate comparison of the concentrations of the proteins identified in this study between human and mouse (Duan et al., Electrophoresis 25:3055-3065 (2004)). From the 93 proteins identified above, several proteins are known to be present in human serum at low μg/ml concentration (Table 3). These include carboxypeptidase N and coagulation factors II, V, XII, and XIII. Except for epidermal growth factor receptor and serum amyloid P-component, none of the other proteins listed in Table 3 have been identified in previous mouse 2-D map, suggesting that they are present at low abundance in mouse serum (Duan et al., Electrophoresis 25:3055-3065 (2004)). To estimate the detection sensitivity, the peak intensities of the identified peptides from these proteins were calculated using the intensities of chromatographic peaks at the charge states used for peptide identification. Examination of the peak intensities indicated an average peptide peak intensity of 2.7×107, which is ˜900 times greater than the observed background signal for these experiments (Table 3). This indicates that even without multidimensional separation, serum proteins at concentrations on the order of ng/ml may be detected by LC-MS of formerly N-linked glycopeptides.


Table 3. Peak intensities of formerly N-linked glycopeptides identified from mouse sera and the reported concentration of their corresponding proteins in human serum.









TABLE 3







Peak intensities of formerly N-linked glycopeptides identified from


mouse sera and the reported concentration of their corresponding proteins in


human serum.











Protein name
IPI Number
Peptide sequences
μg/ml
Intensity





kallikrein B, plasma 1
IPI00113057
R.IVGGTN#ASLGEWPWQVSLQVK.L
50
1.50 × 107




K.LQTPLN#YTEFQKPICLPSK.A

3.30 × 107


coagulation factor II
IPI00114206
R.CAMDLGVNYLGTVN#VTHTGIQCQLWR.S
20
1.30 × 107




R.WVLTAAHCILYPPWDKN#FTENDLLVR.I

2.90 × 107


coagulation factor V
IPI00117084
K.SN#ETALSPDLN#QTSPSM*STDR.S
20
1.50 × 106


Similar to carboxypeptidase N
IPI00119522
E.ITGSPVSN#LSAHIFSN#LSSLEK.L
35
1.10 × 108




R.DGSDSAAM*VYN#SSQEWGLR.S

3.20 × 107


Epidermal growth factor receptor
IPI00121190
R.DCVSCQN#VSR.G

8.30 × 106




R.DIVQNVFM*SN#M*SM*DLQSHPSSCPK.C

1.80 × 107




K.DTLSIN#ATNIK.H

1.10 × 107


coagulation factor XIII, beta subunit
IPI00122117
K.EQETCLAPELEHGN#YSTTQR.T
10
5.30 × 106




R.TYEN#GSSVEYR.C

8.40 × 106


coagulation factor XII (Hageman
IPI00125393
R.HN#QSCEWCQTLAVR.S
30
3.30 × 107


factor)


interferon (alpha and beta) receptor 2
IPI00132817
K.SGPPAN#YTLWYTVM*SK.D

1.70 × 107


serum amyloid P-component
IPI00267939
K.LIPHLEKPLQN#FTLCFR.T
20
7.00 × 107





Average
2.70 × 107





Background
3.00 × 104





SNR
8.99 × 102





N# indicates the N-linked glycosylation site.


M* = oxidized methionine


SNR = signal to noise ratio






Assessment of reproducibility of LC-MS patterns following glycopeptide capture-and-release of serum proteins. Out of the 319 peptides and 93 proteins identified by four LC-MS/MS analyses, 109 unique peptides and 52 unique proteins were identified from all four analyses. The number of peptides identified in all four LC-MS/MS runs is low compared to the total number of unique peptides identified (34.2%). The Pep3D software tool was used (Li et al., Anal. Chem. 76:3856-3860 (2004)) to determine whether, these observations were due to peptide under sampling in the LC-MS/MS experiment or whether they indicated poor pattern reproducibility. The results show that, first, as expected, the LC-MS patterns of the peptides from individual mouse serum were consistent. Second, due to the complexity of the sample, not all peptides in a given analysis were selected for MS/MS analyses and subsequently identified. Third, as far as could be determined from the difference between the number of identified peptides from MS/MS analysis and total peptides present in a sample from MS analysis, only a small portion of peptides, predominantly the high abundance peptides from each sample were selectively identified by MS/MS analyses. Fourth, the differences between peptide/protein identifications by MS/MS analyses between different samples were caused mainly by the fact that only a fraction of total peptides was identified by MS/MS analysis in the data dependant mode of operation. Collectively, these results suggest that LC-MS analyses of glycopeptides isolated from genetically identical mice are reproducible. However, peptide/protein identifications using MS/MS analyses, due to peptide under sampling, results in a relatively small number of peptide identifications and a seemingly poor reproducibility of the method.


The reproducibility of the peptide patterns obtained by LC-MS was examined. Four 50 μl aliquots from a single serum sample were processed in parallel to generate four isolates and then analyzed by LC-MS. First, to assess LC-MS reproducibility, equal amounts of each isolate were combined and analyzed the combined sample 9 times by LC-MS using a 100 min reverse phase gradient. In house developed software tools were used to detect peaks in the resulting patterns, to measure peak intensity, and to align corresponding peptide peaks between multiple patterns (Li et al. manuscript in preparation). From these data, the average intensity, standard deviation of intensity, and coefficient of variance (CV) was calculated for each peptide. A histogram of CV from the 9 repeat analyses of identical samples by LC-MS is shown in FIG. 8 (rectangles). The mean and median CVs observed in the 9 repeat LC-MS analyses of the same sample were 28.3% and 21.8%, respectively. Next glycopeptides were analyzed'from the four individual isolates as described above to determine reproducibility with respect to peptide isolation. This data is shown in FIG. 8 (squares). The mean and median CVs for the four replicate sample preparations were 25.7% and 21.6%, respectively, and therefore comparable to the analogous values from repeat LC-MS analysis of identical samples. These results indicate that sample preparation does not significantly contribute to the variability of observed peptide patterns.


Application of the method to distinguish sera from normal and skin cancer-bearing mice. To test the hypothesis that the serum proteome profiles from individuals in different physiological states can be differentiated, the glycopeptide capture-and-release method was applied to serum samples from mice in which skin tumors had been induced and from normal untreated littermates. Skin tumors were induced in a well established skin carcinoma model via topical treatment of the skin with a single dose of DMBA followed by repeated treatments with the tumor promoter TPA (Kemp et al., Cell 74:813-822 (1993)). This treatment gives rise to papillomas that are hyperplastic and well-differentiated benign lesions of the skin, each one originating from a single initiated cell (Brown et al., K., Cell 46:447-456 (1986); Quintanilla et al., Nature 322:78-80 (1986)). After a latency period of several months, a small percentage of these lesions progress to squamous cell carcinomas.


From the sera of three cancer-bearing male mice (C1, C2, and C3) and two untreated normal male mice (N1 and N2) from the same litter, glycopeptides were isolated and analyzed by LC-MS as described above. The sample from N1 was analyzed by LC-MS twice (N1a, N1b), thus a total of six LC-MS patterns were generated. After aligning peptide peaks from all six patterns, over 3000 peptide peaks were found to occur in at least 2 of the 3 analyses from either normal or cancer-bearing mice. The six LC-MS patterns consisting of the peptide peaks matched between the samples and their associated intensities were next subjected to unsupervised hierarchical clustering (Eisen et al., Proc. Natl. Acad. Sci. USA 95:14863-14868 (1998)). Neither predefined reference vectors nor prior knowledge about the nature of each pattern (untreated normal versus cancer-bearing) was used. The results of this unsupervised hierarchical clustering analysis are represented by a tree structure. The lengths of the branches among different samples are proportional to the similarity of the obtained peptide patterns. From this clustering, it is apparent that the cancer-bearing mice (C1, C2, and C3) were clustered together and clearly differentiated from the patterns obtained from their sex and litter matched normal mice (N1a, N1b, and N2) which were also clustered together.


To test whether the same serum samples could be equally differentiated without applying the glycopeptide capture-and-release enrichment method, tryptic peptides from 50 nl of each unprocessed serum sample were subjected to the same LC-MS and pattern analysis procedure. Peptide peaks were aligned from the resulting patterns, and a similar number of peptide peaks were detected as for the glycopeptide enriched samples. In contrast to the glycopeptide enriched samples, unsupervised clustering of the total serum peptide patterns did not differentiate the cancer group from normal group. These results indicate that the larger number of proteins and/or the deeper penetration into the serum proteome achieved by the glycopeptide selection chemistry is critical to the successful differentiation between serum samples according to the clinical state of the individuals.


The glycopeptide enriched samples were then further analyzed by MS/MS to identify peptides that increase in abundance in cancer-bearing mice from untreated normal animals. The m/z and retention time coordinates of these peptides were added to the inclusion list on a tandem mass spectrometer and identified by LC-MS/MS and sequence database searching. FIG. 9A shows a peptide at m/z of 709.7 (eluted at ˜65 min) that, while showing variation between individuals, also clearly showed consistently increased abundance in cancer-bearing mice (C1, C2, C3) compared with normal animals (N1a, N1b, N2). The signal at m/z of 709.7 was subsequently identified as a peptide with the amino acid sequence LIPHLEKPLQN#FTLCFR (in which N# indicates the formerly N-linked glycosylation site; SEQ ID NO:) derived from serum amyloid P component in mouse. This is an acute-phase protein whose expression is known to be elevated during inflammation (Mole et al., J. Immunol. 141:3642-3646 (1988).


The differential abundance of the identified peptides was verified by applying accurate quantitative analysis using stable isotope labeling. In these experiments, the amino groups of the glycopeptides were isotopically labeled with d0 and d4 succinic anhydride, respectively, while the peptides were still attached to the solid support during their isolation (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)). Equal aliquots of samples from two cancer-bearing mice (C2 and C3) and two normal mice (N1 and N2) were reverse labeled with either the d0- and d4-succinic anhydride and the released peptides were combined in the following way: sample N1 (d0) was paired with sample C2 (d4); sample C2 (d0) was paired with sample N1 (d4); sample N2 (d0) was paired with sample C3 (d4); and sample C3 (d0) was paired with sample N2 (d0). The combined samples were analyzed by LC-MS/MS. The m/z of peptides identified with higher abundance in cancer-bearing mice using LC-MS analysis and pattern matching were selected and the corresponding mass for light and heavy succinic anhydride labeled peptides were included in the mass inclusion list (with a 100 Dalton addition for the light form of succinic anhydride and a 104 Dalton addition for the heavy succinic anhydride labeling) and then sequenced by MS/MS analysis using ESI-QTOF and identified by database searching. Table 4 lists the identified peptides and proteins with elevated protein level in the cancer-bearing mouse group detected by LC-MS analysis and verified by reverse stable isotope labeling. The LC-MS spectrum obtained for the same peptide from serum amyloid P-component is shown in FIG. 9B. The increased level of this peptide in cancer-bearing mice quantified by isotopic labeling was consistent with that determined by LC-MS analysis (FIG. 9A).










TABLE 4







Identification of peptides and proteins with elevated abundance in



treated cancer-bearing mice














CID spectrum






number given in





Supplementary


Protein name
IPI number
Peptide sequences
FIG. 1 online





Ig gamma-1 chain C region secreted
IPI00109911
R.EEQFN#STFR.S
332



form





serum amyloid P-component
IPI00267939
K.LIPHLEKPLQN#FTLCFR.T
333





haptoglobin
IPI00274017
K.NLFLN#HSETASAK.D
334







K.N#LTSPVGVQPILNEHTFCAGLTK.Y
335





leucine-rich alpha-2-glycoprotein
IPI00129250
R.SLPPGLFSTSAN#LSTLVLR.E
336





complement component factor h
IPI00130010
K.DNSCVDPPHVPN#ATIVTR.T
337





fetuin beta
IPI00134837
R.VLYLPAYN#CTLRPVSK.R
338







R.RVLYLPAYN#CTLRPVSK.R
339









Collectively these data indicate that the LC-MS-based analysis of isolated, formerly N-linked glycosylated peptides reproducibly detected peptides of different abundance in serum samples of cancer and normal mice and that the discriminatory peptides could be identified by MS/MS analysis.


Described above is a method for high throughput quantitative analysis of serum proteins using glycopeptide capture and LC-MS. It consists of the selective and reproducible isolation of those peptides from the serum proteome that are modified by N-linked glycosylation in the intact protein. The complex mixture of the de-glycosylated forms of these peptides was then analyzed by LC-MS. The mass of discriminatory peptides was determined using pattern matching software, and these peptides were subsequently identified by MS/MS. These results indicate that the glycopeptide capture-and-release method is specific for the isolation of N-linked glycopeptides. On average, 3.6 peptides were isolated per protein representing an average of 1.8 glycosylation sites per protein. This is contrasted with a predicted 28.8 unique tryptic peptides per protein calculated from the pool of identified proteins. The data also indicates that this reduced sample complexity resulted in an increase in sensitivity compared to the analysis of non-selected serum digests using an identical analytical platform. To test its suitability for analysis of disease, the method was applied to the differentiation of sera from genetically identical mice that were either untreated normal or cancer-bearing. The resulting peptide patterns could clearly and correctly be differentiated into two groups via unsupervised clustering. Some of the discriminatory peptides were further identified by MS/MS and their differential abundance in cancer versus control mice was verified by accurate quantification using stable isotope labeling.


Ideally, for the detection and validation of protein biomarkers in serum, the complete serum proteomes of multiple individuals representing different clinical states would be completely and quantitatively analyzed. Due to the enormous complexity of the serum proteome and technical limitations, all the current proteomic technologies for such analyses can only sample a small part of the proteome, predominantly the most abundant proteins (Anderson and Anderson, Mol. Cell. Proteomics 1:845-867 (2002); Zhang et al., Curr. Opin. Chem. Biol. 8:66-75 (2004)). For example, 2DE-based studies have identified about 300 serum proteins collectively (Anderson and Anderson, Mol. Cell. Proteomics 1:845-867 (2002); Pieper et al., R., Proteomics 3:1345-1364 (2003); Anderson et al., Mol. Cell. Proteomics 3:311-326 (2004). It has also been estimated that SELDI-TOF approaches have limited detection of low abundant proteins due to the high dynamic range of serum proteins and the limited binding capacity of the SELDI chip (Diamandis, Mol. Cell. Proteomics 3:367-378 (2004)). In the method described above, the selective isolation of the N-linked glycosylated peptides resulted in a substantial improvement in the concentration limit of protein detected due to the reduction in sample complexity.


A number of factors contribute to this effect. First, the number of peptides per protein isolated after applying the glycopeptide capture-and-release method is significantly reduced. The 93 proteins identified in this study are predicted to generate an average of 28.8 tryptic peptides per protein. Of these, only 3.6 on average contain the N-linked glycosylation consensus motif and can be potentially glycosylated, and an average of 3.6 peptides representing 1.8 unique N-linked glycosylation sites per protein were actually identified. By comparison, a similar number of N-linked glycosylation sites identified per protein was reported by Kaji and colleagues (1.8 sites per protein) in a study in which N-linked glycopeptides were isolated from C. elegans proteins using lectin enrichment (Kaji et al., Nat. Biotechnol. 21:667-672 (2003)). Second, the most abundant serum protein, albumin, does not contain N-linked glycosylation motifs and therefore is effectively transparent to the analysis. Since albumin itself comprises almost 50% of total serum protein content, exclusion of albumin eliminates numerous peptides that otherwise dominate serum peptide samples. Indeed, quantitative removal of albumin, a goal that is normally attempted by use of costly affinity depletion methods (Pieper et al., Proteomics 3:422-432 (2003) is an automatic by-product of the glycopeptide capture method. Third, the method only selects peptides from the constant region of immunoglobulins and thus dramatically reduces the number of immunoglobulin-derived peptides. This is important since immunoglobulins constitute approximately 20% of total protein mass in serum (Putnam, The plasma proteins: Structure, Function, and Genetic Control, 2nd ed. Academic Press, New York, N.Y. (1975)) and comprise a population of an estimated 10 million different molecules (Anderson and Anderson, Mol. Cell. Proteomics 1:845-867 (2002)). The difficulty of penetrating the population of immunoglobulins in unbiased serum proteome analyses was recently illustrated in a study in which a tryptic digest of serum was analyzed by ultra-high-efficiency strong cation exchange LC/RPLC/MS/MS. Of the 1061 plasma protein identifications reported, 38% were immunoglobulins (Shen et al., Anal. Chem. 76:1134-1144 (2004)). It is also likely that an even more significant fraction of peptides observed in LC-MS patterns of unbiased serum protein digests are derived from immunoglobulins since nucleic acid and protein sequence databases dramatically underreport the contribution of somatic combinatorial gene rearrangement to immunoglobulin diversity. Fourth, many serum proteins are post-translationally altered by phosphorylation, glycosylation, acetylation, methionine oxidation, protease processing and other mechanisms, resulting in multiple forms for each protein. It has been estimated that one protein may generate on the order of 100 species (Anderson and Anderson, Mol. Cell. Proteomics 1:845-867 (2002)). In the case of glycosylation, the oligosaccharide structures attached at each site are typically diverse, compounding the complexity of the peptide mixture. The peptides isolated by the glycopeptide capture method remove the heterogeneous oligosaccharides, and thus by isolating a few peptides per protein only, also eliminate other significant sources of pattern heterogeneity.


The cumulative effect of these factors is the generation of a peptide sample from the serum proteome with a moderate redundancy of an average of 3.6 unique peptides per protein. Theoretically, an average of 3.6 potential N-linked glycopeptides (containing an N—X-T/S motif) is predicted for the 93 identified serum proteins. However, not all of these potential N-linked glycosylation sites were observed. Some of these potential N-linked glycosylation sites may not actually be occupied (Petrescu et al., Glycobiology 14:103-114 (2004)), or the peptides from certain sites may not be detectable by mass spectrometry, or protein digestion may be hindered by the protein post-translational modifications such as oligosaccharide attachment and/or disulfide bond formation. On the other hand, the number of peptides from each glycosylation site was increased due to other types of protein modifications (that is, methionine oxidation, protease processing) in the glycosylaton region. It is expected that the same factors would also lead to an inflation of the number of peptides observed if digests of non-selected serum samples were analyzed. In the analyses of peptides generated from 5 μl of mouse serum using glycopeptide capture-and-release method, over 3000 peptide peaks were detected and quantified that were present at least at 2 of 3 samples in either group with intensity at least at 2-folds above background noise level. In MS/MS analysis, only a small fraction of peptides (319 unique peptides) were identified. This was due to the complexity of the sample and the fact that the mass spectrometer only had time to sequence a small portion of the peptides, predominantly the highly abundant peptides in each sample. The same under sampling factor was also the major cause of the inconsistency of protein identifications using LC-MS/MS. In this study, reproducible LC-MS was used for quantitative analyses, and this allowed analysis of all the peptide ions in each sample, including those from proteins of low abundance.


While the reduction of peptide redundancy is beneficial for achieving higher coverage of the proteome per analysis, it is also apparent that it leads to the loss of some, potentially important information. First, non-glycosylated proteins are transparent in this system. While it is believed that the majority of serum-specific proteins are in fact glycosylated (Durand and Seta, Clin. Chem. 46:795-805 (2000), intracellular proteins (typically non-glycosylated) that may represent a rich source of biomarkers if leaked into serum might go undetected. Second, the availability of fewer peptides per protein increases the challenge of identifying the corresponding protein. Third, this approach will reveal differences in protein level, or glycosylation level (glycosylation site occupancy). Disease markers that alter other protein post-translational modifications including proteolytic processing will not be detected on a glycopeptide level. Finally, collapsing peptides modified by different oligosaccharide structure into a single signal will obscure potential disease markers that are due to oligosaccharide structure alteration (Durand and Seta, Clin. Chem. 46:795-805 (2000).


In this study, the glycopeptide capture and LC-MS analysis platforms was used to differentiate serum from mice with chemically induced skin cancer from that of non-treated littermates. In this experiment, the mice with skin cancer and their untreated littermates had the same genetic background and lived in the same environment. The study therefore represents a controlled experiment with chemically induced skin cancer being the sole variable. The sera were clearly distinguished by numerous distinct peptides, the abundance of which was consistently increased or decreased between the cancer and control sera. While in this controlled experiment, the low number of samples was sufficient to detect disease-associated signatures, the application of the method to identification of potential biomarkers in much more variable human samples will require the analysis of a larger sample numbers in order to facilitate statistical validation of the data. The current method, at present, has sufficient throughput to perform studies involving a few hundred samples, a number that appears sufficient to generate statistically significant results within a reasonable time frame (Sullivan Pepe et al., J. Natl. Cancer Inst. 93:1054-1061 (2001); Adam et al., Cancer Res. 62:3609-3614 (2002)). By developing a robotic procedure to allow automated sample preparation, and by further optimizing LC-MS analysis procedures and the development of a robust, automated data analysis platform, the performance of the system can be further increased.


In contrast to the widely used SELDI-TOF and similar polypeptide profiling methods, the signals detected in the present method are defined molecular species, mostly peptides ranging in length between 7 and 30 amino acids. These peptides, if selected for CID in a tandem mass spectrometer, are readily sequenced. By adding the coordinates of selected discriminatory peptides to an inclusion list, several serum proteins were identified for which the abundance is increased in correlation with the chemical induction of skin cancer in mice (Table 4). While these proteins are indicators of interesting biology and have been reported to change the abundance in different types of cancer (Vejda et al., Mol. Cell. Proteomics 1:387-393 (2002), they are likely not markers for the specific diagnosis of skin cancer. Proteins useful for cancer detection, diagnosis or stratification might be proteins released in small amounts from the primary lesion, indicators of a specific response of the system to the lesion or other subtle changes in the serum proteome. For the reliable detection of such proteins or patterns of proteins, it is imperative that a large number of candidate molecules are identified, so that potential markers or signatures observed in different diseases, studies and laboratories can be validated, correlated and compared. This will allow the proteomics biomarker discovery community to establish defined molecular signatures as the currency of communication and to distinguish between true biomarkers and coincidental changes.


The identification of discriminatory peptides in this study furthermore indicates that at least some of the proteins changing in abundance in the skin cancer model are moderately to highly expressed. In contrast, serum cancer markers currently in clinical use have concentrations in the ng/ml range. Diamandis has argued that the SELDI-TOF method and by implication similar methods, are about 3 orders of magnitude too insensitive from the sensitivity required to detect such proteins (Diamandis, Mol. Cell. Proteomics 3:367-378 (2004)). The method presented here has the potential to reach ng/ml sensitivity levels and even lower concentration limits if high performance Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) instruments are used. For example, at a concentration of 4 ng/ml, 5 μl of serum sample contains approximately 20 picogram (˜700 attomole) of PSA, an amount that is readily detected in a modern mass spectrometer. In comparison, if non-biased serum digests are analyzed on the same capillary LC-MS system, the total amount of serum that can be applied to the system would be 50 n1 and therefore the concentration limit of detection would be 100 fold reduced, compared with the glycopeptide selected sample. Thus PSA would be well outside the detection limit of such an analysis. If further increases in the concentration limit of detection were required, the glycopeptide capture-and-release method could easily be combined with other peptide fractionation methods, including electophoresis (gel based or free flow electrophoresis) chromatography or affinity depletion.


In summary, selectively isolating peptides from N-linked glycosylated serum proteins has been found to be a powerful method for the analysis of the serum proteome. Together with the high reproducibility of this method, the high level of serum proteome coverage achieved at a moderate throughput suggests that this method will be most useful for the detection of proteins or protein patterns that distinguish individuals in different physiological states.


Example 3
Development of High-throughput LC-MALDI MS/MS Method Using Stable Isotope-labeled Peptides for Biomarker Identification and Quantification

In the past few years MS-based proteomics as a “discovery science tool” has been quickly emerging into an informative quantitative technology for studying systems biology. Quantitative proteomics has demonstrated its potential applications in detection and quantification of diagnostic or prognostics disease markers and therapeutic proteins. The combination of off-line LC separation/spotting and MALDI MS/MS provides several conceptual advantages for such applications: more complete peptide coverage, the ability for repeat or multiple analysis on the same sample, selective MS/MS analysis based on MS information, high mass range, higher contamination tolerance, and easy to interpret data structure.


A straightforward, high-throughput screening technique was developed, which can be applied for clinical diagnostics, using LC-MALDI MS/MS combined with isotope-labeled peptide spiking. The isotope-labeled peptides were synthesized and spiked in the samples with appropriate concentration. The complex peptide mixture were separated and spotted on MALDI plates using HPLC/probot system (LC Packing). The spotted MALDI plate was analyzed in a MALDI TOF/TOF instrument (Applied Biosystems 4700 Proteomics Analyzer) in MS mode. The selected peptides were further analyzed in MS/MS mode for peptide/protein identification and confirmation. The CD fragmentation information of the peptides was searched against a human sequence database for peptide/protein identification and confirmation using a suite of software tools essentially as described in Examples 1 and 2. Quantification was achieved using the abundance ratio of the native peptide and the corresponding spiked peptide.


The isotope-labeled peptides were synthesized and characterized with HPLC and mass spectrometry. The elution properties of the isotope-labeled peptides and the effects of competitive ionization in a complex system were further evaluated by LC-MALDI TOF/TOF. The glycopeptides were captured from human serum proteins using hydrazide chemistry. The glycopeptide mixtures were spiked with isotope-labeled peptides and analyzed by LC-MALDI TOF/TOF. The study has demonstrated that the approach using LC-MALDI TOF/TOF and isotope-labeled peptide spiking can specifically target interesting peptide/protein identifications and quantification, therefore, significantly reducing the time intensive MS/MS analysis and database searching.


In these studies, a novel approach to facilitate the detection and quantification of specific proteins in a complex sample was developed. The highly selective, high throughput platform is built based on a MALDI TOF/TOF spectrometer and using stable isotope labeled peptides as internal standards. The detection and quantification of targeted proteins was accomplished using a complementary approach of specific mass matching, peptide sequencing and peptide quantification. The system demonstrated the capability to detect, selectively identify and quantify proteins of interest in a complex serum sample. These studies were extended and are described in more detail in Example 4.


Example 4
High-Throughput Proteome Screening for Biomarker Detection

This example describes the use of TOF-TOF analysis on an array as an example of qualitative and/or quantitative analysis of serum glycoproteins.


Preparation of formerly N-linked glycosylated peptides from serum. Serum glycoproteins in coupling buffer (100 mM NaAc and 150 mM NaCl, pH 5.5) were oxidized by adding 15 mM of sodium periodate at room temperature for 1 hour. After removal of sodium periodate, the sample was conjugated to the hydrazide resin at room temperature for 10-24 hours. Non-glycoproteins were then removed by washing the resin 6 times with an equal volume of urea solution (8M urea/0.4M NH4HCO3, pH 8.3). After the last wash and removal of the urea solution, the resin was diluted with 3 bed volumes of water. Trypsin was added at a concentration of 1 mg of trypsin/200 mg of serum protein and digested at 37° C. overnight. The peptides were reduced by adding 8 mM TCEP (PIERCE, Rockford, Ill.) at room temperature for 30 min, and alkylated by adding 10 mM iodoacetamide at room temperature for 30 min. The trypsin-released peptides were removed by washing the resin three times with 1.5 M NaCl, 80% Acetonitrile/0.1% trifluoroacetic acid (TFA), 100% methanol, and six times with 0.1 M NH4HCO3. N-linked glycopeptides were released from the resin by addition of peptide-N-glycosidase F (PNGase F) (at a concentration of 1 ml of PNGase F/40 mg of serum protein) (New England Biolabs; Beverly Mass.) overnight. The released peptides were dried and resuspended in 0.4% acetic acid for mass spectrometry analysis.


Synthesis of stable isotope labeled peptides. Fluorenylmethoxycarbonyl-derivatized phosphoamino acid monomers were from AnaSpec, Inc (San Jose, Calif.). Fmoc-derivatized stable-isotope monomers containing one 15N and five to nine 13C atoms were from Cambridge Isotope Laboratories (Andover, Mass.). Pre-loaded Wang resins were from Applied Biosystems. Synthesis scale was 5 pima Amino acids activated in situ with 1-H-benzotriazolium, 1-[bis(dimethylamino)methylene]-hexafluorophosphate(1-),3-oxide: 1-hydroxybenzotriazole hydrate were coupled at a 5-fold molar excess over peptide. Each coupling cycle was followed by capping with acetic anhydride to avoid accumulation of one-residue deletion peptide byproducts. After synthesis, peptide-resins were treated with a standard scavenger-containing trifluoroacetic acid-water cleavage solution, and the peptides were precipitated by addition to cold ether. Peptides were purified by reversed-phase C18 HPLC using standard TFA/acetonitrile gradients and characterized by matrix-assisted laser desorption ionization-time of flight (Biflex III, Bruker Daltonics, Billerica, Mass.) and ion-trap (ThermoFinnigan, LCQ DecaXP) MS.


LC/Probot fractionation and MALDI TOF/TOF analysis. The glycopeptide mixture was separated by reverse phase C18 column and spotted on a MALDI plate. The separation was performed using an Ultimate HPLC system (LC Packing/Dionex, Sunnyvale, Calif.) coupled with a Famos micro autosampler (LC Packing/Dionex, Sunnyvale, Calif.). A 100 minute gradient was used with liquid chromatography (LC) for peptide separation using a house packed C18 column. The eluent from the capillary column was mixed with the α-cyano-4-hydroxycinnapinic acid matrix solution (Agilent Technologies, Palo Alto, Calif.) in a mixing tee before spotting onto the MALDI plate. The matrix solution was delivered with a syringe pump. The fractions were automatically collected with 30 second intervals and spotted on a 192-well MALDI plate (Applied Biosystems, Foster City, Calif.) using a Probot Micro Fraction collector (LC Packing/Dionex, Sunnyvale, Calif.). The samples were analyzed by a MALDI TOF/TOF tandem mass spectrometer (ABI 4700 Proteomics Analyzer, Applied Biosystems, Foster City, Calif.). Both MS and MS/MS data were acquired with a Nd:YAG laser with 200 Hz sampling rate. For MS spectra, 1000 laser shots per spot were used. MS acquisition for the entire plates took 16 minutes with a total of 192000 laser shots per plate. MS/MS mode was operated with 1 KeV collision energy. The CID was performed using air as the collision gas. A typical 2000 laser shots was used for MS/MS acquisition. Both MS and MS/MS data were acquired using the instrument default calibration.


Database searching of MS/MS data. MS/MS data were searched against the human protein database from NCBI and a standard peptide database containing the spiked peptides. The mass tolerance of the precursor peptide was set at ±0.4 Daltons (Da), and the database search was set to expect the stable isotope labeling and the following modifications: carbonxymethylated cysteins, oxidized methionine and an enzyme-catalyzed conversion of asparagine to aspartic acid at the site of carbohydrate attachment. No other constrains were include in the SEQUEST search. All of the MS/MS spectra were manually checked to verify the validity of the results.


Quantification. Binary files of MS survey scans were exported using 4700 Explorer software. Each file is corresponding to a single MS spectrum. The peak information, including spot number, mass and intensity, was extracted from the binary files and converted to text files. The individual files were then combined into a single text files, which contains the peak information from all the spots. The file was scanned for peptides that had been eluted across more than one sample spot. The signal intensities of these peptides from each adjacent spots were summed together to determine an accurate intensity over the entire peptide elution profile. The quantification of targeted peptides was achieved using the abundance ratio of a native peptide to the corresponding spiked stable isotope labeled peptide, which the amount is known. The quantification of each identified peptide was manually checked to verify the validity of the results.


The method used is schematically outlined in FIG. 10. It is conceptually simple and consists of two main steps, the production of ordered peptide arrays and their interrogation by MALDI-MS and MS/MS. For the production of ordered peptide arrays, protein samples (untagged proteins or proteins labeled with specific stable isotope tags) were subjected to tryptic digestion and combined with a cocktail of defined amounts of isotopically labeled reference peptides, each of which uniquely identified a particular protein or protein isoform (proteotypic peptides). The reference peptides were generated by chemical synthesis and contained heavy stable isotopes. The combined peptide mixture was separated by capillary reverse phase chromatography (μLC), and the eluting peptides are deposited on a sample MALDI plate to form an ordered peptide array in which each array element contains peptides that are derived from the digested sample proteins and/or from the cocktail of reference peptides. For the detection and quantification of the target polypeptides, that is, those proteins for which a reference peptide was added to the sample, the sample was analyzed using a matrix assisted laser desorption/ionization (MALDI) tandem time-of-flight (TOF-TOF) mass spectrometer that operated under a data-driven instrument control protocol, carrying out the following sequential steps A-C.


Step A) High speed MS scanning. MALDI-MS spectra were acquired from each array element, generating two types of signals, one representing the signals of the peptides for which no reference peptide was added, appearing as single peaks, and the other representing the signals for those peptides for which a reference peptide was added, appearing as paired signals with a mass difference that precisely corresponded to the mass differential encoded in the stable isotope tag. B) Peptide quantification. The signal intensities of the isotopically heavy and light forms of a signal pair were determined and used to calculate the absolute abundance of the peptide derived from the protein sample. As reverse-phase chromatography could split a specific pair of isotopic peptides across several consecutive spots on the MALDI plate, it was necessary to process the data prior to quantification. A specifically developed software tool scanned the MS data files for peptides (pairs) that eluted across more than one sample spot, summed the signal intensities of the corresponding signals from adjacent spots and used the integrated value for quantification, thus ensuring higher quantitative accuracy. C) Optional confirmation of peptide identity by MS/MS. In this method, proteins are primarily identified by correlating the array position and the accurately measured mass of each isotopically labeled peptide pair in the array with a list of added reference peptides with known mass. Optionally, peptide sequences could be confirmed by subjecting selected peptides to CID and sequence database searching of the resulting spectra (Eng et al., J. Am. Soc. Mass Spect. 5:976-989 (1994)).


To test the robustness of peptide identification reference peptides were added to a complex glycopeptide mixture extracted from human serum (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)) and spotted onto the sample plate under slightly different chromatography conditions. The plates were then analyzed and the peptides were identified in the sample mixture based on their accurate mass, the paired nature of the signal and the location on the peptide array. FIG. 11 shows the extracted ion trace over the chromatographic separation range for two consecutive runs. It is apparent that peptide LADLTQGEDQYYLR (1683.8 Da, derived from Clusterin precursor; SEQ ID NO:) was unambiguously identified in the complex background even though the targeted peptide pair was found in different spot positions in the two runs. The accurate mass, together with the paired nature of the signal, were sufficient for the identification of the target peptide. With increasing complexity of the analyzed sample, the chance that these criteria are insufficient for unambiguous peptide identification also increases. In these cases, peptide identities were confirmed by the fragment ion spectra of the precursors that are isobaric to the targeted peptide. An example of peptide confirmation by CID is illustrated in FIG. 12. Two peaks that corresponded to the mass of the stable isotope labeled reference peptide LHEITDETFR (1269.4 Da, from proteins similar to RIKEN cDNA 2610528G05 gene (Fragment); SEQ ID NO:) were detected within the mass search window. The expected signal was discriminated from the unexpected one based on the CID spectrum. The SEQUEST search results (Eng et al., supra, 1994) of the obtained spectra indicated that the precursor ion with higher intensity, eluting across spot 133 to spot 138, was the target peptide. Using this approach that limits the number of sequencing operations, the platform not only provided the high confidence for peptide identification, but also operated in a high throughput mode. For instance, with a laser sampling rate at 200 Hz available in the 4700 MALDI TOF/TOF instrument, a 192-well sample plate can be analyzed in less than 1 hour by MS scan of 192 spots followed by 200 MS/MS scans for selected peptide sequence validation.


To assess the performance of the system for rapid profiling of selected proteins in complex mixtures, N-glycoproteins were analyzed in human serum. The serum-derived peptides were generated from serum proteins by using a solid-phase glycopeptide capture and release method as described above (Zhang et al., What is claimed is: Nat. Biotechnol. 21:660-666 (2003)). In brief, serum glycoproteins were immobilized on a solid phase via their glycostructure. Immobilized glycoproteins were trypsinized and the non-glycosylated peptides were washed to waste. The peptides that carried an N-linked carbohydrate on the native protein were isolated in their de-glyscosylated form using the enzyme PNGA'se F that cleaves between the carbohydrate and the peptide, converting the carbohydrate anchoring Asn into an Asp residue. The serum derived sample was added with a cocktail of iostopically labeled reference peptides. The composition of the reference peptide sample is summarized in Table 5.









TABLE 5







List of reference peptides labeled with heavy stable isotope.










Swiss-





Prot/TrEMBL

Synthesized stable isotope


accession No.
Protein annotation
labeled peptide sequences





P03952
Plasma kallikrein precursor
IVGGTDSSWGEWPWQVSLQ VK






P08185
Corticosteroid-binding globulin precursor
AQLLQGLGFD LTER





P55058
Phospholipid transfer protein precursor
IYSDHSALESLALIPLQAP LK





P10909
Clusterin precursor
LADLTQGEDQYY LR





P51884
Lumican precursor
LGSFEGLVDLTFIH LQHNR





P19652
Alpha-1-acid glycoprotein 2 precursor
SVQEIQATFFYFTPDKTEDTIF LR





P02750
Leucine-rich alpha-2-glycoprotein precursor
LPPGLLADFTL LR





Q9H4M1
Glycosylphosphatidylinositol-specific
FHDVSESTHWTPFLDAS VHYIR



phospholipase D precursor, Phosphatidylinositol-



glycan-specific phospholipase D 1 precursor





P04004
Vitronectin precursor
DGSLFAFR





P04004
Vitronectin precursor
DNATVHEQVGGPSLTSD LQAQSK





NA
Prenylcysteine lyase precursor
GELDTSIFSSR





Q9UK55
Protein Z-dependent protease inhibitor precursor
LPYQGDATmLVV LmEK





P04180
Phosphatidylcholine-sterol acyltransferase
mAWPEDHVFISTPS FDYTGR



precursor





Q13201
Endothelial cell multimerin precursor
FNPGAESVVLSDST LK





P40197
Platelet glycoprotein V precursor
ISALGLPTDLTHILL FGmGR





Q04756
Hepatocyte growth factor activator precursor
CFLGDGTG YR





P41222
Prostaglandin-H2 D-isomerase precursor
SVVAPATDGGLDLTSTF LR





P41222
Prostaglandin-H2 D-isomerase precursor
WFSAGLASDSSW LR





P11597
Cholesteryl ester transfer protein precursor
GHFIYKDVSEDLPLPTFSPTL LGD




SR





P33151
Vascular endothelial-cadherin precursor
EVYPWYDLT VEAK





P02786
Transferrin receptor protein 1
KDFEDLYTPVDGSIVI VR





P04278
Sex hormone-binding globulin precursor
LDVDQA LDR





P06681
Complement C2 precursor
TmFPDLTD VR





Q96KN2
Glutamate carboxypeptidase-like protein 2
LVPHmDVSA VEK



precursor





Q9UGM5
Fetuin-B precursor
GCDDSDVLAVAGFA LR





Q9UGM5
Fetuin-B precursor
VLYLAAYDCTLRP VSK





P06276
Cholinesterase precursor
DDYTKAEEILSR





P07333
Macrophage colony stimulating factor I receptor
HTDYSFSPWHGFTIHR



precursor





P03952
Plasma kallikrein precursor
LQAPLDYTEFQKPICIPSK





P05156
Complement factor I precursor
DGTAVCATNR





P04114
Apolipoprotein B-100 precursor
YDFDSSmLYSTAK





P80188
Neutrophil gelatinase-associated lipocalin
SYDVTSVLFR



precursor





P54289
Dihydropyridine sensitive L-type, calcium
IDVNSWIEDFTK



channel alph-2/delta subunits precursor





P40225
Megakaryocyte stimulating factor
DGTLVAFR





Q13876
Quiescin, Bone-derived growth factor (Fragment)
DGSGAVFPVAGADVQTLR





Q16769
Glutaminyl-peptide cyclotransferase precursor
NYHQPAILDSSALR





P40189
Interleukin-6 receptor beta chain precursor
ETHLETDFTLK





NA
Nectin-like protein 2, Hypothetical protein
FQLLDFSSSELK



HEMBA1001879





NA
hypothetical protein XP_174441
SHAASDAPEDLTLLAETADAR





P13473
lysosomal-associated membrane protein 2
IAVQFGPGFSWIADFTK



precursor, Lysosome-associated membrane



glycoprotein 2 precursor





P13473
lysosomal-associated membrane protein 2
WQMDFTVR



precursor, Lysosome-associated membrane



glycoprotein 2 precursor





Q96CX1
Similar to RIKEN cDNA 2610528G05 gene
LHEITDETFR



(Fragment)





Q07954
Low-density lipoprotein receptofrelated protein
FDSTEYQVVTR



1 precursor





P01009,
Alpha-1-antitrypsin precursor
QLAHQSDSTNIFFSPVSIATAFAmL




SLGTK





Q86SU4,
Similar to RIKEN cDNA 1300018K11 gene
QGSLGLQYDASQEWDLR





Q8N5V4
(Fragment)





Q16853
Membrane copper amineoxidase
IQmLSFAGEPLPQDSSmAR





P23470
Protein-tyrosine phosphatasegamma precursor
SDFSQTmLFQADTTR





P01033
Metalloproteinase inhibitor 1 precursor
FVGTPEVDQTTLYQR





Q92859
Neogenin precursor
TLSDVPSAAPQDLSLEVR









The combined sample was separated by capillary reverse phase chromatography and spotted onto the sample plate in 192 spots and analyzed by MALDI-MS. Results from this analysis are shown in FIG. 13. FIG. 13A shows the base peak display of the detected peptides, indicating that peptides were detected over the whole separation range, with the majority of peptide signals concentrated between fractions 45 and 165. FIG. 13B shows the mass spectrum of a representative spot, indicating the complexity of the sample analyzed. In total, more than 2500 unique precursor ions were detected in MS mode. To identify and quantify the target peptides, the computer driven selective peptide analysis method described above was used. FIG. 14 indicates that the added reference peptides could be detected and identified over a broad range of the chromatographic separation range in a very complex sample. FIG. 14A shows the number of precursor ions detected in each spot in MS mode; and FIG. 14B shows the distribution of spike-in peptides over the chromatographic separation range. The distribution profile of the spike-in peptides were extracted from the very complex background.



FIG. 15 shows that the peptides could be identified and quantified even though they represented relatively minor peaks in a complex spectrum. Data for peptide FDSTEYQVVTR (SEQ ID NO:), which was derived from low-density lipoprotein receptor-related protein 1 precursor and 13C labeled on residue valine 9, are shown. Using the specific mass matching to search the MS data, the spot (or spots) containing the peptide pairs was located. By examining the MS spectrum, the paired peaks (spiked and native) were identified. The mass of the spike-in peptide and native peptide were 1349.6 Da and 1344.6 Da, respectively. The identification of the peptides was further confirmed by MS/MS analysis and sequence database searching. Since the amount of the spike-in peptide was known, the concentration of the native peptide could be calculated based on the signal intensity ratio of the paired peptide signals. Consequently, the identification and quantification of the related proteins in a complex serum sample was accomplished. The concentration of the protein in a serum sample can be calculated according to equation 1:









C
=




(


A
n

/

A
s


)

*

M
s



V
a


*

(


V
b

/
V

)






Equation





1







where An and As are the integrated peak area of the native and spike-in peptide in the MS spectrum, respectively. Ms is the amount of stable isotope labeled peptide spiked in the glycolpeptide mixture. Va is the volume of the glycopeptide mixture used for MALDI TOF/TOF analysis. Vb is the total volume of the glycopeptide mixture extracted from the serum sample. V is the total volume of the serum used for glycoprotein extraction. It is important to note that the accuracy of the result estimated from the above formula depends on many factors, including data processing, sample purification, and glycopeptide extraction efficiency, and these factors can be readily determined.


To demonstrate the capacity of the system to rapidly and quantitatively profile selected serum proteins, isolates from four human serum samples using the glycopeptide capture and release method described above were spiked with reference peptides and analyzed by offline LC-MALDI TOF/TOF platform. The proteins and the corresponding signature peptides for which both spike-in and native signals are detected by the platform are listed in Table 6. The results are presented in the form of a peptide map in FIG. 16. The x axis represents the mass of the targeted native peptides and the y axis indicates the abundance ratio of a native peptide to the corresponding isotope-labeled peptide, providing the quantitative information describing the corresponding protein. The result demonstrates that even in very complex samples with an enormous number of proteins that may fluctuate within a population, the key elements that indicate the state of a specific biological condition can be effectively extracted and expressed quantitatively by this approach.










TABLE 6







List of proteins and the corresponding signature



peptides used in FIG. 16.












Mass



Protein
Peptide sequence
(m/z)





Apolipoprotein B-100 precursor
YDFN*SSM#LYSTAK
1542.7






Corticosteroid-binding globulin precursor
AQLLQGLGFN* LTER
1559.8





Endothelial cell multimerin precursor
FNPGAESVVLSN*ST LK
1662.9





Clusterin precursor
LAN*LTQGEDQYY LR
1683.8





Neogenin precursor
TLSDVPSAAPQN*LSLE VR
1897.1





Transferrin receptor protein 1
KDFEDLYTPVN*GSIVI VR
2065.4





Lumican precursor
LGSFEGLVN*LTFIH LQHNR
2195.5





Phospholipid transfer protein precursor
IYSN*HSALESLALIPLQAP LK
2278.7





Vitronectin precursor
N*NATVHEQVGGPSLTSD LQAQSK
2381.5





*enzyme-catalyzed conversion of asparagine to aspartic acid at the site of carbonhydrate attachment.


#methionnine oxidation.



amino acid labeled with 15N and 13C.







These results demonstrate a method for proteome screening and an experimental platform that supports the method. The method has the potential to reach very high throughput because the redundancy common to LC-MS/MS based proteomics experiments is eliminated and the analysis is focused on specific, information rich analytes. The offline LC-MALDI TOF/TOF based platform provides several advantages for such an approach. These advantages include more complete peptide coverage, low redundancy, the option to perform repeated or multiple analyses on the same sample, high mass range and accuracy, selective MS/MS analysis based on MS information, higher contamination tolerance, and easy to interpret data structure. The generation of predominantly singly charged peptides by MALDI simplifies the quantitative analysis. Global identification can be performed on the same MALDI plate afterwards, if the information is needed. The ability to reexamine and verify the same sample set can be very beneficial for quantitative applications.


It noteworthy that not all of the spike-in peptides behaved the same in a complex sample. In selection of reference peptides, criteria, such as biological significance, sensitivity for mass analysis, good mass range, and without potential mass overlap with other peptides, and the like, need to be satisfied. The development of proteome-screening technology indicates an important transition of quantitative proteomics from a sole discovery mode into a multi-phase technology. The implementation of the browsing/screening mode allows the utilization of the extensive genomic and proteomic knowledge that has been accumulated by biology and medicine, and focus on analyzing the key elements that uniquely represent a specific biological condition, as was demonstrated in this study. Technically, since the identification and quantification of targeted proteins is based on searching and identifying the corresponding signature peptide pairs directly, the approach significantly reduces sample complexity, therefore improving the throughput and identification confidence. It provides a greater analytical dynamic range and facilitates the detection of low abundance proteins. The ability to describe specific protein patterns associated with certain biological conditions within a complex background in an absolute quantitative way provides the feasibility for data standardization. The proteome-screening technology described in this example opens new opportunities for quantitative proteomic analysis and can be developed into a high throughput technology for clinical diagnostic at proteome level.


Example 5
Identification of Serum Glycoproteins

Thousands of N-linked glycosylation sites have been isolated and identified using the methods described above. Sixty peptides have been synthesized according to the identified N-linked glycosylation sites, and one N-linked glycopeptide with heavy isotope labeling was spiked to human sera of different persons to quantify the abundance of the glycopeptide. Table 7 shows the N-linked glycosylation sites of glycopeptides (SEQ ID NOS: 1-3244) identified from human serum/plasma using the above-described methods. Table 8 shows N-linked glycopeptides (SEQ ID NOS: 3245-3369) identified from human serum/plasma using the above-described methods and which do not contain the consensus (N—X-T/S) glycosylation motif. Asparagines modified in the peptide sequence are marked (*).









TABLE 7







N-linked glycosylation sites identified from human serum/plasma.










Protein IPI #

Peptide



(VERSION 2.28)
Identified Peptide Sequences
Probability













IPI00000001
R.EFVMQVKVGN#HTAEGTGTNK.K
0.7332






IPI00000013
Y.RPENSVAN#DTGFTVVAPGKEK.A
0.6348





IPI00000070
M.SDEVGCVN#VTLCEGPNK.F
0.6201





IPI00000075
R.LASPPSQGEVPPGPLPEAVLALYN#STR.D
0.9994





IPI00000087
K.QFSLN#WTYQECNN#CSEEMFLQFR.M
0.6626





IPI00000124
R.N#LSFLDLCFTTSIIPQM*L.V
0.55





IPI00000137
K.YEFCPFHN#VTQHEQTFR.W
1





IPI00000151
R.SEVELEVLGDTEGLN#LSFTAI.C
0.8574





IPI00000160
R.N#SSSSGSSGAGQK.R
0.7791





IPI00000213
M.GAAVTLKN#LTGLNQRR.-
0.9553





IPI00000213
R.AM*LAAIYN#TTELVMM*QDSSPDFED.T
0.7446





IPI00000321
E.RLASSN#SSQSLAPLMMEVPMLSSLGVTNSK.S
0.7342





IPI00000330
R.KMAAN#SSGQGFQNK.N
0.9623





IPI00000330
L.M*QN#QSSTNHPGASIALSRPSLNKDFR.D
0.7219





IPI00000352
L.DTCPSSSTASSISSSGGSSGSSSDN#RTYR.Y
0.6171





IPI00000375
Q.RNAENTKSN#VTH.K
1





IPI00000458
K.NNYGLLLNEN#ESLFLM*VVLWK.I
0.9232





IPI00000691
K.VFDSLLN#LSSTLQATR.A
0.9897





IPI00000758
I.N#STLKGRWR.V
0.514





IPI00000764
R.AQPLINLQMVN#ASLYEHVER.M
0.5611





IPI00000775
R.NN#ISKLTDGAFWGLSKMHVLH.L
0.5702





IPI00000792
K.GIDIIIEMLANVN#LSKDL.S
0.6397





IPI00000812
S.MISNMN#ASR.A
0.5828





IPI00000828
M.KKDAEEDDSLAN#SSDLLICELLETGDNR.E
0.6778





IPI00000837
R.AN#ASFTWVASDGWGAQESIIK.G
0.5568





IPI00000839
R.NVN#FSGIAGNPVTFNENGDAPGR.Y
0.7319





IPI00000845
R.ENALNNLDPNTELN#VSR.L
0.9806





IPI00000877
R.KDIN#TTAQ.N
0.7877





IPI00000877
R.LSALDNLLN#HSSM*FLK.G
0.9941





IPI00000877
K.VIN#ETWAWK.N
0.9549





IPI00000899
M.VDKYIPN#ISM*CLKDSDPFIR.K
0.6638





IPI00001091
K.RGRGNFGGQSEQENTLNQLLVEMDGFN#T.T
0.6573





IPI00001120
L.TSLSVTNTN#LSTVPFLAFK.H
0.7904





IPI00001120
R.VLN#VSQNLLET.L
0.9643





IPI00001120
K.LVPLGVFTGLSN#LTK.L
0.7469





IPI00001152
S.YQPWGNVPDAN#YTSDEEEEK.Q
0.6651





IPI00001451
S.EEN#STFR.N
0.8398





IPI00001458
K.LFKEVASLQENFEVFLSFEDYSN#SSLVADLR.E
0.9428





IPI00001461
G.FVN#STM*EEAGLCGLREK.A
0.6389





IPI00001497
E.NAPN#GTLVVTVN#ATDLDEGVNK.D
0.5032





IPI00001510
K.EKGN#STTDNSDQ.-
0.723





IPI00001522
A.SSFKGYIEN#CSTPNTYICMQR.T
0.5919





IPI00001586
K.KAADTAVGWALGYM*LN#LTNLIPADPPGLR.K
0.9623





IPI00001592
R.VSVNTAN#VTLGPQLM*EVTVYRR.H
0.9272





IPI00001592
K.NDRN#SSDETFLKDLPIMFD.V
0.6647





IPI00001593
K.NGGSILFYTGNEGDIIWFCN#NTGFM*WDVAEELK.A
0.6036





IPI00001651
Y.KPLN#DSVRAQYSNWLLAGNLALSPTGNAKK.P
0.7263





IPI00001654
K.KMNMM*N#RSYN#VTLKR.Q
0.7934





IPI00001662
K.GRM*STLTFFN#VSEK.D
0.7988





IPI00001672
K.KSLELNPN#NSTAM*LR.K
0.7527





IPI00001759
K.IN#STADLDFIQQAISYSSFPFWM*GLSRR.N
0.8974





IPI00001866
R.GSDDGDGESFN#GSPTGSIN#LSL.D
0.6138





IPI00001872
R.ETVPEYN#LSITAR.D
0.5406





IPI00002054
K.GTVLPVATIQN#ASTAM*LM*AASVAR.K
0.5668





IPI00002070
K.TLEELHLTGN#LSAENNR.Y
0.6831





IPI00002103
M.TVKVDGVAQDGTTMYIHNKVHN#RTR.T
0.7155





IPI00002159
R.KFSFYGN#LSPRR.S
0.6247





IPI00002159
K.SCSSHSSSNTLSSN#TSSNSDDK.H
0.7344





IPI00002185
K.N#WSALLTAVVIILTIAGNILVIM*AVSLEKK.L
0.6377





IPI00002197
K.FLMSN#ETVLLAKHNIFTLALMIV.N
0.9243





IPI00002224
R.RGDN#DSHQGDLEPILEASVLSSHHK.K
0.6188





IPI00002232
K.LRKEQLICEELNEN#QSTPKKEK.Q
0.5897





IPI00002251
R.VPPTLN#SSPCGGFTLCK.A
0.5889





IPI00002272
R.KKVTAQN#LSDGDIKLLVNIVRAYDIPVR.K
0.6856





IPI00002283
R.ETPPLEDLAAN#QSEDPRNQRLSK.N
0.807





IPI00002283
K.NGRYQPSIPPHAAVAAN#QSRARR.G
0.8881





IPI00002293
K.CGSAYEPEN#QSK.D
0.5995





IPI00002320
K.EEFVIHTIFPPNGM*NLYKNN#HSESSSN#R.S
0.8932





IPI00002335
M.NSEFN#LSLLAPCLSLGMSEISGGQK.S
0.6653





IPI00002354
R.AFDMLSECGFHM*VACN#SSVTASFINQYT.D
0.6123





IPI00002366
-.MSTLSN#FTQTLEDVFR.R
0.5344





IPI00002374
K.TNLDDDVPILLFESN#GSLIYTPTIEIN#SSHHSAMEK.R
0.63





IPI00002526
A.N#ASGYM*YETSYR.R
0.6113





IPI00002541
K.AFN#STLPTMAQMEK.A
0.8872





IPI00002547
R.LFCDPTFLPEN#DSLFYNRLLPGK.V
0.7198





IPI00002580
K.YEIYLN#SSLVQFLLS.R
0.7748





IPI00002632
K.RNHM*LLLYPREILILDLEVN#QTVGVIAIERTGV.P
0.5125





IPI00002647
K.LLKGDIDIGSQN#GTDLFGFGNTHEYPDLQMIL.S
0.8714





IPI00002666
N.GPDTNHQNPQN#KTSPFSVSPTGPSTK.I
0.6038





IPI00002689
K.AQHEFTEFVGATM*FGTYNVISLVVLLNMLIAMMN#NS.Y
0.5671





IPI00002707
K.TN#RTNKPSTPTTATRKKKDLKNFR.N
0.6502





IPI00002707
R.NVDSNLANLIMNEIVDN#GTAVK.F
0.6768





IPI00002790
K.M*YSEGSDIVPQSN#ETALHYFK.K
0.5645





IPI00002806
-.M*NQFGPSALIN#LSN#FSSIKPEPASTPPQGSM*AN.S
0.9191





IPI00002816
F.KNFVITYN#RTYESKEEARWR.L
0.7172





IPI00002876
H.SFLVHLIGLLVWQCDISVSPVAAIVTDIFN#TSDGGR.F
0.6888





IPI00002984
K.NPELSGSLMTLSN#VSCLSNTPARK.I
0.5173





IPI00003048
P.DN#ASGCGEQINYGR.V
0.9521





IPI00003057
R.DVNICN#MTSHLPAAASAS.P
0.8908





IPI00003096
R.RLSLSQSITDDDLEAIAN#DSEEEIIKPR.S
0.5042





IPI00003323
K.TSKSEENSAGIPEDN#GSQRIEDTQK.L
0.9714





IPI00003323
K.SDSSKSESDSSDSDSKSDSSDSN#SSDSSDNS.D
0.957





IPI00003325
R.DLAELKSSLVN#ESEGAAGSAGIPGVPGAGAGAR.G
0.5809





IPI00003351
K.HIPGLIHN#MTAR.C
0.9991





IPI00003365
R.KVHLM*GYNCN#ATTK.C
0.9023





IPI00003370
K.SIEQSIEQEEGLN#RSSADLR.I
0.7622





IPI00003384
R.N#LSVDGKNVDMAGFIANN#GTREG.C
0.6318





IPI00003451
R.FSSFVPVTIPHATTAN#TSV.L
0.6909





IPI00003478
K.CEFLANLHITALLN#VSRR.T
0.5036





IPI00003480
K.DIDVSPKHVGFATIPRN#YTMSFLPR.-
0.6035





IPI00003515
K.AKSDQLLSSNEN#FTNK.V
0.8642





IPI00003515
K.N#ISLTKQIDQLSK.D
0.6204





IPI00003515
K.LM*SLAN#SSEGKVDKVLM*R.N
0.6075





IPI00003562
K.TEPMDADDSNN#CT.G
0.5459





IPI00003590
K.N#GSGAVFPVAGADVQTLR.E
0.9966





IPI00003706
K.KPYVSLAQQMAPPSPSN#STPN#SSSGSNGNDQLSK.T
0.6332





IPI00003834
R.DAGGELAN#LSQAELVDLVQWTDLILFDYLTANFDR.L
0.8774





IPI00003897
R.DHGSPTLSAN#VSLRVLVGDRNDNAPR.V
0.9405





IPI00003919
K.NYHQPAILN#SSALR.Q
0.9994





IPI00003932
T.N#CTTEASMAIRPK.T
0.5913





IPI00003965
K.VLKN#SSLAEFVQSLSQTM*GFPQDQIR.L
0.6703





IPI00004022
T.N#QTPPTYN#KTNK.F
0.8329





IPI00004022
R.IDDLQM*VLN#QTEDHRQR.V
0.9878





IPI00004047
K.M*PGDIKNWVDAHM*NCEDIAMNFLVAN#VTGK.A
0.5867





IPI00004047
K.CTN#LSEGVLSVRK.R
0.783





IPI00004067
K.SPDTFM*IPM*ALPNDN#GSVSG.V
0.7678





IPI00004084
K.MSLVM*PAM*APN#ETLSGR.G
0.5375





IPI00004121
R.YDGAVQVMATQDGAN#FTAARQGYR.R
0.6451





IPI00004237
K.TNQGIPELN#ASSVGM*AK.A
0.7276





IPI00004247
R.CSAEEATEGLM*N#LSPSAM*K.N
0.5785





IPI00004362
S.LPSWKSLLNVPMEDVN#LSSGHIAR.V
0.6084





IPI00004368
-.MAHSQNSLELPININ#ATQITTAYGHR.A
0.7548





IPI00004388
K.EN#NTGYIN#ASHIK.V
0.5666





IPI00004399
E.FKNNFLNIDPITMAYSLN#SSAQER.L
0.8111





IPI00004413
R.ECTCPPGMFQSN#ATCAPHTVCPVGWGVRKK.G
0.545





IPI00004416
L.KSN#NSM*AQ.A
0.5174





IPI00004457
R.IQM*LSFAGEPLPQN#SSM*AR.G
1





IPI00004457
R.KEEEPSSSSVFNQNDPWAPTVDFSDFINN#ETIAGK.D
0.999





IPI00004462
R.GGLN#LTAVTVAAENN#HTVAFLGTSDGRILK.V
0.6774





IPI00004462
R.EAESLQPM*TVVGTDYVFHN#DTK.V
0.9936





IPI00004462
R.SFASGGRSIN#VTGQGFSLIQR.F
0.8388





IPI00004480
K.EHAVFTSNQEEQDPAN#HTCGVK.S
0.9335





IPI00004494
F.GLFN#TTSNIFR.G
0.734





IPI00004503
M.FMVKNGN#GTACIM*AN#FSAAFSVNYDTK.S
0.9952





IPI00004503
R.GHTLTLN#FTR.N
0.9941





IPI00004527
K.GVSFN#ESAADNLK.L
0.7928





IPI00004529
R.IDWDDDKYYN#TSLETR.L
0.9999





IPI00004534
K.FCDN#SSAIQGKEVRFLR.P
0.5374





IPI00004557
M.SN#YSSSSLLSGAGK.D
0.7134





IPI00004560
T.KNVNPN#WSVNVK.T
0.5555





IPI00004560
K.IKKHFNTGPKPN#STAAGVSVIATTALDK.E
0.9054





IPI00004565
-.M*ALNN#VSLSSGDQRSR.V
0.8782





IPI00004573
R.AN#LTNFPEN#GTFVVNIAQLSQDDSGR.Y
0.9994





IPI00004573
K.VPGN#VTAVLGETLK.V
1





IPI00004573
R.LSLLEEPGN#GTFTVILNQLTSR.D
1





IPI00004573
K.WN#NTGCQALPSQDEGPSK.A
0.99





IPI00004576
M.PVSSSSPLSSLTFNAINRYTN#TSK.T
0.6661





IPI00004617
R.EQQFN#STFR.V
1





IPI00004618
R.EEQFN#STYR.V
1





IPI00004641
W.SESGQN#VTAR.N
0.7299





IPI00004641
K.TPLTAN#ITK.S
1





IPI00004641
K.HYTN#PSQDVTVPCPVPPPPPCCHPR.L
1





IPI00004641
R.LSLHRPALEDLLLGSEAN#LTCTLTGLR.D
1





IPI00004641
R.LAGKPTHVN#VSVVMAEVDGTCY.-
1





IPI00004670
R.IAEN#YTAVVSPDIASIDLNTFEFNK.P
0.5166





IPI00004671
K.KNADN#NSSAFTALSEER.D
0.6348





IPI00004712
K.SVVEKM*KN#ISNHLVIEANLDGELNLK.I
0.5179





IPI00004758
K.VSPRGIILTDN#LTNQLIEN#VSIYR.I
0.98





IPI00004758
K.APLSTVSAN#TTNMDEVPRP.Q
0.9034





IPI00004901
T.ANSQVM*GSAN#STLR.A
0.8959





IPI00004931
R.YN#VSQQALDLQNLR.F
0.7112





IPI00004957
R.IDGSQNFN#ETWENYK.Y
0.9995





IPI00004957
K.NEEVKN#M*SLELNSK.L
0.9674





IPI00004970
C.FYNLELGDM*SLSDN#ASMCLM*SIIK.K
0.5294





IPI00004977
R.DGVLLCQLLHN#LSPGSIDLK.D
0.9554





IPI00005037
K.TN#VTHEEHTAVEK.I
0.5072





IPI00005084
I.WEKAN#LTLPR.G
0.5219





IPI00005089
K.VN#KTLTSLNIESNFITGTGILALVEALK.E
0.6373





IPI00005101
K.KN#ITYYDSM*GGINNEACR.I
0.7313





IPI00005107
K.DGYDLVQELCPGFFFGN#VSLCCDVR.Q
0.5078





IPI00005118
R.RQAVELNVVAIVN#DTVG.T
0.8452





IPI00005118
R.RQGAYNIDVVAVVN#DTVGTM*M*.G
0.8535





IPI00005146
K.LN#VSDLYKLTDTVAIR.E
0.8929





IPI00005188
S.VGAAPN#ASDGLAHSGK.V
0.5798





IPI00005258
K.YEYLMTLHGVVN#ESTVCLM*GHER.R
0.8617





IPI00005264
K.ANGLLDFDIFYN#VTGCLRN#MSSAGADGRK.A
0.9686





IPI00005270
M.M*SVQANTGPPWESKN#STAVWR.G
0.7247





IPI00005439
R.VLYLAAYN#CTLRPVSK.K
1





IPI00005439
R.GCN#DSDVLAVAGFALR.D
1





IPI00005485
K.GPGEVIPGGN#HSLYSLK.G
0.5225





IPI00005512
K.EFYLTPNSPAEMLHN#VTLALELLK.D
0.5241





IPI00005543
K.N#WTFGPQDVDELIFMLSDSPGVMCR.P
0.7216





IPI00005549
K.EDGSGSAYDKESM*AIIKLN#NTTVLYLK.E
0.8451





IPI00005565
T.ILLDAHEAGSAEN#DTADAEPPK.I
0.8401





IPI00005607
R.LQNSQCYN#WTLLLGNR.W
0.9011





IPI00005613
Q.N#SSQSADGLR.C
0.5344





IPI00005638
R.LAM*AYGLN#VSFLER.L
0.7107





IPI00005667
R.EFSAGTVYPETN#KTK.N
0.7715





IPI00005675
K.HWTNFVITENANDAIGILN#NSASFNK.M
0.5914





IPI00005683
K.ALWNLRSN#DTGLLGNVVNIQTGHWVGK.Q
0.5878





IPI00005683
M.GN#SSEFQKAVKLVINTVSFDK.D
0.7686





IPI00005700
K.KTLDEERN#SSSRSGITGTTNK.K
0.702





IPI00005704
A.LCDQEGWDTPIN#YSK.T
0.839





IPI00005704
K.GAEIEVDEN#GTLDLSMKK.N
0.5705





IPI00005750
M.TGVADN#GSVLEITPDVAEVYLVRK.N
0.8014





IPI00005791
K.ELLN#ETEEEINKALNK.K
0.7699





IPI00005792
K.QMN#MSPPPGNAGPVIM.S
0.6751





IPI00005808
M.LAQEGM*LANLVEQN#ISVRR.R
0.6502





IPI00005826
K.SLN#VSSSVNQASR.L
0.657





IPI00005858
G.FDEDM*VIQALQKTNN#RSIEAAIEFISK.M
0.9909





IPI00005858
R.REQMAAAAARPIN#ASMKPGNVQQSVNR.K
0.7193





IPI00005858
R.QPPPPYPLTAANGQSPSALQTGGSAAPSSYTN#GSIP.Q
0.5362





IPI00006011
K.N#LSCTNVLQSN#STK.K
0.9003





IPI00006011
R.M*KSDSFLQEMPN#VTN.I
0.7042





IPI00006011
R.NCQAIQQN#HSCSK.S
0.6602





IPI00006035
R.LPLAN#MSYYVSPQAVDAVHRGLGLPLPR.T
0.908





IPI00006038
R.ALSMYEEAFQN#TSDSDR.Y
0.5732





IPI00006038
K.ITNEKGECIVSDFTIGRKGYGSIYFEGDVN#LT.N
0.6621





IPI00006065
M.RPRGQPADIRQQPGM*M*PHGQLTTIN#QSQLSAQLG.L
0.5097





IPI00006079
Q.KFN#DSEGDDTEETEDYRQFRK.S
0.5259





IPI00006093
K.VVNPQEYSSN#CTEPFPN#STNLLPT.E
0.6183





IPI00006096
S.LN#GTSRGSSDLTSAR.N
0.9003





IPI00006096
K.LQTTN#TTRSVLK.D
0.8793





IPI00006097
Q.PQAVPPYASEN#QTCR.D
0.7754





IPI00006114
K.VTQN#LTLIEESLTSEFIHDIDR.E
1





IPI00006154
R.LQNNENN#ISCVER.G
1





IPI00006158
K.CPGPTSGPSPGTN#LSGCIR.M
0.7724





IPI00006165
K.NIFVN#GTTGEGLSLSV.S
0.797





IPI00006173
K.GVVVN#SSVM*VK.F
0.9573





IPI00006173
K.GHFIYKN#VSEDLPLPTFSPTLLGDSR.M
1





IPI00006173
K.TVSN#LTESSSESIQSFLQSM*ITAVGIPEVM*SR.L
0.9999





IPI00006181
R.NLAMEATYINHN#FSQQCLR.M
0.8303





IPI00006195
K.NN#YSPTAAGTERR.K
0.6855





IPI00006195
R.VESN#SSAHPWGLVGK.S
0.9732





IPI00006197
Y.PDPQSANHMN#SSLLSLYR.K
0.6374





IPI00006213
M.QINTN#KSKDASTSPPNR.E
0.683





IPI00006213
M.NDQDLPN#WSNENVDDR.L
0.859





IPI00006266
R.GRGASPRGGGPLILLDLNDENSN#QSFHSEGSLPKGTEP.S
0.6518





IPI00006278
R.SFCKDQQGDHNGEN#SSK.C
0.7131





IPI00006280
R.IVAARLN#GSLDFF.S
0.5099





IPI00006288
K.ESYLQIPSAKVRPQTN#ITLQIATDEDSGILLYK.G
0.5946





IPI00006314
R.N#TTLFIDQVEAK.W
0.6619





IPI00006374
K.SSRMETVGN#ASSSSN#PSSPGRIKGR.L
0.9833





IPI00006496
A.AEGGN#TSDTQSSSSVNIVMGPSAR.A
0.7315





IPI00006515
K.RYN#GSDPASGPSVQDKYVTALYFTFSSLTSV.G
0.7263





IPI00006543
R.EQFCPPPPQIPNAQN#M*TTTVNYQDGEK.V
0.9848





IPI00006552
K.FN#LTEDM*YAQDSIELLTTSGIQFKK.H
0.5749





IPI00006612
A.TN#ETNVNIP.Q
0.6571





IPI00006631
R.FIN#STFLEQK.E
0.5296





IPI00006662
R.CIQAN#YSLMENGK.I
0.9993





IPI00006662
R.ADGTVNQIEGEATPVN#LTEPAK.L
1





IPI00006663
R.KTFPTVN#PSTGEVICQVAEGDKEDVDK.A
0.5661





IPI00006665
K.NGDPELNVIQNYNEGIIDN#LSK.D
0.5882





IPI00006669
R.QSKSESDYSDGDN#DSIN#STSNSN#DTIN#CSSESSSR.D
0.5434





IPI00006674
R.QN#NTSLRLGVYAALGILQGFLVMLAAMAMAAGGIQAAR.V
0.8225





IPI00006675
K.M*DTELAESGSN#FSVGQR.Q
0.7018





IPI00006680
K.LSELHDNQDGLVNMESLN#STR.S
0.848





IPI00006735
L.QVEQQLAN#ITV.S
0.6736





IPI00006746
R.KLQGNM*LLN#SSMEDKM*LKENPEEK.L
0.894





IPI00006803
R.DDALKN#LSHTPVSKFVLDR.I
0.9538





IPI00006854
R.TKSQSKLDRN#TSFR.L
0.6814





IPI00007002
R.GIEAALGTRASASSFLN#MSRCCIR.A
0.5876





IPI00007032
K.TNEISVIQSGGVPTLPVSLGATSVVNN#ATVSK.M
0.5945





IPI00007063
K.EEEN#KSSSEGGDAGN#DTR.N
0.7125





IPI00007096
C.YPDNPAN#RSLVLPWSFPLEWAPQN#LTR.W
0.6644





IPI00007124
M.DGM*N#SSGVYASPTCSNM*AHHALSFR.G
0.7767





IPI00007160
R.EVTNKN#GTNVFQEESR.K
0.7667





IPI00007178
R.TGLLKQTHIAPKPAAHLAAPAN#GSAP.S
0.7895





IPI00007182
R.ARAGHTM*N#TSPGTVGSDPVILATAGYDHTVR.F
0.7311





IPI00007193
K.NN#RSDM*M*SALGLGQEEDIESPWDSESISENFPQK.Y
0.7689





IPI00007193
K.M*N#RTALHLACANGHPEVVT.L
0.6784





IPI00007199
K.ETFFN#LSK.R
0.9904





IPI00007199
K.LPYQGN#ATM*LVVLM*EK.M
1





IPI00007202
G.SPPGFN#NTER.T
0.9431





IPI00007205
K.VM*VVLTDGGIFEDPLN#LTTVI.N
0.5793





IPI00007210
K.YKSVYVGEETN#ITLNDLKPAM*DYHAKVQAEYNSIK.G
0.5686





IPI00007221
R.VVGVPYQGN#ATALFILPSEGK.M
1





IPI00007221
K.VLPSLGISNVFTSHADLSGISN#HSNIQVSEMVHK.A
1





IPI00007221
R.EDQYHYLLDRN#LSCR.V
0.9996





IPI00007240
K.EHETCLAPELYNGN#YSTTQK.T
1





IPI00007240
K.HGVIISSTVDTYEN#GSSVEYR.C
1





IPI00007248
R.RN#ASGLTNGLSSQER.P
0.5707





IPI00007249
R.LNN#ITMWLN#NSNPPV.T
0.7009





IPI00007250
K.QVLLFN#NSHLTYVSFDFHEHCR.G
0.9651





IPI00007253
L.LLSN#CSK.A
0.7067





IPI00007273
M.FFMNHQHSTAQLN#LSNMK.I
0.8387





IPI00007296
G.RVPVN#VTSTALLSVLDIFPTVVALAQASLPQGR.R
0.9365





IPI00007321
G.NN#M*STPLPAIVPAARK.A
0.844





IPI00007362
K.NGLSN#SSILLDK.C
0.7844





IPI00007367
K.GN#M*TLSPENGYWVVIM*MK.E
0.7557





IPI00007404
R.GFN#M*SIPMPGHPVN#FSSVTLEQAR.R
0.7404





IPI00007612
R.MKRGYDNPNFILSEVN#ETDDTKM.-
0.5981





IPI00007614
K.RN#ETLVFSHNAVIAMR.D
0.8212





IPI00007632
S.LERFIHGGAN#VTGFQLVDFNTPMVTK.L
0.5962





IPI00007672
S.KKEHISAEN#MSLETLR.N
0.5996





IPI00007682
R.TALVAN#TSNM*PVAAR.E
0.6446





IPI00007765
K.NAVITVPAYFN#DSQR.Q
0.9757





IPI00007775
S.FMN#VSESHFVSALTVVFINSK.S
0.6851





IPI00007775
K.QPKVGFYSSLN#QT.H
0.622





IPI00007778
K.QIN#SSISGNLWDKDQR.A
0.9991





IPI00007798
R.LLN#LSLNSEVVLDQDAIDVIIHVAR.N
0.9597





IPI00007798
K.NNFN#GSLVQASYQHEELR.R
0.9406





IPI00007818
R.NFNYHILSPCDLSN#YTDLAMSTVK.Q
0.9536





IPI00007818
M.VVLEWLAN#PSNDMYADTVTTVILEVQSNPKIR.K
0.6691





IPI00007834
T.VAPQGQDM*ASIAPDN#RSK.S
0.5314





IPI00007843
R.NPDM*EVDEN#GTLDLSMNKQR.P
0.8337





IPI00007858
C.LIPN#ETKTPGVMDHYLVM*HQLRCNGVLEGIR.I
0.6604





IPI00007927
K.YLINGVNAN#NTRVQDLFCSV.G
0.533





IPI00007941
R.YHTESLQN#M*S.K
0.7632





IPI00007979
M.AILFNNMLSGQWTMTN#TTNQYSSLM*IMM*AMAMK.L
0.5334





IPI00008052
E.EADVDM*EPN#VSVYSGLK.E
0.6963





IPI00008085
A.HNHHGEN#KTVLR.K
0.6903





IPI00008091
K.NKISIEDLLQSSM*GSTQQAQN#TTSSLMNLVM*QFR.K
0.9063





IPI00008129
R.N#M*SQLM*ETGEVSDDLASQLIYQLVAELAK.A
0.896





IPI00008129
L.FN#GSLLLQN#VSLENEGTYVCIATNALGK.A
0.5277





IPI00008135
R.DYKQTGDN#LSSMLLEN#LTDN#ESENTNLKKK.V
0.9339





IPI00008135
K.INFENAN#LSALNLK.I
0.6945





IPI00008161
R.QDAVVAVTGDGVN#DSPALKK.A
0.7642





IPI00008198
K.LLYNLRASLNKN#QSSR.H
0.5161





IPI00008226
K.LPGLAN#TTLSTPNPDTQASASPDPR.P
0.5447





IPI00008274
K.KWRVENQEN#VSNLVIEDTELK.Q
0.5781





IPI00008283
K.TLDLQSGLKDITGN#KSEM*IEK.P
0.6912





IPI00008334
Y.DLKEGLLVSPGSVIM*N#GSNMAN#TSPSVKSK.E
0.6222





IPI00008372
K.EASLADN#NTDVRLIGEKLFHGVSM*SER.C
0.9182





IPI00008372
R.LDKSNFQQPYITN#RTFML.A
0.5419





IPI00008454
M.APQN#LSTFCLLLLYLIGAVIAGR.D
0.6872





IPI00008490
K.MLM*GIN#VTPIAALLYTPVLIR.F
0.6937





IPI00008494
R.LN#PTVTYGN#DSFSAK.A
0.9995





IPI00008494
R.AN#LTVVLLR.G
0.9973





IPI00008522
G.IDTTSLHSHN#GSPLTSK.N
0.5483





IPI00008522
K.IIGNSVGALGN#LTIILAIIVFVFALVGK.Q
0.9389





IPI00008556
K.LETTVN#YTDSQRPICLPSK.G
1





IPI00008556
R.VYSGILN#QSEIK.E
1





IPI00008556
K.GINYN#SSVAK.S
0.9987





IPI00008558
R.GVNFN#VSK.V
0.9985





IPI00008558
R.IVGGTN#SSWGEWPWQVSLQVK.L
1





IPI00008558
R.IYSGILN#LSDITK.D
1





IPI00008558
K.IYPGVDFGGEELN#VTFVK.G
1





IPI00008558
K.LQAPLN#YTEFQK.P
0.9983





IPI00008569
K.EQDYLCHVYVRN#DSLAGVVIADNEYPS.R
0.5379





IPI00008588
K.TN#DTYMKFSWLTVPEESLDKEHR.C
0.5907





IPI00008632
T.M*NPLIYN#ITR.V
0.6089





IPI00008787
R.VFPQVN#VTK.M
0.9774





IPI00008822
M.ATYSATCAN#NSPAQGINMANSIANLRLK.A
0.8428





IPI00008829
R.AYYGNINFFGGPSN#TSV.K
0.5929





IPI00008868
R.DVMSDETNNEETESPSQEFVN#ITK.Y
0.813





IPI00008884
D.DDLIISQDTDIIQDMVAGEN#TSEAGSEDEGEVSLPEQPK.V
0.9406





IPI00008887
K.MDIEN#LTISNAQ.M
0.5802





IPI00008905
M.ISN#MSEESANM*IASALAQIPQKVLWR.F
0.914





IPI00008909
R.ILSN#M*TFLFVSLSYTAESAIVTAFITFI.P
0.7843





IPI00008913
R.NRHDLLN#VSQGTVFIFWGPSSYMR.R
0.7151





IPI00008918
A.VSKQSSSTN#YTNELK.A
0.8421





IPI00008918
R.SNTEN#LSQHFR.K
0.6229





IPI00008942
R.TCYYPTTVCLPGCLN#QSCGSS.C
0.8511





IPI00008982
T.KSRVGMGGMEAKVKAALWALQGGTSVVIAN#GTHPK.V
0.7814





IPI00008982
R.NLN#GTLHELLRM*NIVPIVNTNDAVV.P
0.6147





IPI00008993
K.SVNKMQEATPSAQATN#ETQM*CYASLDHSVK.G
0.6581





IPI00009009
M.ENILSGNPLLN#LTGPSQPQANFK.V
0.6902





IPI00009030
R.VQPFN#VTQGK.Y
0.8397





IPI00009030
K.IAVQFGPGFSWIAN#FTK.A
1





IPI00009030
K.VASVININPN#TTHSTGSCR.S
0.9999





IPI00009030
K.WQMN#FTVR.Y
0.9569





IPI00009054
R.KLYKCPACGETLQDSTGN#FSSPEYPNGYSAHM.H
0.728





IPI00009101
R.AETQGAN#HTPVISAHQTR.S
0.8619





IPI00009135
K.ANQQLN#FTEAK.E
0.9998





IPI00009137
R.TPQVIGVMQSQN#SSAGNR.G
0.6672





IPI00009143
K.YMISTSETIIDIN#GTVMN#YSGWSHR.D
0.5276





IPI00009149
K.RAM*N#KSFM*ESGGTVLSTN#WSDVGKRK.V
0.9192





IPI00009243
K.FCVVLLHWEFIYVITAFN#LSYPITPWR.F
0.9082





IPI00009268
K.DM*N#LTLEPEIM*PAATDNRYIR.A
0.7641





IPI00009291
R.GLN#SSFETSPKK.V
0.7305





IPI00009329
R.IPRADELN#QTGQILVEQMGK.E
0.7349





IPI00009477
K.HYLVSN#ISHDTVLQCH.F
0.9946





IPI00009477
R.GN#ETLHYETFGK.A
0.9998





IPI00009477
K.AAPAPQEATATFN#STADR.E
0.9997





IPI00009499
R.ESIASYLSLTSEDN#TSFDRKK.K
0.8712





IPI00009504
R.KGIIDVNLYN#ETVETLMAG.E
0.5421





IPI00009521
R.VDN#FTQNPGM*FR.I
0.9997





IPI00009604
R.SSN#SSVSGTKKEDSTAKIH.A
0.7481





IPI00009612
R.NFDN#SSQN#TTASVSSKGPM*ILLQAT.K
0.7958





IPI00009618
R.LM*LPDDTTN#HSN#SSK.E
0.7359





IPI00009631
R.N#SSLGDAINKYDVVIRLNNAPVAG.Y
0.6899





IPI00009646
R.RLRELAGN#SSTPPPVSPGRGNPM*HRLLNP.F
0.7324





IPI00009655
C.FPTLSDFLTEIN#STVDK.D
0.8633





IPI00009703
M.SQHYQSGPVPGTAIN#GTLPLS.H
0.8971





IPI00009704
R.VVSN#SSVLASQSVGITNVRT.V
0.7275





IPI00009791
K.KGDGLQLPAADGAAASNAADSAN#ASLVNGK.M
0.8429





IPI00009791
K.QN#SSPPSSLNKN#NSAIDSGIN#LTTDTSK.S
0.6347





IPI00009793
R.KN#QSVNVFLGHTAIDEMLK.L
0.9367





IPI00009793
K.GFLALYQTVAVN#YSQPISEASR.G
1





IPI00009793
R.QDGEEVLQCM*PVCGRPVTPIAQN#QTTLGSSR.A
0.9998





IPI00009793
N.VLPVCLPDN#ETLYR.S
0.827





IPI00009802
K.N#SSTAEIN#ETTTSSTDFLARAYGFEMAKE.F
0.9241





IPI00009803
K.M*N#LTFHVINTGNSMAPN#VSVEIM*VPNSFSPQTDK.L
0.8668





IPI00009803
K.TLMLN#VSLFNAGDDAYETTLHVK.L
0.6288





IPI00009804
K.EHSEMSNN#VSDPKGPPAKIAR.L
0.687





IPI00009804
R.NGKPEN#NTMNIN#ASIYDEIQQEMK.R
0.6373





IPI00009822
K.GLFKGGDMSKN#VSQSQMAK.L
0.5094





IPI00009841
M.GVYGQESGGFSGPGEN#RSMSGPDNRGR.G
0.6221





IPI00009861
-.MDPN#CSCAAGVSCTCASSCKCKECK.C
0.644





IPI00009865
K.TIDDLKNQILN#LTTDNANILLQIDNAR.L
0.9999





IPI00009896
M.ALVLSN#FSTLTLLLGQR.F
0.9324





IPI00009906
I.VLNN#LSVNAEN.Q
1





IPI00009910
K.HLDLSSNLLKTIN#KSALETK.T
0.79





IPI00009910
K.KQN#DSVIAECSNRR.L
0.6285





IPI00009913
M.FSLITWNIDGLDLNN#LSER.A
0.5047





IPI00009920
K.VLN#FTTK.A
0.9934





IPI00009920
R.TRLSSN#STK.K
0.9678





IPI00009961
K.EGEHDLVQGSGQQPQAGLSQAN#FTLGPVSR.S
0.9394





IPI00009992
K.IGHPHGLQVTYLKDN#STR.N
0.6302





IPI00009995
K.GVARVVN#ITSPGHDASSR.S
0.6514





IPI00009997
R.VAQPGINYALGTN#VSYPNNLLR.N
0.9618





IPI00010037
K.HTGPGILSM*ANAGPNAN#GSQFFM*CPA.K
0.7553





IPI00010065
R.NPFHHSLPFSIPVHFTN#GTYHVVGFDGSSTVDEFLQR.L
0.623





IPI00010088
M.PIASEFAPDVVLVSSGFDAVEGHPTPLGGYN#LSAR.C
0.8827





IPI00010134
N.#CTCVGIAASKSGN#SSGIVGRCQK.D
0.6131





IPI00010141
R.IIKEALPDGVN#ISK.E
0.5035





IPI00010193
G.N#MSGN#FTYIIDK.L
0.9081





IPI00010196
L.LSN#KTNAVEENK.A
0.5128





IPI00010196
R.SPYNSHM*GNN#ASRPHSANGEVYGLLGSVLTIKK.E
0.8051





IPI00010213
M.EVCNN#ETISVSSYK.I
0.8865





IPI00010221
R.N#CTTLQGLAPGTAYLVTVTAAFRSGR.E
0.6559





IPI00010250
K.GTN#SSASSNFRCR.S
0.8811





IPI00010272
R.NSKN#CTEPALHEFPNDIFTNEDRR.Q
0.9345





IPI00010281
K.TN#GTLLRNGGLPGGPNKIPNGDICCIPNSNLDK.A
0.7153





IPI00010286
F.NEHMTN#STMSPGTVGQSLK.S
0.8811





IPI00010286
K.QLNVQMN#MSNVMGN#TTWTTSGLK.S
0.7521





IPI00010381
R.NKEVN#ISAVVWPS.Q
0.5495





IPI00010421
K.KQIN#DSANLR.E
0.5543





IPI00010433
R.SM*NPN#VSMVSSASSSPSSSR.T
0.6833





IPI00010448
K.ATMGLLQNKENN#NTKDSPSR.Q
0.6608





IPI00010463
K.LLQTTN#NSPM*NSKP.Q
0.5738





IPI00010487
K.RYN#QSMVTAELQR.L
0.5103





IPI00010540
R.LDN#ITQVM*SLHTQYLESFLR.S
0.6334





IPI00010540
K.FRM*VYN#LTYNTM*ATHEDVDTTMLR.R
0.9082





IPI00010625
M.NN#NSGAPATAPDSAGQPPALGPVFELVSK.E
0.5206





IPI00010676
R.GPM*NQCLVATGTHEPKN#QSYMVR.G
0.9334





IPI00010700
K.ETPPNGN#LSPAPRLR.R
0.6319





IPI00010728
R.GVSGDRDENSFSLN#SSISSSAR.R
0.6981





IPI00010790
M.IEN#GSLSFLPTLR.E
0.9074





IPI00010807
Y.N#RTDLTTAAPSPPR.R
0.9763





IPI00010862
K.GTGSWTQLYLITDYHEN#GSLYDYLK.S
0.5774





IPI00010903
R.LINLYIIQN#NSFS.Q
0.5246





IPI00011031
M.GINECQYQFRFGRWN#CSALGEK.T
0.7317





IPI00011041
-.MDGDN#QSENSQFLLLGISESPEQQR.I
0.5781





IPI00011092
M.TSGN#ISVSWPATK.E
0.7217





IPI00011092
M.ISSSSEMNEEFLKEN#NSVEYKKSK.A
0.5895





IPI00011155
R.SLKEAFSN#FSSSTLTEVQAISTHGGSVGDK.I
0.6585





IPI00011155
R.FVACQM*ELLHSN#GSQR.T
0.9947





IPI00011168
R.GISARVWGHFPKWLN#GSLLRIG.P
0.6584





IPI00011177
Y.LAN#LTQSQIALNEKR.V
0.7331





IPI00011180
K.AYTDFQNN#HSSPK.P
0.7463





IPI00011218
K.VLTLNLDQVDFQHAGN#YSCVASNVQGK.H
0.9379





IPI00011218
R.HTN#YSFSPWHGFTIHR.A
0.9994





IPI00011218
K.VM*VEAYPGLQGFN#WTYLGPFSDHQPEPK.L
0.9985





IPI00011219
R.HSSTDSNKASSGDISPYDN#NSPVLSER.S
0.9822





IPI00011229
K.GSLSYLN#VTR.K
0.9947





IPI00011252
R.GGSSGWSGGLAQN#R.S
0.9998





IPI00011255
K.VASHLEVNCDKRN#LTALPPDLPK.D
0.9977





IPI00011264
R.SPYEM*FGDEEVMCLNGN#WTEPPQCK.D
0.9927





IPI00011285
K.RDFFLAN#ASRARSEQFINLR.E
0.5852





IPI00011374
R.LECN#GTISAHCNLHLPGSSDSPASSSRVAGITGIK.T
0.892





IPI00011528
K.SAMPIEVMMN#ETAQQNMENHPVIR.T
0.9028





IPI00011538
R.KKN#LTLALEALVQLR.G
0.8122





IPI00011578
C.N#ATNAIGSASVVTVLR.V
0.6967





IPI00011601
K.AN#MTLTSGIMFIVSGLCAI.A
0.981





IPI00011609
K.GASSAYLENSKGAPN#NSCSEIKM*NK.K
0.8334





IPI00011651
R.SDFSQTM*LFQAN#TTR.I
0.9999





IPI00011651
K.VEFHWGHSN#GSAGSEHSINGR.R
0.9516





IPI00011651
S.GVTHAAEERN#QTEPSPTPSSPN#R.T
0.7968





IPI00011651
K.NRN#SSVVPSERARVGL.A
0.5831





IPI00011665
K.DFLN#VTTEANIL.P
0.5409





IPI00011730
K.VNLNSVSKSLTGLSDSVSQYSDAFLAAN#TSLDER.E
0.6698





IPI00011756
R.SAN#LTDQPSW.N
0.7055





IPI00011757
R.KLN#PSQN#ATGTSRS.E
0.51





IPI00011798
K.RN#ASSSSHSSTEGLQELK.R
0.526





IPI00011836
R.YVKQPLPDEFGSSPLEPGACN#GS.R
0.748





IPI00011879
K.VN#GSHEANMLSQVHR.-
0.6038





IPI00011989
Q.VGIYN#GTHVIPNDR.K
0.9222





IPI00012009
M.N#LSWDCQEN#TTFSKCFLTDK.K
0.5996





IPI00012033
R.RPLVLQLVN#ATTEYAEFLHCK.G
0.5378





IPI00012058
E.EYKNYLDAAN#MSMRVR.R
0.6311





IPI00012113
R.TLPLILILLALLSPGAADFN#ISSLSGLLSPALT.E
0.5196





IPI00012136
R.RRGRPRGNN#LSTISDTSPMKR.S
0.6504





IPI00012136
M.GN#STDPGPM*LAIPAMATNPQNAASR.R
0.8807





IPI00012165
R.VVLLDPKPVAN#VTCVNK.H
0.8881





IPI00012221
E.QTYHMALNAATFPKN#ATWIGPLW.-
0.797





IPI00012269
K.FNPGAESVVLSN#STLK.F
1





IPI00012269
K.LQN#LTLPTN#ASIK.F
0.9972





IPI00012318
K.CRLDVNTELN#SSIEDLLEASMPSSD.T
0.9028





IPI00012363
K.SLM*DQLQGVVSN#FSTAIPDFHAVLAGPGGPGNGLR.S
0.8632





IPI00012390
M.KKVHVNSVNPN#YTGGEPK.R
0.9153





IPI00012391
R.QM*SQQN#LTK.Q
0.7042





IPI00012471
K.MSHPPNIPKEQTPAGTSN#TTSVSV.K
0.5742





IPI00012488
K.VTGSGGPFKSDPHWESMLN#ATTR.R
0.8033





IPI00012503
R.TN#STFVQALVEHVKEECDR.L
0.9923





IPI00012503
R.NLEKN#STKQEILAALEK.G
0.6514





IPI00012508
R.YLINSYDFVN#DTLSLK.H
0.678





IPI00012519
V.YYM*VVCLVAFTIVMVLN#ITR.L
0.917





IPI00012545
K.DGSN#KSGAEEQGPIDGPSKSGAEEQTSK.D
0.6523





IPI00012574
A.MVN#TTQQQGLSN#ASTEGPVADAFN#NSSISIK.E
0.9076





IPI00012578
R.VQN#TSLEAIVQN#ASSDNQGIQLSAVQAAR.K
0.5783





IPI00012585
K.LDSFGPIN#PTLN#TTYSFLTTFFK.E
0.9903





IPI00012728
K.RKEAELRSGIIRN#NSLWDR.L
0.5083





IPI00012730
G.AASYFLILDSTNTVPDSAGSGN#VTR.C
0.562





IPI00012773
K.AGVVN#GTGAP.G
0.7917





IPI00012773
K.VAPVINN#GSPTILGKR.S
0.5426





IPI00012792
R.EVYPWYN#LTVEAK.E
0.9992





IPI00012792
R.LDREN#ISEYHLTAVIVDK.D
1





IPI00012792
R.AQVIIN#ITDVDEPPIFQQPFYHFQLK.E
1





IPI00012828
K.DGSTTAGN#SSQVSDGAAAILLARR.S
0.7344





IPI00012843
L.SSLSPVN#SSNHGPVSTGSLTN#R.S
0.8791





IPI00012876
R.N#RSFQPGLDNIIFVVETGPL.P
0.718





IPI00012885
M.ADLIDGYCRLVN#GTSQSFIIRPQK.E
0.56





IPI00012887
K.YSVAN#DTGFVDIPK.Q
0.5022





IPI00012891
R.CEGSQPWN#LTPR.Q
0.9283





IPI00012990
I.IAAGVAHAITAACTHGN#LSDCGCDKEK.Q
0.6049





IPI00013010
D.LGNVPN#GSALTDGSQLPSR.D
0.5082





IPI00013049
K.VSRIPQGTFSNLEN#LTLLDLQNNK.L
0.879





IPI00013096
N.#ISRLDPQTN#SSQIKDEFQTLNIVTPR.V
0.5466





IPI00013174
M.SQGAVANAN#STPPPYERTR.L
0.7707





IPI00013177
K.RVYSLMEN#NSYPRFLESEFYQDLCK.K
0.8289





IPI00013179
R.WFSAGLASN#SSWLR.E
1





IPI00013179
K.SVVAPATDGGLN#LTSTFLR.K
1





IPI00013226
R.RGASVN#RTTRTN#STPLR.A
0.7364





IPI00013234
K.LKLFLN#ETQTQEITEDIPVKTLNM*K.T
0.6948





IPI00013299
K.SAWCEAKN#ITQIVGHSGCEAK.S
0.838





IPI00013303
K.ISN#ISSDVTVNEGSN#VTLVCMANGR.P
0.5254





IPI00013409
R.YTVSN#LSMQTHAARFK.T
0.5053





IPI00013414
K.LQDIFYPN#TSNCAK.G
0.716





IPI00013436
K.LQINN#LTMNLIELEN.-
0.725





IPI00013437
K.AFSN#SSTLANHKITHTEEKPYKCK.E
0.5749





IPI00013441
R.THKM*N#VSPVPPLR.R
0.6668





IPI00013452
N.#ISSN#SSASILESK.S
0.5018





IPI00013492
R.SGTNHYSTSSCTPPAN#GTDSIMANR.G
0.5103





IPI00013624
K.EYPN#LSTSLDDAFLLR.F
0.9721





IPI00013712
R.LLQMPSVVN#YSGLRK.R
0.5647





IPI00013743
R.RARHDSPDLAPN#VTYSLPRTK.S
0.7072





IPI00013744
V.AIVYN#ITLDADGFSSR.V
0.7322





IPI00013877
R.MGM*GNN#YSGGYGTPDGLGGYGRGGGGSGGYYGQGGMSGGGWR.G
0.9609





IPI00013880
W.TPVN#ISDNGDHYEQR.F
0.5364





IPI00013892
K.GEGLN#KTVIGDYLGERDEFNIK.V
0.7954





IPI00013928
M.N#NSESHFVPNSLIGMGVLSCVFNSLAGK.I
0.6737





IPI00013967
R.LN#M*TTEQFTGDHTQHFLDGGE.M
0.527





IPI00013970
T.DCGHTWNSPN#CTDPKLLN#GSVLGN#HTK.Y
0.5064





IPI00013972
M.SEEVTGQFSVHPETPKPSISSN#NSNPVEDK.D
0.7948





IPI00014011
K.DLYRSN#ISPLTSEKDLDDFR.R
0.9479





IPI00014053
K.GLSNHFQVN#HTVALSTIGESNYHFG.V
0.8905





IPI00014072
K.RRPLNN#NSEIALS.L
0.7144





IPI00014147
K.VLGSSTSATN#STSVSSR.K
0.971





IPI00014186
K.ASASPGEN#DSGTGGEEPQRDK.R
0.601





IPI00014194
M.CVKN#STGVEIK.R
0.9649





IPI00014202
V.N#LTGLDLSQNN#LSSVTNINVKK.M
0.9364





IPI00014211
G.KSVLVN#GTKER.D
0.6008





IPI00014312
R.DM*SISN#TTM*DEFR.Q
0.8411





IPI00014319
G.HKQISSSSTGCLSSPN#ATVQSPK.H
0.6699





IPI00014335
R.DATGNMN#DTIISGM*NCN#GSAACGLGYD.F
0.9396





IPI00014456
R.HIKFYDN#NTGK.L
0.8422





IPI00014502
E.PCYVSASEIKFDSQEGSVDQN#HSWLGRKRR.N
0.6144





IPI00014544
T.NN#ISLMATLK.A
0.6331





IPI00014553
M.QSQAGGN#NTGSTPLR.K
0.75





IPI00014802
A.VSQN#WTFHGPGASGQAAANWLAGFGR.G
0.847





IPI00014829
K.N#GTIFTISPVLLLDTISTTR.F
0.8234





IPI00014845
M.ITVVQTYSTLSN#STIEGIDIMAIKFR.N
0.8202





IPI00014898
M.NEILTDPSDDTKGFFDPNTEEN#LTYLQLM*ER.C
0.6611





IPI00015102
R.TVNSLN#VSAISIPEHDEADEISDENR.E
0.7966





IPI00015102
N.#LSEN#YTLSISNARISDEK.R
0.9391





IPI00015102
K.NAIKEGDN#ITLK.C
0.8636





IPI00015115
R.VEIISN#NSIQAVFN#PTGVYAPSGYSYR.C
0.5105





IPI00015283
K.N#CTNN#CTFVYAAEQPPEAPGK.I
0.7401





IPI00015286
K.WRSN#TSLLQQNLR.Q
0.5223





IPI00015309
-.MDLSN#NTM*SLSVRTPGLSR.R
0.5004





IPI00015345
P.GAYN#NTALFEESGLIR.I
0.9034





IPI00015467
K.N#QSASPPPKDRSSSPATEQSWTQ.N
0.6481





IPI00015488
R.DLDGFLAQASIVLN#ETATSLDNVLRTMLRR.F
0.9121





IPI00015508
V.QDSVN#ISGHTNTNTLK.V
0.748





IPI00015525
F.GNFQGLMEAN#VSLDLGK.L
0.9741





IPI00015525
K.FN#TTYINIGSSYFPEHGYFR.A
1





IPI00015525
R.SFN#QSLHSLTQAIR.N
0.7485





IPI00015553
V.YN#PSGLN#LSIK.G
0.833





IPI00015573
R.QLCGLLLGGGGN#RSHSTPYCGLR.R
0.7096





IPI00015688
C.CTSEMEENLAN#R.S
0.8297





IPI00015745
K.TGTTLN#TSIIFGPN#LS.-
0.6054





IPI00015749
K.NFAQNRGAGN#TSSLNPLAVGFVQTPPVISSAHIQDER.V
0.9563





IPI00015782
R.SLSTPNALSFGSPTSSDDM*TLTSPSM*DN#SSAE.L
0.8927





IPI00015830
K.FCHSQLSN#NSVSFFLYNLDHSHANYYFCN.L
0.5405





IPI00015902
D.AYYVYRLQVSSIN#VSVNAVQTVVR.Q
0.5157





IPI00015902
R.SILHIPSAELEDSGTYTCN#VT.E
0.5395





IPI00015911
A.LLN#NSHYYHM*AHGTDFASR.G
0.8476





IPI00015952
R.DDNSAAN#NSANEKER.H
0.5125





IPI00015963
K.LMISSYSGSVDIVN#TTDGCH.E
0.6129





IPI00015980
R.LM*QGDQILM*VNGEDVRN#ATQEAVAALLK.C
0.5682





IPI00015990
K.GQNLNN#YSFSTNGFSGSGGSGSHGS.S
0.695





IPI00015994
K.QQN#HTLDYNLAPGPLGR.G
0.7563





IPI00016006
R.EAPGM*ALAMLMGSLN#VTP.L
0.7394





IPI00016053
R.RLSLN#QSR.G
0.9005





IPI00016095
K.ELVNAGCN#LSTLN#ITLLSWSKK.R
0.9813





IPI00016339
K.LPKNEPQN#ATGAPGR.N
0.5492





IPI00016371
K.MEDGLLTCHGPGPDN#CTKCSHFK.D
0.6301





IPI00016422
R.EGDNRERALN#TTQPGSLQLTVGNLK.P
0.7916





IPI00016454
R.VMVHGRN#HTPFLGHHS.F
0.5467





IPI00016475
R.LQQLAEPQSDLEELKHEN#K.S
0.515





IPI00016480
K.ENLPEN#VTASESDAEVER.S
0.5715





IPI00016488
D.YNVQTSN#WTR.T
0.6482





IPI00016542
R.LKN#ISENADFFASLQLSESAARLREM.I
0.9726





IPI00016553
K.ASLCLPTTSAPASAPSNGN#CS.S
0.9822





IPI00016589
K.EN#STASEVLDSLSQSVHVKPENLR.L
0.5232





IPI00016590
R.SIQKLGELNIGM*DGLGNEVSALNQQCN#GSK.G
0.5157





IPI00016633
R.HVLATILAQLSDMDLIN#VSK.V
0.7999





IPI00016637
R.FIGLTNSFGFGGTN#A.T
0.5093





IPI00016645
R.PPSAPQNLIFNIN#QTTVSLEWSPPADNGGR.N
0.5488





IPI00016645
K.DN#FTAAGYNSLES.V
0.5271





IPI00016665
K.HQVEALKNMQHQN#QSLSM*LDEILEDVRK.A
0.6939





IPI00016677
K.SEM*AQIQQNAVQN#HTATMLEIGTSLLSQTAEQTRK.L
0.5277





IPI00016677
R.DCADVYQAGFN#KSGIYTIYINNM*PEPK.K
0.8654





IPI00016701
K.RGN#TTLESTD.T
0.5684





IPI00016709
K.RLVSMNM*PLNSDGTVMFN#ATLFALVRTALRIK.T
0.9595





IPI00016709
K.CAPESEPSN#STEGETP.C
0.5736





IPI00016709
K.LM*GSAGN#ATISTVSSTQRKR.Q
0.55





IPI00016780
-.MNQN#TTEPVAATETLAEVPEHVLR.G
0.5736





IPI00016783
R.SQSSSQSPASHRN#PTGAHSSSGHQSQSPN#TSPPPKRHK.K
0.5254





IPI00016890
K.EPHLN#YSPTCLEPPVLSIHPGAID.-
0.9034





IPI00016906
R.GATAAVLAPDSSN#ASSEPSS.-
0.8257





IPI00016906
K.VKM*VVSREEVELAYQEAMFNMATLN#RTAAGLMHT.F
0.7829





IPI00016949
R.M*FTNPDN#GSPAM*THRN.L
0.6304





IPI00017025
M.ANAGPNTN#GSQCFICTAK.T
0.6715





IPI00017070
R.DPNIEALNGN#CSDTEIHEK.E
0.571





IPI00017094
M.VISPSGFTASPYEGEN#SSNIIPQQM*AAHMLR.S
0.606





IPI00017094
M.N#STDIQWSAILSWGYADNILRLK.S
0.6979





IPI00017163
R.STIISN#TTNPIWHR.E
0.8535





IPI00017174
R.PQSN#SSAVTGTSGSIM*ENGVSSSNTADK.S
0.5115





IPI00017203
R.LIGEPDLVVSVIPN#NSNENIPR.V
0.6294





IPI00017234
R.RNAEWHVHM*M*EYYAAENMNN#WSHGM*NEAER.F
0.5073





IPI00017373
K.M*FILSDGEGKN#GTIELMEP.L
0.9304





IPI00017381
R.VLELN#ASDERGIQVVREK.V
0.9425





IPI00017390
R.WEYCN#LTR.C
0.9997





IPI00017405
K.VLLN#SSVPPAGAEELSSAMANPPPKR.P
0.7221





IPI00017480
R.LLLTAAHLLFVAPHN#DSATGEPEASSGSGPPSGGALGPR.A
0.9963





IPI00017522
M.HAVVFGN#VTAIIQR.M
0.7185





IPI00017562
K.GDYN#DSVQVVDCGLSLN#DTAFEK.M
0.5841





IPI00017601
K.LEFALLFLVFDEN#ESWYLDDNIK.T
0.9879





IPI00017601
K.AGLQAFFQVQECN#K.S
1





IPI00017601
K.EN#LTAPGSDSAVFFEQGTTR.I
1





IPI00017601
K.EHEGAIYPDN#TTDFQR.A
1





IPI00017601
K.ELHHLQEQN#VSNAFLDK.G
1





IPI00017601
R.QKDVDKEFYLFPTVFDEN#ESLLLEDNIR.M
0.9993





IPI00017603
R.NLFLTNLDNLHEN#NTHNQEK.K
0.829





IPI00017617
R.LM*EEIMSEKEN#KTIVFVETK.R
0.6564





IPI00017640
R.HLTLIDLSN#NSISMLTN#YTFSN#M*S.H
0.5467





IPI00017640
R.HLTLIDLSN#NSISM*LT.N
0.7484





IPI00017648
K.FGLYHVDFN#NTNRPR.T
0.9931





IPI00017696
K.TM*QEN#STPRED.-
1





IPI00017696
K.NCGVN#CSGDVFTALIGEIASPNYPK.P
0.9996





IPI00017696
H.CAGN#GSWVNEVLGPELPK.C
0.7099





IPI00017734
K.GLGAQTGVLRM*KGVN#LS.C
0.6495





IPI00017818
A.EESPFVGNPGN#ITGAR.G
0.9891





IPI00017841
K.VQN#M*SQSIEVLDR.R
0.9999





IPI00017919
R.ESNAPSVPTVSLLPGAPGGN#ASS.R
0.6685





IPI00017940
M.EEVRKVN#ESIK.Y
0.55





IPI00017964
M.SN#ITVTYR.D
0.9826





IPI00018071
R.EALN#ISSSISESGGLNWKM*.T
0.7432





IPI00018073
R.DEDTLQDPAPLETPM*N#ASSSHS.C
0.7424





IPI00018098
K.N#ESKEKSNK.R
0.7036





IPI00018198
M.AAANPWDPASAPNGAGLVLGHFIASGMVNQEMLN#MSKK.T
0.5016





IPI00018214
K.N#HTHQQDIDDLKRQNALLEQQVR.A
0.5199





IPI00018251
M.MRGQGLN#M*TPSMVAPSGM*PATMSNPR.I
0.8896





IPI00018287
K.ALWN#SSVPVCEQIFCPNPPAILNGRH.T
0.5438





IPI00018305
R.AYLLPAPPAPGN#ASESEEDR.S
1





IPI00018305
K.VDYESQSTDTQN#FSSESK.R
1





IPI00018305
R.GLCVN#ASAVSR.L
1





IPI00018313
R.FLIEDINDNAPLFPATVIN#ISIPENSAINSK.Y
0.6066





IPI00018313
R.YIVNPVN#DTVVLSENIPLNTKI.A
0.6323





IPI00018672
R.VSGAVATAVLWVLAALLAMPVMVLRTTGDLEN#TTK.V
0.8758





IPI00018678
F.VQN#CTSLNSLNEVIPTDLQSK.F
0.7695





IPI00018810
K.VGSFGN#GTVLR.S
0.7229





IPI00018860
K.TFLHYDCGN#KTVTPVSPLGKK.L
0.9597





IPI00018953
R.IPN#NTQWVTWSPVGHK.L
0.6221





IPI00018953
K.KLDFIILN#ETK.F
0.9992





IPI00018956
K.NSDFYMGAGGPLEHVM*ETLDN#ESFYSK.A
0.824





IPI00019006
M.KYLN#LSSTR.I
0.7613





IPI00019020
L.FQN#ITLEDAGSYTLR.T
0.5141





IPI00019056
R.DN#LSETASTM*ALAGASITGSLSGSAM*VNCFNR.L
0.9179





IPI00019148
K.TMN#NSAEN#HTAN#SSMAYPSLVAM*ASQR.Q
0.7877





IPI00019157
R.YVHDGSETLTDSFVLMAN#ASEMDR.Q
0.7313





IPI00019157
R.GVN#ASAVVN#VTVRALLHVWAGGPWPQGATLR.L
0.6806





IPI00019223
K.HSRIVELLN#ETEKYK.L
0.64





IPI00019226
A.YLM*EPLCISSN#ESSEGCCPPSGTR.Q
0.5861





IPI00019226
M.FQNAVMYN#SSDHDVYHMAVEM*QR.D
0.7918





IPI00019243
P.RMSVLRSAETM*QSALAAMQQFYGIN#M*TGK.V
0.8088





IPI00019308
A.IM*NN#MSLIIHR.S
0.7765





IPI00019311
R.CFPWTN#ITPPALPGITN#DTTIQQGISGLIDSLNAR.D
0.9139





IPI00019359
K.N#YSPYYNTIDDLKDQIVDLTVGNN#K.T
0.6174





IPI00019391
F.HGLYEEKN#LSPGFNFR.F
0.6242





IPI00019399
R.VYLQGLIDYYLFGN#SSTVLEDSK.S
0.9998





IPI00019449
R.CKNQNTFLLTTFANVVNVCGNPN#M*TCPSN#K.T
0.6502





IPI00019450
T.PADVFIVFTDN#ETFAGGVHPAIALR.E
0.6459





IPI00019450
R.VLGSILN#ASTVAAAMCM*VVTR.T
0.5794





IPI00019464
K.DRN#ASNDGFEM*CSLSDFSANEQK.S
0.5948





IPI00019491
K.QDYNMDLELDEYYN#KTLATEN#N.T
0.7281





IPI00019537
R.SSINSVDGESPN#GSSDR.G
0.576





IPI00019568
R.SEGSSVN#LSPPLEQCVPDR.G
0.8766





IPI00019568
R.YPHKPEIN#STTHPGADLQENFCR.N
1





IPI00019568
K.N#FTENDLLVR.I
0.9816





IPI00019568
R.GHVN#ITR.S
0.7855





IPI00019571
K.NLFLN#HSEN#ATAK.D
1





IPI00019571
K.VVLHPN#YSQVDIGLIK.L
1





IPI00019571
K.MVSHHN#LTTGATLINEQWLLTTAK.N
1





IPI00019580
R.GNVAVTVSGHTCQHWSAQTPHTHN#R.T
0.9931





IPI00019581
R.N#HSCEPCQTLAVR.S
0.9997





IPI00019581
R.N#VTAEQAR.N
0.9524





IPI00019591
R.SPYYN#VSDEISFHCYDGYTLR.G
1





IPI00019591
K.IVLDPSGSMNIYLVLDGSDSIGASN#FTGAK.K
1





IPI00019591
K.ALQAVYSM*M*SWPDDVPPEGWN#R.T
0.9768





IPI00019591
R.GSAN#RTCQVNGR.W
0.5636





IPI00019600
K.INMNGIN#NSSGMVDAR.S
0.5128





IPI00019729
S.RGCN#VSR.K
0.6694





IPI00019772
R.HRAGMQN#LTEFIGSEPSKKRKR.R
0.57





IPI00019943
F.TTCCTLSEEFACVDNLADLVFGELCGVNEN#R.T
0.7473





IPI00019943
R.DIENFN#STQK.F
1





IPI00019943
R.YAEDKFN#ETTEK.S
1





IPI00019943
K.HN#FSHCCSK.V
0.9818





IPI00019981
K.QNSDHSN#GSFNLKA.L
0.9833





IPI00019983
R.TEAPEGTESEMETPSAINGN#PSWHLAD.S
0.6169





IPI00019989
R.ALQWNAGSGGLPEN#ETTFARIL.Q
0.6498





IPI00020003
R.RN#NSIRRN#NSSLMVPK.V
0.8358





IPI00020036
K.LRWDPADYEN#VTSIR.I
0.9655





IPI00020078
R.QFN#QTVQSSGN#MTDK.S
0.5929





IPI00020091
V.PITN#ATLDR.I
0.9855





IPI00020091
R.QNQCFYN#SSYLNVQR.E
1





IPI00020091
K.SVQEIQATFFYFTPN#K.T
1





IPI00020091
R.EN#GTVSR.Y
0.9899





IPI00020091
R.NEEYN#K.S
0.9747





IPI00020094
R.N#STELSEM*FPVLPGSH.L
0.9587





IPI00020122
-.M*LVNGENFGVSLNIFPSVAIN#KSSGAPRR.V
0.547





IPI00020124
K.DN#KSPLHLVQMPPVIVET.A
0.8207





IPI00020134
R.QN#SSPHLPK.L
0.9677





IPI00020354
R.N#TSPDTN#YTLYYWHR.S
0.5808





IPI00020366
A.FNCPPN#STM*NR.G
0.8296





IPI00020368
R.QPGKAPN#FSVN#WTVGDSAIEVIN#ATTGK.D
0.8377





IPI00020396
K.TGFTQLGTSCITN#HTCSNADETFCEMVK.S
0.5834





IPI00020407
K.VDNLVVN#GTGTN#STN#STTAVPSLVALEK.I
0.5666





IPI00020416
R.KQEEFDVANN#GSSQANK.L
0.5453





IPI00020426
K.SPTSPTQNLFPASKTSPVNLPN#KSSI.P
0.7398





IPI00020501
K.EIEN#LTQQYEEK.A
0.8717





IPI00020546
R.MIEQYHN#HSDHYCLNLDSGM*VIDSYR.M
0.5458





IPI00020557
R.INNGGCQDLCLLTHQGHVN#CSCR.G
0.9991





IPI00020557
R.FN#STEYQVVTR.V
0.9997





IPI00020557
R.M*HLN#GSNVQVLHR.T
0.997





IPI00020557
R.ELQGN#CSRLGCQHHCVPTLDGPTCY.C
0.8785





IPI00020557
K.DN#ATDSVPLRTGIGVQLKDIKVFNRDR.Q
0.8689





IPI00020557
K.SDALVPVSGTSLAVGIDFHAEN#DTIYWVDMGLSTISRAK.R
0.6213





IPI00020586
T.ELQLAAVETTANSLM*WILYN#LS.R
0.6761





IPI00020598
R.ILKVAEFFN#YSKNR.I
0.7997





IPI00020692
R.NSN#VSQASMSSR.M
0.54





IPI00020772
T.GN#YTACQKDLCCHLTYKM*SEKR.T
0.792





IPI00020873
K.WSPTGPATSNPN#SSIMLASASFDSTVR.L
0.5122





IPI00020903
R.RRN#VSGNNGPFGQDKNIAM*TGQITSTKPKR.T
0.5652





IPI00020918
K.AAHN#NSENIPLHK.S
0.8707





IPI00020966
Y.N#QSTATTLFHSLPLLRYIFVRER.V
0.9881





IPI00020985
M.GMNTGTNAGM*NPGMLAAGNGQGIMPNQVMN#GSIGAGR.G
0.7024





IPI00020986
R.LSHNELADSGIPGNSFN#VSSLVELDLSYNK.L
1





IPI00020986
K.LGSFEGLVN#LTFIHLQHNR.L
1





IPI00020986
K.LHINHNN#LTESVGPLPK.S
1





IPI00020986
K.AFEN#VTDLQWLILDHNLLENSK.I
1





IPI00020996
R.YLSLRN#NSLR.T
0.7943





IPI00020996
K.AGAFLGLTNVAVMN#LSGNCLR.N
1





IPI00020996
R.FVQAICEGDDCQPPAYTYNN#ITCASPPEVVGLDLR.D
0.9999





IPI00020996
K.ALRDFALQN#PSAVPR.F
0.9955





IPI00021089
R.WLSSTGPECN#CSLGNFDSQVGACGFNSR.I
0.8905





IPI00021106
K.AMAETFYLSNIVPQDFDN#NSGYWNR.I
0.7649





IPI00021131
L.DLSM*NN#ISQLLPNPLPSLRFLEELRLAGNALTYIPK.G
0.8889





IPI00021131
K.IHHIPDYAFGN#LSSLVVLHLHNNRIHSLGK.K
0.5879





IPI00021175
K.EN#SSVEAKDSGLESK.K
0.7359





IPI00021175
M.KTQEPAGSLEEN#NSDK.N
0.6109





IPI00021176
K.TTTRQLSSPN#HSPSQSPN#QSPR.I
0.6246





IPI00021187
R.AQTEGIN#ISEEALNHLGEIGTKTTLR.Y
0.9365





IPI00021250
K.EIQHPNVITLHEVYEN#K.T
0.5461





IPI00021302
K.VSM*M*EKSELVN#ETRWQYYGTAN#TSGN#LSLTWHVK.S
0.6375





IPI00021304
R.FGGFGGPGGVGGLGGPGGFGPGGYPGGIHEVSVN#QSLLQPLNVK.V
0.999





IPI00021304
R.M*SGDLSSN#VTVSVTSSTISSNVASK.A
0.882





IPI00021305
K.VDEFN#VSSPQF.V
0.7039





IPI00021319
M.QNNWCFPACSFN#GTSAQEWFM*AQDCPYRK.R
0.5829





IPI00021364
K.N#VTFWGRPLPR.C
0.9279





IPI00021388
R.CTCGFSAVM*NRKFGN#NSGLFLE.D
0.6283





IPI00021426
R.M*LWEHN#STIIVMLTK.L
0.641





IPI00021426
R.KVEVEPLN#STAVHVYWK.L
1





IPI00021477
R.QNVYIPGSN#ATLTNAAGK.R
0.8796





IPI00021531
R.N#PSASTFLHLSTNSFR.L
0.9423





IPI00021556
R.MQSPQNLHGQQDDDSAAESFNGN#ET.L
0.8236





IPI00021557
K.M*FLN#NTTTNRHTSGEGPGSKTGDKEE.K
0.9548





IPI00021578
K.LGYNAN#TSVLSFQAVCR.E
1





IPI00021612
K.TLPDSAGYVEGLQCM*SVEN#ATTIR.T
0.5723





IPI00021689
K.EGKENTRITN#LTVNTGLDCSEK.T
0.693





IPI00021695
K.EASDIILTDDN#FTSIVK.A
0.8332





IPI00021711
R.SN#HTQATNDPPEVTVFPK.E
0.5239





IPI00021727
K.DQYVEPEN#VTIQCDSGYGVVGPQSITCSGN#R.T
0.9884





IPI00021727
R.FSLLGHASISCTVEN#ETIGVWR.P
1





IPI00021731
M.KLGTEALSTN#HSVIVNSPVITAAINKEFSNK.V
0.6088





IPI00021731
K.QSESSFITGDIN#SSASLNREGLL.N
0.909





IPI00021753
K.NEN#SSEQLDVDGDSSSEVSSEVNFNYEYAQM*EVTMK.A
0.5242





IPI00021786
R.M*IEDAIRSHSESASPSALSSSPNN#LSPTGWSQPK.T
0.5917





IPI00021807
R.M*ELSM*GPIQAN#HTGTGLLLTLQPEQK.F
0.6119





IPI00021817
R.EVSFLN#CSLDNGGCTHYCLEEVGWR.R
1





IPI00021834
R.YFYNN#QTK.Q
0.9342





IPI00021846
P.ASSDFSDLNTQTN#WTK.S
0.8431





IPI00021885
R.M*DGSLNFN#R.T
0.7193





IPI00021888
R.VSGYLNLAADLAHN#FTDGLAIGASFRGGR.G
0.7351





IPI00021891
K.DLQSLEDILHQVEN#K.T
1





IPI00021903
D.NTLQQN#SSSN#ISYSNAMQK.E
0.5195





IPI00021935
R.NGIALEILQN#TSYLPVLEGQALR.L
0.7079





IPI00021968
G.GQSPASGN#VTGNSN#STFISSGQVMNFK.G
0.8734





IPI00021970
R.SEHTGACNPCTEGVDYTN#ASNNEPSCFPCTVCK.S
0.7994





IPI00021997
K.LN#ITNIWVLDYFGGPK.I
0.9916





IPI00021998
K.CTLHFLTPGVN#NSGSYICRPKMIK.S
0.8551





IPI00021998
R.RKFVCFVQNSIGN#TTQSVQLKEK.R
0.9146





IPI00022072
K.SEHN#PSTSGCSSDQSSK.V
0.5193





IPI00022080
M.N#RSQFEELCAELLQK.I
0.7362





IPI00022080
K.ELN#NTCEPVVTQPK.P
0.9299





IPI00022080
K.NQQITHAN#NTVSNFKR.F
0.616





IPI00022200
R.VAVVQHAPSESVDN#ASM*PPVK.V
0.9999





IPI00022215
K.EHKAEKVPAVANYIMKIHN#FTSK.C
0.5359





IPI00022229
K.FVEGSKN#STVSLTTK.N
1





IPI00022229
R.FN#SSYLQGTNQITGR.Y
1





IPI00022229
K.N#LTDFAEQYSIQDWAK.R
1





IPI00022229
R.VNQNLVYESGSLN#FSK.L
1





IPI00022229
K.QVLFLDTVYGN#CSTHFTVK.T
1





IPI00022229
R.FEVDSPVYN#ATWSASLK.N
1





IPI00022229
K.YNQN#FSAGNNENIM*EAH.V
0.9997





IPI00022229
K.SSVITLNTNAELFN#QSDIVAHLLSSSSSVIDALQYK.L
0.9997





IPI00022229
K.TIRDLHLFIENIDFN#K.S
0.9993





IPI00022229
K.IQSPLFTLDANADIGN#GTTSANEAGIAASITAK.G
0.9989





IPI00022229
K.YDFN#SSMLYSTAK.G
0.9986





IPI00022229
K.SYN#ETK.I
0.9971





IPI00022229
K.QVFPGLNYCTSGAYSN#ASSTDSASYYPLTGDTR.L
0.9936





IPI00022229
K.DFHSEYIVSASN#FTSQLSSQVEQFLHR.N
0.9921





IPI00022229
A.EEEM*LEN#VSLVCPK.D
0.985





IPI00022229
G.GN#TSTDHFSLR.A
0.9798





IPI00022229
K.VHN#GSEILFSYFQDLVITLPFELR.K
0.9723





IPI00022229
K.LYQLQVPLLGVLDLSTNVYSNLYN#WSASYS.G
0.5051





IPI00022250
R.ALKGETVN#TTISFSFKGIKFSKGK.Y
0.6772





IPI00022255
K.LN#DTTLQVLNTWYTK.Q
0.8462





IPI00022286
A.HAASTEEKEAGVGN#GTCAPVR.L
0.8239





IPI00022296
R.SLYGKEDN#DTLVR.C
0.9917





IPI00022296
R.TFTDKWEDYPKSEN#ESNIR.Y
1





IPI00022296
K.QISESTNHIYSNLAN#CSPNRQK.P
0.8465





IPI00022314
K.FNGGGHIN#HSIFWTN#LSPN.G
0.6848





IPI00022325
K.VQGLVPAGGSSSN#STR.E
0.9971





IPI00022325
R.QNM*CPAHQN#RSLA
0.8074





IPI00022331
R.M*AWPEDHVFISTPSFN#YTGR.D
1





IPI00022331
R.QPQPVHLLPLHGIQHLNMVFSN#LTLEHINAILLGAYR.Q
0.9557





IPI00022331
K.AELSN#HTRPVILVPGCLGNQLEAK.L
0.5521





IPI00022371
R.VEN#TTVYYLVLDVQESDCSVLSR.K
1





IPI00022371
R.VIDFN#CTTSSVSSALANTK.D
1





IPI00022371
R.HSHNN#NSSDLHPHK.H
0.9976





IPI00022375
M.LGGYGHISSSIDIN#SSR.K
0.8028





IPI00022391
R.ESVTDHVNLITPLEKPLQN#FTLCFR.A
1





IPI00022392
R.NPPM*GGNVVIFDTVITNQEEPYQN#HSGR.F
1





IPI00022395
R.FSYSKN#ETYQLFLSYSSK.K
1





IPI00022395
R.AVN#ITSENLIDDVVSLIR.G
1





IPI00022417
A.VEFFN#LTHLPANLLQGASK.L
0.997





IPI00022417
K.LPPGLLAN#FTLLR.T
1





IPI00022417
R.DGFDISGNPWICDQN#LSDLYR.W
1





IPI00022417
K.MFSQN#DTR.C
0.9952





IPI00022417
R.QLDMLDLSN#NSLASVPEGLWASLGQPNWDMR.D
0.6558





IPI00022418
F.LYNNHN#YTDCTSEGR.R
0.9808





IPI00022418
K.LDAPTNLQFVN#ETDSTVLVR.W
1





IPI00022418
R.DQCIVDDITYNVN#DTFHK.R
1





IPI00022418
S.PGLEYN#VSVYTVK.D
0.9975





IPI00022418
R.HEEGHMLN#CTCFGQGR.G
0.9938





IPI00022426
T.PPDNIQVQENFN#ISR.I
1





IPI00022426
R.YFYN#GTSMACETFQYGGCM*GNGNNFVTEK.E
0.9996





IPI00022426
K.WN#ITM*ESYVVHTNYDEYAIFLTK.K
0.9955





IPI00022429
I.TN#ATLDQITGK.W
0.5341





IPI00022429
R.QDQCIYN#TTYLNVQR.E
1





IPI00022429
R.EN#GTISR.Y
0.887





IPI00022430
M.FVMGVNENDYNPGSM*NIVSN#ASCTTNCLAPLAK.V
0.6785





IPI00022431
K.VCQDCPLLAPLN#DTR.V
1





IPI00022431
K.AALAAFNAQNN#GSNFQLEEISR.A
1





IPI00022432
K.ALGISPFHEHAEVVFTAN#DSGPR.R
1





IPI00022447
K.IILNALVAQQKN#GSPAGGDAKELDSKSK.G
0.824





IPI00022447
K.KNNLPFLTN#VTLPR.S
0.5774





IPI00022461
W.NLNN#DTEVPTASVAIEGASALNRVR.W
0.5787





IPI00022462
K.LAVDEEENADN#NTKAN#VTK.P
0.5547





IPI00022462
K.DFEDLYTPVN#GSIVIVR.A
1





IPI00022462
R.KQNNGAFN#ETLFR.N
0.9963





IPI00022463
K.CGLVPVLAENYN#K.S
1





IPI00022463
R.QQQHLFGSN#VTDCSGNFCLFR.S
1





IPI00022471
R.EDGDGDEDGPAQQLSGFNTN#QSNNVLQAPLPPMR.L
0.5492





IPI00022479
R.QSLTSPDSQSARPAN#RTALSDPSSR.L
0.5326





IPI00022479
M.CQELETGIVDLLIPSPN#ATAEVGYNR.D
0.804





IPI00022488
R.CSDGWSFDATTLDDN#GTMLFFK.G
0.9981





IPI00022488
K.ALPQPQN#VTSLLGCTH.-
1





IPI00022488
R.SWPAVGN#CSSALR.W
1





IPI00022488
R.N#GTGHGN#STHHGPEYM*R.C
0.9993





IPI00022525
A.MNEPQCFYN#ESIAFFYN#R.S
0.9212





IPI00022529
K.N#LSDVNILHR.L
0.5671





IPI00022557
R.GYPGQVCAN#DSDTLELPDSSRALLLGWVPTR.L
0.8556





IPI00022579
R.AVFIQGAEEHPAAFCYQVN#GSCPR.T
0.5777





IPI00022608
R.VEGLQGVYIATLIN#GSMNEENM*RSVITFDK.G
0.7377





IPI00022608
S.LLCLPKAN#NSR.S
0.6448





IPI00022609
L.KRKWNSLSVIPVLN#SSSYTK.E
0.5925





IPI00022643
K.ELLLTLDDSFNDVGSDNSN#QSSPRLRLPSPSMDK.I
0.7513





IPI00022674
R.SVNILFN#LTHR.V
0.999





IPI00022674
F.EN#LTYNQAASDSGSCGHVPVSPK.A
0.9785





IPI00022674
Q.N#FTTLEAAPSEAPDVWR.I
0.9323





IPI00022731
K.ELLETVVN#R.T
0.9883





IPI00022733
K.EGHFYYN#ISEVK.V
1





IPI00022733
R.IYSN#HSALESLALIPLQAPLK.T
1





IPI00022733
K.VSN#VSCQASVSR.M
0.9999





IPI00022733
R.GAFFPLTERN#WSLPNR.A
0.999





IPI00022733
K.VTELQLTSSELDFQPQQELM*LQITN#ASLGLR.F
0.9888





IPI00022792
R.VDLEDFEN#NTAYAK.Y
0.8906





IPI00022808
R.VGSSPKIN#VSPFYQN#QTSTQR.S
0.837





IPI00022850
K.VWKKIGIWNSNSGLN#MTDSNK.D
0.7854





IPI00022892
K.DEGTYTCALHHSGHSPPISSQN#VTVLR.D
0.8764





IPI00022895
H.N#ISVADSAN#YSCVYVDLKPPFGGSAPSER.L
1





IPI00022895
R.EGDHEFLEVPEAQEDVEATFPVHQPGN#YSCSYR.T
1





IPI00022895
R.FQSPAGTEALFELHN#ISVAD.S
0.9998





IPI00022895
L.AN#VTLTCQAR.L
0.961





IPI00022933
K.M*RMATPLLMQALPM*GALPQGPMQN#ATKYGN#MTE.D
0.9428





IPI00022933
R.MATPLLMQALPMGALPQGPM*QN#ATK.Y
0.9613





IPI00022937
R.QFYVAAQGISWSYRPEPTN#SSLN#LSVTSFK.K
0.9497





IPI00022937
K.VSAITLVSATSTTAN#M*TVGPEGK.W
1





IPI00022937
K.NSVLN#SSTAEHSSPYSEDPIEDPLQPDVTGIR.L
1





IPI00022937
K.NM*ASRPYSIYPHGVTFSPYEDEVN#SSFTSGR.N
1





IPI00022937
R.TNIN#SSRDPDNIAAWYLR.S
1





IPI00022937
K.TYEDDSPEWFKEDNAVQPN#SSYTYVWHATER.S
0.9214





IPI00022937
M.DNVGTWMLTSMN#SSPR.S
0.7819





IPI00023014
R.M*EACM*LN#GTVIGPGK.T
0.9997





IPI00023014
R.TEPM*QVALHCTN#GSVVYHEVLNAM*ECK.C
1





IPI00023014
R.HCDGN#VSSCGDHPSEGCFCPPDK.V
0.9999





IPI00023014
K.TTCNPCPLGYKEEN#NTGECCGR.C
0.9991





IPI00023014
K.GQVYLQCGTPCN#LTCR.S
0.9986





IPI00023014
R.GLQPTLTNPGECRPN#FTCACR.K
0.9829





IPI00023014
K.WN#CTDHVCDATCSTIGM*AH.Y
0.8999





IPI00023019
R.LDVDQALN#R.S
0.9997





IPI00023019
R.SHEIWTHSCPQSPGN#GTDASH.-
1





IPI00023100
R.TGGIGDSRPPSFHPNVASSRDGMDN#ETGTESMVSHR.R
0.6243





IPI00023109
R.TILEN#NSGRSNSNPFNKEELTAILK.F
0.7956





IPI00023118
-.MGLN#TSASTFQLTGFPGMEK.A
0.9007





IPI00023183
K.N#WTAALFTGNLLLAR.D
0.5026





IPI00023186
K.EATN#TTSEPSAPSQDLLDLSPSPR.M
0.8169





IPI00023212
K.AMILLN#SSMYPLVTATQ.D
0.7868





IPI00023217
K.DM*VVM*LLSM*LEGNVVN#GTIGK.Q
0.9428





IPI00023217
Q.KAMFDHLSYLLEN#SSVGLASPAM*R.G
0.5504





IPI00023237
-.MSYQLYNYPN#KTLLFSK.H
0.7534





IPI00023246
K.VAGSEEN#GTAETEEVEDESASGELDLEAQFHLH.F
0.5677





IPI00023258
K.AENSAAVQIN#LSPTM*LENVK.K
0.5821





IPI00023312
R.EDFHYN#DTAGYFIIGGSRYVAGIEGFFGPLK.Y
0.6552





IPI00023314
R.EQECEIISFAETGLSTIN#QTR.L
0.9485





IPI00023315
R.YDPFPAGDPEPRAAPN#NSADPRV.R
0.9586





IPI00023339
K.KKPSMPN#VSNDLSQKLYATM*EKHK.E
0.52





IPI00023339
R.NQQTILGSPASGIQNTIGSVGTGQQN#AT.S
0.5983





IPI00023340
R.MTQPMM*N#SSYHSNPAYMN#QTAQYPMQM.Q
0.5611





IPI00023412
N.N#YTAVFLGTVNGR.L
0.5886





IPI00023502
R.YTSAGISVTVKELFPAPVLN#ASVTSP.L
0.6911





IPI00023586
K.VADRTKSENGLQN#ESLSSTHHTDGLSK.I
0.6943





IPI00023586
R.NHETTN#LSIQQK.R
0.6117





IPI00023648
R.FQAFAN#GSLLIPDFGK.L
0.9988





IPI00023648
K.SLDLSHNLISDFAWSDLHN#LSALQLLK.M
0.9995





IPI00023673
K.GLN#LTEDTYKPR.I
0.9999





IPI00023673
K.EPGSN#VTM*SVDAECVPM*VR.D
1





IPI00023673
R.TVIRPFYLTN#SSGVD.-
1





IPI00023673
R.ALGFEN#ATQALGR.A
1





IPI00023673
K.AAIPSALDTN#SSK.S
0.9996





IPI00023673
R.DAGVVCTN#ETR.S
0.9987





IPI00023722
R.LLPILSQQSTIN#LSHNPLDCTCSNIHFLTWYK.E
0.798





IPI00023722
T.FSRLM*N#LTFLDLTR.C
0.7961





IPI00023768
K.FLALVTMN#QSGWGTSGR.R
0.5767





IPI00023785
R.GLDVEDVKFVINYDYPN#SSEDYVHRIGR.T
0.9016





IPI00023807
K.NLLIFN#LSEGDSGVYQ.C
0.989





IPI00023814
R.TLSDVPSAAPQN#LSLEVR.N
0.9998





IPI00024036
M.APMN#QSQVLM*SGSPLELNSLGEEQR.I
0.5572





IPI00024046
K.ANYNLPIM*VTDSGKPPM*TN#ITDLR.V
0.9979





IPI00024046
K.IN#NTHALVSLLQNLNK.A
0.6016





IPI00024067
K.FDVN#TSAVQVLIEHIGNLDR.A
0.8201





IPI00024089
-.MACLM*AAFSVGTAMN#ASSYSAEMTEPK.S
0.6233





IPI00024151
M.AVRGLIRPMN#KSPM*LITGIR.C
0.5572





IPI00024163
R.FRGN#LSGKRVDFSGR.T
0.8261





IPI00024214
R.KDEN#ESSAPADGEGGSELQPK.N
0.5864





IPI00024278
K.SSLLLAILGEMQTLEGKVHWSNVN#ESEPSFEATR.S
0.674





IPI00024282
K.M*N#DSNSAGAGGPVKITEN#RSK.K
0.7826





IPI00024284
R.NLHQSN#TSR.A
0.9647





IPI00024289
I.WCEDFLVRSFYLKNLQTN#ETR.T
0.76





IPI00024289
K.AENSHSHSDYIN#ASPIMDHDPR.N
0.7796





IPI00024292
R.CIPQSWVCDGDVDCTDGYDENQN#CTRR.T
0.5367





IPI00024292
K.YDGSNRQTLVN#TTHRPFD.I
0.8456





IPI00024316
R.HN#LSLHSKFIKVHNEATGK.S
0.6199





IPI00024316
R.NAWGN#QSYAELISQAIE.S
0.6386





IPI00024330
R.DGTLEYAPVDITVNLDASGSQCGLHSPLQSDN#ATDSPK.S
0.6181





IPI00024344
K.IIKSLQKN#GSVVAM*TGDGVNDAVALKAADIGVAMGQT.G
0.9981





IPI00024357
M.ALYHN#ISGVGLFLHPVGLELLLDHR.A
0.7441





IPI00024382
R.NTGN#GTQSSM*GSPLTR.P
0.6092





IPI00024403
-.M*AAQCVTKVALN#VSCANLLDKDIGSK.S
0.5908





IPI00024425
V.HSDFTAAATRGAM*AVIDGNVM*AIN#PSEETK.M
0.8108





IPI00024467
K.IKGIVENMGINANN#M*SDFIM*KVDALMSSVPK.R
0.71





IPI00024519
K.MLAQKSGNIIN#M*SSVASSVK.G
0.7651





IPI00024617
K.YLCIPAADSPSQN#LTR.H
0.9154





IPI00024619
K.CLKCNEYVEN#RTK.S
0.7714





IPI00024684
M.FNQDIEKLVEGEEVVREN#ETR.L
0.7901





IPI00024684
K.HFGEFFNLN#QTVQSTIEDIK.V
0.8074





IPI00024726
K.LENSKN#GTAGLIPSPELQEWR.V
0.7954





IPI00024769
R.RTEKLFFTILSPN#QSK.P
0.8668





IPI00024787
K.YN#VTVIQYIGELLR.Y
0.6148





IPI00024802
R.LMPLEAGIPDPPN#MSAELIQLKAKER.H
0.8143





IPI00024816
P.HM*LPEDGAN#LSSARGILSLIQSSTR.R
0.6406





IPI00024825
R.N#GTLVAFR.G
0.992





IPI00024825
K.MTSTMPELN#PTSRIAEAM*LQTTTR.P
0.7371





IPI00024842
K.DN#SSLNPLDRLISEDKKEK.M
0.8154





IPI00024887
R.RQQSRN#R.S
0.8613





IPI00024896
K.IKNM*N#STLTFVTLSGELRAR.R
0.7423





IPI00024911
R.QALLKQGQDN#LSSVKETQK.K
0.5629





IPI00024933
K.NIKHSGN#ITFDEIVNIAR.Q
0.9525





IPI00024970
A.KEAAGASKALN#V.T
0.8369





IPI00024970
R.VLAPILPDN#FSTPTGSR.T
0.5501





IPI00024975
K.TFTMMGPSESDN#FSHNLR.G
0.5064





IPI00025054
M.EPGN#GSLDLGGDSAGR.S
0.6398





IPI00025073
K.ENEEFLIGFN#ITSKGRQLPKR.R
0.6998





IPI00025076
M.DNPFEFNPEDPIPVSFSPVDTN#STSGDPVEKK.D
0.9351





IPI00025092
E.APM*FTQPLVNTYAIAGYN#ATLN#CSVR.G
0.6144





IPI00025110
R.KWN#VTSLETLK.A
0.7974





IPI00025158
M.KM*YSDAFLN#DSYLK.Y
0.5533





IPI00025193
R.LQEM*GFIIYGNEN#ASVVPLLLYMPGK.V
0.8126





IPI00025264
R.EKTSLSANN#ATLEKQLIELTRTNELLKSK.F
0.7759





IPI00025276
R.GLRGPN#LTSPASITFTTGLEAPR.D
1





IPI00025310
K.NCRN#KSLLRSRR.T
0.7196





IPI00025310
K.RPETKLKPLPVAPSQPTLGSSNIN#GSIDYPAK.N
0.5894





IPI00025333
R.KACKN#CTCGLAEELEK.E
0.6207





IPI00025426
N.YLN#ETQQLTQEIK.A
0.9924





IPI00025426
K.TFSSM*TCASGAN#VSEQLSLK.L
1





IPI00025426
K.KGCVLLSHLN#ETVTVSASLESGR.E
1





IPI00025426
K.GCVLLSHLN#ETVTVSASLESGREN#R.S
0.5814





IPI00025465
R.VIHLQFNNIASITDDIFCKAN#DTSYIR.D
0.971





IPI00025468
-.M*ENLQTN#FSLVQGSTK.K
0.5035





IPI00025477
M.IFDFYKQN#KTTR.D
0.5184





IPI00025477
K.TAN#SSPIHFAGAQTSLPAFSPGR.L
0.7326





IPI00025489
K.TLIPN#ASNEAIQLM*TEM*LNWDPK.K
0.5307





IPI00025489
-.M*NRYTTM*RQLGDGTYGSVLMGKSN#ESGELVAIKR.M
0.5123





IPI00025616
R.FLGTSGQN#VSDIFR.Y
0.9973





IPI00025700
R.SLHN#LSTPEVPASVQTVTIESSVTVKIENKESR.E
0.9517





IPI00025753
M.ATFAGQIEENSNANTLVM*ILN#ATDADEPNNLNSK.I
0.7385





IPI00025786
K.QEN#SSN#SSPAPEPNSAVPSDGTEAK.V
0.793





IPI00025788
K.RKN#STSSTSN#SSAGNNAN#STGSKK.K
0.5861





IPI00025815
M.MGM*LASQQN#QSGPSGNNQNQGNMQR.E
0.6898





IPI00025852
K.ELYEPIWQN#FTDPQLR.R
0.9999





IPI00025861
L.TFPN#SSPGLRR.Q
0.666





IPI00025862
K.TLFCN#ASK.E
0.984





IPI00025862
R.LGHCPDPVLVNGEFSSSGPVN#VSDK.I
1





IPI00025862
K.EWDN#TTTECR.L
0.9996





IPI00025862
R.DCDPPGNPVHGYFEGNN#FTLGSTISYYCEDR.Y
0.9962





IPI00025864
R.GM*N#LTVFGGTVTAFLGIPYAQPPLGR.L
1





IPI00025864
K.YGNPN#ETQN#NSTSWPVFK.S
1





IPI00025864
R.DN#YTKAEEILSR.S
1





IPI00025864
K.WSDIWN#ATK.Y
0.9996





IPI00025864
K.DN#NSIITR.K
0.9939





IPI00025864
K.N#ATVLIWIYGGGFQTGTSSLHVYDGK.F
0.7544





IPI00025864
R.EN#ETEIIK.C
0.6817





IPI00025879
K.VKN#LTEEMAGLDETIAKLTK.E
0.7899





IPI00025879
R.QAEEAEEQSNVN#LSK.F
0.9989





IPI00025879
R.EN#QSILITGESGAGK.T
0.9959





IPI00026029
R.SVRKN#LTYSCRSNQDCIINK.H
0.9277





IPI00026089
K.LLLKIKN#GTPPM*R.K
0.561





IPI00026108
M.KN#VSHNPLLLLTPQKVK.R
0.643





IPI00026157
R.IRTYN#FTQDRVSDHRIAYEVR.D
0.747





IPI00026157
N.RNCILHLLSKN#WSR.R
0.6247





IPI00026201
A.ETTLTQSPAFM*SATPGDKVN#ISCK.A
0.9996





IPI00026240
K.DSSGVIHVMLN#GSEPTGAYPIK.G
0.7287





IPI00026270
M.HGDETVGRELLLHLIDYLVTSDGKDPEITNLIN#STR.I
0.6956





IPI00026327
K.NQELKAGTSIMGSHLTSAETVTLDSLKAVEVVN#LSVS.C
0.5498





IPI00026466
K.LSTLLNHNN#DTEEEER.L
0.6877





IPI00026631
D.EAKNN#ITIFTRILDRLLDGYDNR.L
0.6508





IPI00026638
R.STEEPTAPASPQPPN#DSR.L
0.5892





IPI00026638
A.N#RTGSVEAQTALKK.R
0.6591





IPI00026639
R.LSYNVIPLN#LTLDNRVADQLWVP.D
0.8409





IPI00026647
R.FLITHN#PTN#ATLSTFIEDLK.K
0.9108





IPI00026659
M.YFFLAN#LSLADACFVSTTVPK.M
0.8187





IPI00026673
R.EQLSSAN#HSLQLASQIQK.A
0.6035





IPI00026813
Q.RYFVISN#TTGYNDR.A
0.7041





IPI00026828
L.EECCTHN#NSATLSWK.Q
0.8658





IPI00026885
M.ILN#SSTEDGIKR.I
0.7889





IPI00026885
K.SHSN#LSTKMSTLSYRPSDN#VSSSTK.K
0.5691





IPI00026975
L.DCPSSIIGMGLGN#ASTGYGK.I
0.8383





IPI00026987
M.QRLNIGYVIN#VTTHLPLYHYEK.G
0.9563





IPI00026993
G.DSSHCSN#ASTHSNQEAGPSNKR.T
0.7712





IPI00027035
F.EAFQDALNQETTYVSN#LTR.S
0.914





IPI00027086
M.SACN#ISIQGPSIYNK.E
0.7837





IPI00027087
R.YFCLAANDQNN#VTIM*AN.L
0.6509





IPI00027146
K.INPKN#YTENELEKITR.R
0.6551





IPI00027174
R.M*DKPAN#CTHDLYMIM*R.E
0.5864





IPI00027178
R.EGVQLN#LSFIR.P
0.783





IPI00027195
V.NALN#FSVN#YSEDFVELNAAR.Y
0.9366





IPI00027200
R.GSHAGN#LTVAVVLPLAN#TSYPWSWARVGPAVELALAQVK.A
0.9747





IPI00027220
K.IHQGTLTILSLN#SSLLGYYQCLAN#NSIGAIVS.G
0.8917





IPI00027235
K.AATCINPLN#GSVCERPAN#HSAK.Q
0.9999





IPI00027235
R.YLHTAVIVSGTMLVFGGNTHN#DTSM*SHGAK.C
1





IPI00027235
K.AATCINPLN#GSVCER.P
1





IPI00027235
K.M*PSQAPTGNFYPQPLLN#SSM*CLEDSR.Y
1





IPI00027235
K.ISN#SSDTVECECSENWK.G
1





IPI00027235
R.VFHIHN#ESWVLLTPK.A
1





IPI00027235
K.IDSTGN#VTNELR.V
1





IPI00027235
R.N#HSCSEGQISIFR.Y
0.9999





IPI00027235
R.YN#WSFIHCPACQCNGHSK.C
0.9999





IPI00027235
R.GICN#SSDVR.G
0.9996





IPI00027235
R.NHPN#ITFFVYVSN#FTWPIK.I
0.9982





IPI00027235
K.CIN#QSICEK.C
0.9913





IPI00027235
R.GCSCFSDWQGPGCSVPVPAN#QSFWTR.E
0.9717





IPI00027235
K.AVVNGNIMWVVGGYMFN#HSDYNMVLAYDLASR.E
0.9159





IPI00027235
K.CIN#QSICEKCEN#LTTGK.H
0.6417





IPI00027242
Q.RHAAEIAN#MSLDILSAVGTFRMRHMPEVPVR.I
0.9484





IPI00027259
K.N#NSPGTAEGCGGGGGGGGGGGSGGSGGGGGGGGGGDK.S
0.9968





IPI00027269
R.LGSTFSLDTSMSMN#SSPLVGPECDHPK.I
0.7599





IPI00027310
R.VN#STELFHVDR.H
0.9983





IPI00027310
R.ALLTN#VSSVALGSR.R
0.9989





IPI00027341
R.EVQGN#ESDLFM*SYFPR.G
0.6737





IPI00027377
R.TVYLYPN#QTGLPDPLSR.H
1





IPI00027410
R.ISALGLPTN#LTHILLFGM*GR.G
1





IPI00027410
R.N#LSSLESVQLDHNQLETLPGDVFGALPR.L
1





IPI00027410
K.LLDLSGNN#LTHLPK.G
0.9931





IPI00027412
R.LQLSNGN#MTLTLLSVKR.N
0.7565





IPI00027422
G.QTCN#CSTGSLSDIQPCLR.E
0.5268





IPI00027444
K.LEESYTLNSDLARLGVQDLFN#SSK.A
0.976





IPI00027473
L.WLALDYVVSN#ASVMNLLIISFDR.Y
0.526





IPI00027474
M.AN#FTPVN#GSSGN#QSVR.L
0.9558





IPI00027482
K.AVLQLNEEGVDTAGSTGVTLN#LTSK.P
0.9994





IPI00027482
R.AQLLQGLGFN#LTER.S
1





IPI00027482
D.PNAAYVN#M*SNHHR.G
1





IPI00027482
K.VTISGVYDLGDVLEEMGIADLFTNQAN#FSR.I
0.9995





IPI00027482
N.YVGN#GTVFFILPDK.G
0.9813





IPI00027493
K.DASSFLAEWQN#ITK.G
1





IPI00027493
K.SLVTQYLN#ATGNR.W
1





IPI00027504
R.AFGSNPN#LTK.V
0.9987





IPI00027504
K.LYLGSNN#LTALHPALFQN#LSK.L
1





IPI00027504
R.NAITHLPLSIFASLGN#LTF.L
1





IPI00027504
R.QGSLGLQYN#ASQEWDLR.R
0.9999





IPI00027504
N.IFSN#LTSLGK.L
0.9416





IPI00027507
K.LGYNAN#TSILSFQAVCR.E
0.9999





IPI00027507
K.FVQGN#STEVACHPGYGLPK.A
1





IPI00027508
R.STLITVLN#ISEIESR.F
0.75





IPI00027508
K.WN#GSVIDEDDPVLGEDYYSVENPANKR.R
0.5759





IPI00027534
K.SISWDEN#GTCIVINE.E
0.8155





IPI00027569
-.MASN#VTNEKM*DPHSM*NSR.V
0.9216





IPI00027642
R.NTEASSEEESSASRMQVEQN#LSDH.I
0.8298





IPI00027666
R.SN#SSAANLMAKK.R
0.7236





IPI00027682
A.ASSIWSPASISPGSAPASVSVPEPLAAPSN#TSCM*QR.S
0.8377





IPI00027701
R.GCASTGVIM*SVN#NSLYLGPILKFGSK.E
0.7524





IPI00027799
R.N#GSANRN#SSHRTAAQPAETPEDVPGSLDDGADCEA.V
0.962





IPI00027803
K.MLSLNN#YSVPQSTR.E
0.5599





IPI00027828
-.M*NN#PSETSKPSM*ESGDGNTGTQTNGLDFQK.Q
0.768





IPI00027968
K.KQPFSSASSQN#GSLSPHYLSSVIK.Q
0.5436





IPI00028030
R.YRCN#DTIPEDYETHQLR.Q
1





IPI00028030
R.CGPCPAGFTGN#GSHCTDVNECNAHPCFPR.V
0.9891





IPI00028119
R.IYN#VTYLEPSLR.I
0.5842





IPI00028210
K.GTGN#DTVLNVALLNVISNQECNIK.H
1





IPI00028277
R.AAYN#VTLLNFMDPQK.M
0.993





IPI00028338
R.VFYFMVGTAFAN#STCQLIVCQM*SSTR.C
0.7299





IPI00028382
R.NGESMLN#ASLVN#ASSLSEAEQLQR.E
0.9011





IPI00028413
K.TAFITN#FTLTIDGVTYPGNVK.E
0.9995





IPI00028413
K.NAHGEEKEN#LTAR.A
0.9994





IPI00028448
K.NLDLILPTLRN#YTVINSKIIVVTIR.P
0.625





IPI00028448
R.FRDIPN#TSSMENPAPNK.N
0.8805





IPI00028448
K.KDLSCSN#FSLLAYQFDHFSHEKIK.D
0.8152





IPI00028448
M.FPKN#FTN#CTWTLENPDPTK.Y
0.6661





IPI00028490
N.FGHN#DSTSQM*SLNSAAVTK.T
0.6305





IPI00028492
R.MCQAGN#ATVKQSRYR.I
0.5036





IPI00028514
K.KFLYN#FTQIPHLAGTEQNFQL.A
0.5133





IPI00028541
R.KM*PSNQN#VSPSQR.D
0.6196





IPI00028570
I.QAAASTPTN#ATAASDANTGDR.G
0.9839





IPI00028588
K.NFHSMQNLCPPQTN#GTPEGR.Q
0.6444





IPI00028610
K.SCVSNIESTLSALQYVSSIVVSLEN#R.S
0.5546





IPI00028642
I.LESLM*CN#ESSMQSLRQR.K
0.5424





IPI00028928
K.DGKN#KTDKKDHSNIGN#DSKKTDGTKQRS.H
0.7479





IPI00028931
R.ERESFLAPSSGVQPTLAMPNIAVGQN#VTVTER.V
0.7219





IPI00028952
D.KMIENHN#ISTPFSCQFCK.E
0.5917





IPI00028957
M.SNVEQALFARLLLQDPGNHLIN#MTSSTTLN#LSADR.D
0.7777





IPI00028987
K.LIPFSPAVN#TSVSTVASTVAPMYAGDLR.T
0.6633





IPI00028987
K.TRGRGAAN#DSTQFTVAGRMVKK.G
0.6108





IPI00029011
C.IIQMQGN#STSIINPK.N
0.5849





IPI00029019
R.RGGRFSAQGM*GTFNPADYAEPANTDDNYGN#SSGN.T
0.5824





IPI00029048
R.FTLTQSEADADILFN#FSHFK.D
0.7949





IPI00029061
K.EGYSN#ISYIVVNHQGISSR.L
1





IPI00029061
K.VSEHIPVYQQEEN#QTDVWTLLN#GSK.D
1





IPI00029061
K.CGN#CSLTTLK.D
0.9955





IPI00029061
R.DQDPM*LNSN#GSVTVVALLQASCY.L
0.6691





IPI00029166
R.FQGN#DTSPESFLLHNALAR.K
0.6772





IPI00029172
K.WYLENVYPEM*RVYN#NTLTYGEVRNSK.A
0.5181





IPI00029178
K.CEQSYGTN#SSDESGSFSEADSESCPVQDR.G
0.6131





IPI00029193
R.CFLGN#GTGYR.G
0.9999





IPI00029193
K.YIPYTLYSVFN#PSDHDLVLIR.L
1





IPI00029193
R.DSVSVVLGQHFFN#R.T
1





IPI00029260
R.LRN#VSWATGR.S
0.9999





IPI00029260
R.CMWSSALNSLN#LSFAGLEQVPK.G
0.9515





IPI00029268
K.SPM*QWDN#SSNAGFSEASNTWLPTNSDYHTVNVDV.Q
0.9545





IPI00029273
M.VSN#ESVDYRATFPEDQFPN#SSQN#GSCR.Q
0.8522





IPI00029273
R.HVFPHN#HTADIQSEVH.C
0.9993





IPI00029324
K.RNTELETLLAKLIQTCQHVEVN#ASR.Q
0.8552





IPI00029343
R.NMANGQPHSVN#ITR.H
0.6786





IPI00029411
R.IDSQLHTPMYFFLAN#LSFVDVCN#STTITPK.M
0.7805





IPI00029449
K.SVTIQAPGEPLLDN#ESTR.G
0.617





IPI00029468
M.ESYDVIANQPVVIDN#GSGVIK.A
0.6352





IPI00029533
R.N#VTSNDEVLFN#VTVTMKK.C
0.7091





IPI00029591
M.LRN#STDTTPLTGPGTPESTTVEPAARR.S
0.906





IPI00029643
M.NKAGAVM*HSGM*QINM*QAKQN#SSKTTSKRR.G
0.6042





IPI00029643
R.FHN#HTTHM*SLVGTFPWMAPEVIQSLPVSETC.D
0.6596





IPI00029728
K.AVVVFDEAHNIDNVCIDSM*SVN#LTRR.T
0.9764





IPI00029739
K.IPCSQPPQIEHGTIN#SSR.S
1





IPI00029739
R.ISEEN#ETTCYMGK.W
1





IPI00029739
K.SPDVIN#GSPISQK.I
0.9999





IPI00029739
K.MDGASN#VTCINSR.W
0.9995





IPI00029739
R.WDPEVN#CSM*AQIQLCPPPPQIPNSHN#MTTTLNYR.D
0.9978





IPI00029739
R.SPYEMFGDEEVMCLNGN#WTEPPQCK.D
0.9941





IPI00029739
K.LN#DTLDYECH.D
0.99





IPI00029739
Y.YYGDSVEFN#CSESFTM*IGHR.S
0.941





IPI00029751
K.GTEWLVN#SSR.I
0.7866





IPI00029751
K.GTEWLVN#SSRILIWEDGSLEINN#ITR.N
0.8616





IPI00029768
K.IN#NSTNEGM*NVK.K
0.6256





IPI00029778
R.RSN#VSSPATPTASSSSSTTPTR.K
0.5124





IPI00029863
H.LALGAQN#HTLQR.L
0.9987





IPI00029954
K.VSKN#DTEEESN#K.S
0.5904





IPI00030075
R.LHVGNYN#GTAGDALRFNK.H
0.6391





IPI00030099
R.GQGTASSGN#VSDLAQTVKTFDNLK.T
0.6284





IPI00030101
R.GPSHPLDLGTSSPN#TSQIHWTPYR.A
0.8037





IPI00030153
K.EQQPNDLLSVQFIDYGN#VSVVHTNK.I
0.7133





IPI00030241
T.TDFCSVSTATPVPTAN#STAKPTVQPSPSTTSK.T
0.6144





IPI00030250
K.TNLIVNYLPQN#MTQEELK.S
0.7865





IPI00030360
R.EITASSAVSILIKPEQETDPLPVVSRN#VSADAK.C
0.6648





IPI00030380
K.LQESIEYEDLGKN#NSVK.T
0.9004





IPI00030380
R.LNVN#ATDSSSTSNHK.Q
0.5921





IPI00030393
M.RSFLQQDVN#KTKSR.L
0.6779





IPI00030414
R.EPSDPTSN#RSTFHPGDSQKPVK.R
0.9579





IPI00030418
K.QTDVIN#ASWWVMSN#KTRDELER.S
0.6331





IPI00030536
K.RN#SSSSSTDSETLRYNHNFEPK.S
0.6821





IPI00030572
K.LPLSHSALPSQALGGIASGLGMQNLN#SS.R
0.7686





IPI00030572
R.NNPVIQSSTTTN#TTTTTTTTTSN#TTHR.V
0.6237





IPI00030648
R.GNEATEGSGLLLN#STGDLM*K.K
0.6517





IPI00030739
R.FLLYN#R.S
0.7531





IPI00030739
K.TELFSSSCPGGIMLN#ETGQGYQR.F
0.9999





IPI00030746
K.FQDLLSEEN#ESTALPQVLAQPSTSRKR.P
0.5888





IPI00030790
K.LSSQGN#VSGKRK.N
0.5281





IPI00030828
R.DVLQNHLTEVLTLVAMELPHN#VSSAEAVLR.H
0.9971





IPI00030851
K.KLN#CSPDSFR.C
0.7295





IPI00030868
K.EDGKTLYANTIN#GSGLAID.R
0.8024





IPI00030871
K.LLLSQLDSHPSHSAVVN#WTSYASSIEALSSGNK.E
0.9997





IPI00030871
K.LTGVAGN#YTVCQK.D
0.9998





IPI00030875
I.MYPIAVMGN#ITIILMSR.L
0.6124





IPI00030882
K.VAKNAQNIN#PSSSQNSQNFATYK.E
0.5715





IPI00030882
M.VVTLTELPSGN#DTSGLEN#KTVVVTTILESPYVMMKK.N
0.9147





IPI00030907
R.IVAECNAVRQALQDLLSEYMN#NTGRK.E
0.5831





IPI00030907
K.KN#ATM*LYTASQAFLRHPDVAATRANR.D
0.557





IPI00030930
K.FIENIGYVLYGVYN#VTM*VVVLLNM*LIAM*IN#N.S
0.5581





IPI00030930
K.TRYQAGMRNSEN#LTAN#NTLSKPTR.Y
0.8356





IPI00030940
R.LVKVKNEGDDFGWGVVVN#FSKK.S
0.8263





IPI00030986
K.EEDFMQLSPQELISVISN#DSLNVEK.E
0.7113





IPI00031002
K.N#VSQENMCSASAAFK.S
0.885





IPI00031002
M.VAGLLNSGNSN#KTIHTSSSIK.L
0.6624





IPI00031023
K.NM*LVLN#LSHNSIDTIPNQLFIN#LTDLLYLDLSENR.L
0.6059





IPI00031046
M.M*N#NTDFLMLNNPWNK.L
0.8844





IPI00031064
E.N#ITIVDISR.K
0.5226





IPI00031076
R.IVN#DTYR.T
0.9162





IPI00031131
R.AGPN#GTLFVADAYK.G
0.9997





IPI00031138
R.RSLEQHGLPWAIISIPVN#VTSIPTFELLQPPWTFW.-
0.8046





IPI00031171
R.SVQLHDSGN#YSCYR.A
0.9963





IPI00031282
A.VAAGTPN#TSGSIHENPPK.A
0.542





IPI00031411
R.FAN#LTPEEFVGDYWR.N
0.9062





IPI00031509
V.ENLIILAN#NSLSSNGN#VTESGCK.E
0.5445





IPI00031522
K.STKPIVAAIN#GSCLGGGLEVAISCQYR.I
0.5098





IPI00031556
K.N#ATLVSPPAQTIN#QTPVTLQVPG.L
0.9944





IPI00031589
R.CN#SSLSNHQR.I
0.6205





IPI00031595
R.TASIWVPPLQERN#SSWDR.I
0.5407





IPI00031620
L.GDQM*LN#ATVM*NHGDTLTATATATAR.A
0.7552





IPI00031620
R.EN#LTVFSFLGPIVN#LSEPTAHEGSTVTVSC.M
0.6788





IPI00031658
R.YVKTTGN#ATVDHLSK.Y
0.5665





IPI00031696
K.LNYLPPN#ASALFR.K
0.9459





IPI00031710
K.CVPVTLWHLGYWLCYVN#STVNPICYALCN#R.T
0.6615





IPI00031773
M.SAAAM*GSGSGN#MSAGSMN#MSSYVGAGMSPSLAGM*S.P
0.9983





IPI00031789
R.PTLLN#DTGN#YTCM*LR.N
0.9637





IPI00031801
E.GEKGAEAAN#VTGPDGVPVEGSRYAADR.R
0.5246





IPI00031907
K.IFQIYKGN#FTGSVEPEPSTLTPR.T
0.6701





IPI00032034
K.DFLDVYYN#LTLKTM*MGIEW.V
0.8857





IPI00032038
K.IN#RTLETANCMSSQTK.N
0.5753





IPI00032162
A.M*IQFAIN#STERKR.M
0.5121





IPI00032179
K.LGACN#DTLQQLMEVFK.F
1





IPI00032179
K.SLTFN#ETYQDISELVYGAK.L
1





IPI00032179
K.WVSN#KTEGR.I
0.9915





IPI00032190
R.LALTPAHLLFTADN#HTEPAAR.F
0.9997





IPI00032215
K.KLINDYVKN#GTR.G
1





IPI00032215
N.SPLDEEN#LTQENQDR.G
1





IPI00032215
K.YTGN#ASALFILPDQDK.M
1





IPI00032215
K.ALDKNVIFSPLSISTALAFLSLGAHN#TTLTEILK.A
0.9562





IPI00032220
R.VYIHPFHLVIHN#ESTCEQLAK.A
1





IPI00032220
R.LQAILGVPWKDKN#CTSR.L
1





IPI00032220
K.GFSLLAEPQEFWVDN#STSVSVPMLSGM*GTFQH.W
0.8079





IPI00032256
R.GNEANYYSN#ATTDEHGLVQFSIN#TTNVM*GTSLTVR.V
1





IPI00032256
K.VSN#QTLSLFFTVLQDVPVR.D
1





IPI00032256
K.SLGNVN#FTVSAEALESQELCGTEVPSVPEHGR.K
1





IPI00032256
K.GCVLLSYLN#ETVTVSASLESVR.G
1





IPI00032256
K.IITILEEEMN#VSVCGLYTYGK.P
1





IPI00032256
Y.VLDYLN#ETQQLTPEVK.S
0.9998





IPI00032256
K.GCVLLSYLN#ETVTVSASLESVRGN#R.S
0.9739





IPI00032258
R.N#PSDPM*PQAPALWIETTAYALLHLLLHEGK.A
0.9655





IPI00032258
R.GLN#VTLSSTGR.N
1





IPI00032258
R.FEQLELRPVLYNYLDKN#LTVSVH.V
1





IPI00032258
R.FSDGLESN#SSTQFEVK.K
1





IPI00032258
K.N#TTCQDLQIEVTVK.G
0.9998





IPI00032291
K.VEGSSSHLVTFTVLPLEIGLHNIN#FSLETWFGK.E
0.9986





IPI00032291
R.AN#ISHKDM*QLGR.L
0.9982





IPI00032291
K.YN#FSFR.Y
0.9944





IPI00032292
K.FVGTPEVN#QTTLYQR.Y
1





IPI00032299
R.ILTN#FTGVM*PPQFK.K
0.7638





IPI00032328
R.ITYSIVQTN#CSK.E
1





IPI00032328
K.LNAENN#ATFYFK.I
1





IPI00032328
K.YNSQN#QSNNQFVLYR.I
1





IPI00032328
R.HGIQYFNN#NTQHSSLFMLNEVK.R
0.9985





IPI00032334
R.VYVN#ISHPDMVDFARGK.T
0.602





IPI00032388
R.DDNMN#TSEDEDMFPIEMSSDEAMELLESSR.T
0.7408





IPI00032402
K.LM*QN#STSPPLK.L
0.5598





IPI00032402
M.IQTAHVGVGISGNEGLQAAN#SSDYSIAQFK.Y
0.5178





IPI00032406
R.YGEQGLREGSGGGGGMDDIFSHIFGGGLFGFMGN#QSR.S
0.839





IPI00032449
K.NAKSSGN#SSSSGSGSGSTSAGSSSPGAR.R
0.8221





IPI00032461
K.N#YTSVYDKNNLLTN#KTVMAHGCY.L
0.5331





IPI00032466
K.LREQVNSMVDISKMHM*ILYDLQQN#LSSSHR.A
0.9741





IPI00032680
R.CDKDSMPDGN#LSEEEK.L
0.8587





IPI00033017
M.NWVVGSADLEIIN#ATTGR.R
0.7931





IPI00033102
A.QPIEPITAAPSGSGN#GSGSSSSGGSSGGSGFCAVR.A
0.6723





IPI00033419
R.VKN#ISDADVHNAM*DNYE.C
0.8216





IPI00033486
R.KFAMSPSN#FSSSDCQDEEGR.K
0.7204





IPI00033486
W.GKELIETLWNLGDHELLHMYPGN#VSK.L
0.8142





IPI00033583
K.M*VAWSSSEN#MSEESVVLSFPR.F
0.9582





IPI00033583
K.TFVEVDEN#GTQAAAATGAVVSERSLR.S
0.5917





IPI00033798
K.SEVNEM*ENN#LTRR.R
0.7871





IPI00033946
A.EAYLGYPVTNAVITVPAYFN#DSQR.Q
0.7137





IPI00034003
K.SLTN#LSQEEQITKLLILK.L
0.9128





IPI00034277
K.ATFVKVVPTPNN#GSTELVALHR.N
0.5215





IPI00034283
M.ASTFIGN#STAIQELFK.R
0.933





IPI00034309
L.ENSGRSKN#FSYNLQSATQPKN#K.T
0.9674





IPI00034317
K.ALKSN#SSLTKGLRTMVEQNLMEK.L
0.575





IPI00034378
K.EGGVFTFGAGGYGQLGHN#STSHEINPRK.V
0.8953





IPI00034558
K.N#RSTASIQPTSDDLVSSAEC.S
0.8906





IPI00035165
K.AYIHAQAEN#CSHTAELVSWK.R
0.9374





IPI00035691
R.RDMGN#FSWGSE.C
0.7735





IPI00036554
M.FRM*LN#SSFEDDPFFSESILAHRENM*R.Q
0.6512





IPI00037319
K.SIMEN#ASAGVEHLLLGNK.C
0.7305





IPI00040730
K.EKPPNENCNN#NSPESSLLPR.A
0.9121





IPI00043469
R.EN#M*SLPSNLQLNDLTPDSR.A
0.7873





IPI00043550
M.PN#SSGLM*NRR.D
0.5396





IPI00043654
M.LASNHM*N#GSNGESPLA.-
0.6334





IPI00043705
R.YFNPVDQENALIAAIAN#WSELASMPVGR.S
0.7935





IPI00043716
K.KLRLPDTGLYN#MTDSGTGSCKN.S
0.6021





IPI00043716
K.N#GTVDGTSENTEDGLDRK.D
0.8943





IPI00043724
R.LSQNQNNYQISGN#LTVPWITGCSR.K
0.7428





IPI00043744
R.QGN#LSLPLNRELVEKVTNEYN#ESLLYSPEEPK.I
0.8137





IPI00043745
R.VKN#GSRVVSTALLSSYHKGI.A
0.92





IPI00043992
S.LKDN#SSCSVMSEEPEGR.S
0.5533





IPI00044283
R.TPRPASTHN#GSVDTEN#DSCLQQTH.-
0.9394





IPI00044315
-.MSAGN#GTPWGSAAGEEVWA.G
0.5879





IPI00044369
R.VN#LSFDFPFYGHFLR.E
0.9999





IPI00044369
R.SFTDLLLDDGQDN#NTQIEEDTDHNYYISR.I
1





IPI00044369
K.ITN#ISAVEM*TPL.P
0.6299





IPI00044456
R.FPGVM*EN#LTISAAHWLTAPAPRPRPR.R
0.544





IPI00044461
M.DRWN#ETVGLEWELERQLALMNSQFNRR.V
0.9317





IPI00044461
R.NFDKNGNMMDWWSN#FSTQHFR.E
0.5094





IPI00044529
R.KSIDEM*NNAWENLN#KTW.K
0.6338





IPI00044631
R.N#ITPLLLDMVVHNDR.L
0.5685





IPI00044650
K.SKSDLAVSN#ISPPSPDSK.S
0.8147





IPI00044683
G.DQLSN#LSNLLQQYK.T
0.633





IPI00044714
D.QYGKN#FSQ.S
0.6101





IPI00044726
R.N#NSKGYM*KLENKEDPM*DRLL.V
0.6866





IPI00045438
N.N#ATN#ESYVDTAAMEAER.L
0.5244





IPI00045486
R.TEDVMFISDN#ESFN#PSLWEEQR.K
0.975





IPI00045512
R.GSVIGNINDVEFGIAFLN#ATITDSPN.S
0.5086





IPI00045512
R.YLQINNADLGDTAN#YTCVASNIAGK.T
0.7655





IPI00045512
R.QLGN#GSLAIYGTVNEDAGDYTC.V
0.6632





IPI00045512
R.VRASSYSAN#GTIE.Y
0.5949





IPI00045856
R.KAVPM*APAPASPGSSN#DSSAR.S
0.5172





IPI00045914
S.SSREEN#WSFLDWDSR.F
0.8475





IPI00045914
K.N#DTAAVQLHEVSGNNVLAHRS.L
0.676





IPI00045928
K.SVGIFLGIFSGSFTMGAVTGVNAN#VTK.F
0.5903





IPI00045942
R.LKTEYN#ITLR.V
0.7003





IPI00045953
-.NN#FSTEIN#TTSILVGPLVSNLEITHTSN#LTR.V
0.5945





IPI00046047
R.HN#FTLAFSTAEKLADCAQLLD.V
0.5968





IPI00046260
K.VHTGTHM*WN#STPVXQGRQLSGDGPMTFLGGNPIK.F
0.6128





IPI00046366
K.GTENHLLAIVN#GTKGSR.W
0.5746





IPI00046793
K.QPSSPLAN#TTYNIFIM*DGK.T
0.9425





IPI00047137
K.MENGQQAADNILSAVPPGLIN#TSEAGIPAMSTND.L
0.7651





IPI00047437
R.KMFLFGTYLTKN#GSEIPSTM*QDAK.D
0.7148





IPI00047620
Y.HGN#GTHSESLEHHGYHGN#GTDR.E
0.8103





IPI00047620
R.GYHGN#GTHSESLEHR.G
0.6073





IPI00047620
R.VQN#TSLEHRGYHGSGTDGESSGRR.G
0.5039





IPI00049891
D.DRGSYTASIYQNYMGNSFSGYSHSPPLLQVN#R.S
0.6228





IPI00050342
-.MENRNN#M*TEFVLLGLTENPKM*QK.I
0.6014





IPI00050486
R.TN#FTLAELGICEPSPHRSGYCSDMGILHQ.G
0.7133





IPI00051170
K.YKELTLTRNQGICGKN#NSYI.E
0.7528





IPI00051926
N.QGN#FSVVGTVLAATQAEKAVANFDR.T
0.8374





IPI00053761
R.TQN#LSQPSTGIPSGEPGHSAGGAAGSRCTRSMFR.K
0.6953





IPI00054085
M.AN#RTDNTN#RTGDATVIKQEM*LTGQEM*PR.E
0.6436





IPI00054853
K.VTCDIDVN#SSLN#ISAVGKSTEK.E
0.6021





IPI00054874
K.HLFEDSQNKLGAEM*VIN#TSGKYGYK.S
0.6513





IPI00055218
R.SKGAIAPPEVTVPAQN#TSLGPK.K
0.9359





IPI00055405
K.KVLAPRVN#LTFR.K
0.5407





IPI00056324
K.YERGLIFYIN#HSLYENLDEELNEELAAK.V
0.5595





IPI00056499
K.WMLKTGMKNN#ATK.Q
0.9557





IPI00056506
R.IFVGGIDFKTN#ESDLR.K
0.541





IPI00056511
K.YNLEKDLKDKFVALTIDDICFSLNN#NSPNIR.Y
0.5393





IPI00056521
-.MHRLMGVN#STAAA.A
0.6667





IPI00057386
R.QMGGNTNTGAALN#FTLSLLQKAK.K
0.6167





IPI00058265
-.M*M*GHQN#HTF.S
0.9264





IPI00058344
K.SSN#LSEHQTLHTGQR.P
0.7346





IPI00058949
R.YGN#TTQNVPHNPR.R
0.596





IPI00059144
R.VVN#ESTVCLMNHERR.Q
0.7988





IPI00059279
R.ISESGIKKMCRNIFVLQQN#LTN#ITMSR.E
0.9055





IPI00059434
K.N#NSMNSNMGTGTFGPVGNGVHTGPESR.E
0.8325





IPI00059632
K.DHPVSCCLGLLLESLVPFIVNDN#ITNNFFR.F
0.8635





IPI00060143
R.GLNIALVN#GTTGAVLGQKAFDMYSGDVM*HLVK.F
0.7846





IPI00061178
R.GPPSRGGHMDDGGYSMNFN#MSSSRGPLPVK.R
0.589





IPI00061245
R.RLWQGLGN#FSVN#TSKGNTAKNGGLLLSTNM*K.W
0.6969





IPI00061280
F.SYATAAQN#NTVTDPK.N
0.8079





IPI00061780
R.VSTN#GSDDPEDAGAGENRR.V
0.7468





IPI00061876
K.KYLWEN#ETVGAQDDPL.A
0.8062





IPI00062751
K.ILPISLEPSSSTEPTQSN#LSVTAK.I
0.944





IPI00063106
K.N#DSDCGVFVLQY.C
0.6791





IPI00063106
K.FNVATQN#VSTLSSK.V
0.8109





IPI00063120
K.WIHTLTSLLQN#ISSYYTSLPR.F
0.5428





IPI00063217
R.N#DSIYEASSLYGISAMDGVPFTLHPR.F
0.5123





IPI00063408
M.LPN#PSHLEAVNPVAVGKTRGR.Q
0.5408





IPI00063523
R.ESEELECNTGSN#ITNMHQDK.E
0.6076





IPI00063523
K.QN#KSPDTEKINYAGPLEETGISDITKKEK.E
0.8635





IPI00063523
K.AN#LTDM*ESGSSNAMNMNVQHER.E
0.7769





IPI00063590
K.VSN#LSLFGGLPANHVLVNQYLP.G
0.8335





IPI00063780
-.MVDLLSM*SQN#ISPYKNPM*R.F
0.6475





IPI00063800
R.SPPGEN#PSPQGELPSPESSRRL.F
0.8459





IPI00064174
A.GFGNN#FTTVDN#K.S
0.5261





IPI00064201
K.SSVTPAIISAALQQVVHN#K.S
0.7279





IPI00064219
K.N#VTLEEDGTRAVRAAGYAHGLVFSTK.E
0.6342





IPI00064667
R.LVPHM*N#VSAVEK.Q
0.9997





IPI00064667
K.AIHLDLEEYRN#SSR.V
0.9958





IPI00064743
K.AQNGIAIMVYTN#SSNTLYWELNQAVR.T
0.9689





IPI00065253
K.ADN#HTAHRIADQTALRVPSQAESSIFSQATN.G
0.5338





IPI00065348
K.INLLN#LTFCLFVWLTFNLPFLK.N
0.8832





IPI00065383
K.YITVN#ISYVNIF.R
0.9461





IPI00065390
K.CPECDQN#FSDHSYLVLHQK.I
0.5167





IPI00065457
K.LEVEDLDENFLN#SSYQTVFK.T
0.9197





IPI00065553
R.VLTN#M*THEDDVPIN#CTMVLLHIVSK.C
0.542





IPI00066511
K.VSSPLENEKLKSM*TIN#FSSLNR.K
0.5623





IPI00066511
R.SYSVSGVCQPAIPN#SSLHIPHN.A
0.7931





IPI00067421
-.MLTGVLLAN#GTLN#ASILNSLYNENLVK.E
0.6772





IPI00067744
F.FLTTPAIIM*NTIDMYN#VTRPIEK.L
0.9394





IPI00068174
K.GKRMLSEYLSPN#LSLR.A
0.9293





IPI00069084
D.SDMDPN#SSGEGVNSVSSS.I
0.7917





IPI00069084
D.KAKKEHERSN#ASPAIFPEYQLWEDHWIR.C
0.9279





IPI00069126
F.APFLN#NSPQQNPAAQIPAR.Q
0.5403





IPI00069232
Q.IVIKMFQN#ISNIIKSGK.M
0.6518





IPI00069817
K.N#ASMNTQHGTATEVAVETTTPK.Q
0.9321





IPI00070643
R.EYNLN#FSGSSTIQEVK.R
0.7141





IPI00071171
R.VGECSCQVSLMLQN#SSAR.A
0.9243





IPI00071509
V.VRSGASLLSN#M*SR.H
0.7027





IPI00072656
K.LIKTDESVVDRAKAN#ASLWEAR.L
0.6179





IPI00073264
V.SWEILSN#LSFLVTIQR.A
0.5504





IPI00073289
N.DNEGIGGN#FSGLGGFGGSR.G
0.5598





IPI00073577
R.RLSIGLDN#GTISEFILSEDYN.K
0.5822





IPI00073730
-.MNGGN#ESSGADRA.G
0.6388





IPI00075272
M.N#GTSSQPKKEEYGS.-
0.786





IPI00080897
N.KM*GQLGLGN#QTDAVPSPAQIMYNGQPITK.M
0.9485





IPI00081089
K.LKLEAELGNM*QGLVSGM*QN#MSIHTK.T
0.8603





IPI00083235
G.KVFN#DSGN#LSNHK.R
0.8681





IPI00083281
K.VTRDALTEPLAIVEGYNSYFSFSRN#R.S
0.8071





IPI00083708
K.SNEVVAVPTN#GTVNNVAQEPVNTL.G
0.5435





IPI00084434
R.AQIFANTVDN#SSIALQTDNTHLAADDLR.V
0.9349





IPI00084684
K.KSFACSSCN#YTFAKKEQF.D
0.8025





IPI00085314
M.ESLAISN#ATGLSADGGAKR.Q
0.7372





IPI00090720
K.NGQSLGDLDGIPIAVKDN#FSTSGIETTCASNMLK.G
0.9304





IPI00090972
R.VKAISDSDGVSYPWYGN#TTETV.T
0.9788





IPI00091258
R.FAN#GSAVIQSGDTAVMATAVSK.T
0.5183





IPI00091258
N.GNSVALSLSDILWNGPVGTVXIGMTDGECVVN#PTRK.E
0.6853





IPI00092641
K.FRNPPLVN#GSLALAFQGTAPPPNWRR.P
0.6463





IPI00097839
V.YN#GSVDEGSKPGTYVMTVTANDADDSTTANGM*VR.Y
0.691





IPI00098769
R.RVYDFVGLLVSPEMEQFALN#MT.S
0.7711





IPI00098827
R.FIIVSAFDHFASVHSVSAEGTVVSN#LSS.-
0.721





IPI00099004
K.YRETKSQESEELVVTGGGGLRRFKTIELN#ST.I
0.708





IPI00099111
K.MSGGSTMSSGGGNTN#NSNSKK.K
0.5752





IPI00099433
V.TQQMSN#ISGSCSM*LQQTSISSPPTCSVK.S
0.6188





IPI00099433
R.RRIN#SSVTTETISETTEVLNEPFD.N
0.7223





IPI00099650
K.RRKPGSHTHSASEDN#TTNNVR.E
0.6515





IPI00099688
R.LGKPSVM*TPTEGLDTGEMSN#STSSLK.R
0.9425





IPI00099863
E.YDTIPHTN#RTILK.E
0.9414





IPI00099890
L.GLN#LSEGDGEEVYHF.-
0.616





IPI00100099
K.YSTTTAQN#SSSSSSQSK.M
0.6061





IPI00100099
R.GVN#GSPRISVTVGNIPKNSVSS.S
0.7602





IPI00100151
R.M*QN#NSSPSISPN#TSFTSDGSPSPLGGIKR.K
0.555





IPI00100291
K.EVTQATQPEAIPQGTN#ITEEKPGR.K
0.9988





IPI00100402
K.THMNVLGVLGPLDPQWLVENN#ITGC.P
0.6885





IPI00100453
K.KSSLDSN#SSEM*AIMMGADAK.I
0.6373





IPI00100715
R.SSSGHLFTLPGATPGGDPNSN#NSNNK.L
0.6021





IPI00100984
C.QAEAAAAAN#GTGGEEDDGPAAELLEK.L
0.9125





IPI00101172
R.WEALGNTLSSQPN#LTVSWDPR.I
0.8018





IPI00101261
R.GM*GPM*GTPIMPSPADSTN#SSDNIYTM*TGGR.S
0.5278





IPI00101462
K.THTN#ISESHPN#ATFSAVGEASICEDDWNSGER.F
1





IPI00101462
R.GLTFQQN#ASSM*CVPDQDTAIR.V
1





IPI00101462
K.N#NSDISSTR.G
1





IPI00101952
R.NPVTSTNVLGMMTAILGVFLYN#KTK.Y
0.9204





IPI00102329
K.DDWIRPALLSGPVAANVLN#FSDHHVIPM*PLLK.G
0.7592





IPI00102378
K.LEFLPEEIGQMQKLRVLN#LSDNRL.K
0.5894





IPI00102543
K.MNCNNRN#VSSLADLKPK.L
0.7013





IPI00102677
R.LEEFEGGGGGEGN#VSQVGRVWPSSYR.A
0.9512





IPI00102678
R.LVSN#DSFISIQPSLSSCGQDLPR.D
0.7196





IPI00102752
R.SKKLGGSGGSN#GSSSGKTDSGGGSRR.S
0.6252





IPI00102829
T.DGTTITESSN#LSEIESR.L
0.6275





IPI00102856
M.MNYGQSMSGGNGQAAN#QTLSPQMWK.-
0.5956





IPI00103026
F.SYPNGLSEN#TSVVEKLK.H
0.7284





IPI00103055
K.HAAFFADAEGYFAACTTDTTMN#SSLSEPLYVPVK.F
0.8229





IPI00103277
K.N#GTAVCATNR.R
0.9995





IPI00103277
K.LSDLSIN#STECLHVHCR.G
1





IPI00103277
K.FLNN#GTCTAEGK.F
1





IPI00103288
R.ASVVWM*AYM*N#ISFHVGNHVLSELGETGVFGRSSTLK.R
0.6024





IPI00103335
E.DGLYGAPEPN#GSWTGM*VGELINR.K
0.6009





IPI00103380
D.DSGATLLSAN#QTLRRLHNRR.T
0.6553





IPI00103419
K.MEQKAKQNQVASPQPPHPGEITNAHN#SSCISNK.F
0.5721





IPI00103451
K.DRCNVEKVPSNSQLEIEGN#SSGR.Q
0.5878





IPI00103487
K.KLAEILVN#TSSENWIR.N
0.7167





IPI00103552
K.VPTGTITEVSSTGVN#SSSK.I
0.8545





IPI00103552
T.QHFYLN#FTITNLPYSQDKAQPGTTNYQRNKR.N
0.9423





IPI00103552
K.FN#TTEXVLQGLLXPX.F
0.7668





IPI00103552
R.KTNELPSDSSSSSDLIN#TSIAS.S
0.7492





IPI00103552
K.N#TSVGPLYSGSRLT.L
0.7448





IPI00103552
M.AAGPLLVPFTLN#FTITNLQYGEDMGHPGSRK.F
0.5561





IPI00103552
R.EPGTSSTSN#LSSTSHER.L
0.5329





IPI00103577
-.MERAPPDGPLN#ASGALAGDAAAAGGAR.G
0.6536





IPI00103606
V.QVCSLPACGGNHQN#STVR.A
0.5192





IPI00103647
R.MIVEIHLEEYNN#ISKKPM*NLVLFR.F
0.5834





IPI00103723
K.GEISEKAKLEN#STQAEEGFDVPDCK.K
0.7861





IPI00103752
K.RRTTN#RTIPSVDDFQNYLRVAFQEVNSGCTGK.T
0.5825





IPI00103755
K.M*PYIQN#LSSLPTRTELR.T
0.5618





IPI00103772
P.MQNFM*AGTAGVYQTQGLVGSSN#GSSHKK.S
0.7419





IPI00103871
R.IQLEN#VTLLNPDPAEGPKPR.P
0.9983





IPI00103879
R.TLQQLYEAYASKSN#NTAYLIYNDGVPK.P
0.9018





IPI00104074
R.WGHSECGHKEDAAVN#CTDISVQK.T
0.9993





IPI00105353
W.LNAQFDGNN#ETIK.W
0.7496





IPI00105532
R.CTLHPN#DSLAMEGPLSRVKSLKKS.L
0.7472





IPI00106786
R.VGVDPDQDPPPNN#DSFQVLQGDSPDSAR.G
0.5136





IPI00106795
V.KVVMDIPYELWN#ETSAEVADLK.K
0.6752





IPI00107463
K.LN#PTPGSNAISDAYLN#ASETTTLSPS.G
0.7419





IPI00107463
K.WKNIETFTCDTQN#ITYR.F
0.7143





IPI00107617
K.HSSGSSN#TSTANRR.A
0.6024





IPI00107642
R.KFKTNVLPFRQN#DSSSHCQKSGSPISSEERR.R
0.6554





IPI00107728
K.VDSN#DSLYGGDSKFL.A
0.6038





IPI00107838
R.ASSPN#STVSN#TSTEGFGGIM*SFASSLYR.N
0.6865





IPI00140246
M.DTRN#LSLAHNR.I
0.8804





IPI00140489
I.SNPLHCN#MTMTPGTCR.V
0.5482





IPI00141118
M.N#NSCLTNAVHLNN#VSVVSPVNVHINTR.T
0.7235





IPI00141559
M.LFLSMN#LTISAGPASTLPTATPAAGELTMR.S
0.7546





IPI00142487
R.RSLN#SSSSSPPSSPTM*MPR.L
0.6373





IPI00142538
M.KNSCNVLHPQSPN#NSNR.Q
0.8927





IPI00142768
S.ISHDNNN#ISSTSELGTDLANTK.V
0.8639





IPI00142919
R.ILVN#LSMVENKLVELEHTLLSK.G
0.5





IPI00144289
R.VRRTDDTPVVLVGN#KSDLKQLRQVTK.E
0.5634





IPI00146438
G.IKVKN#HSGGGMSLTHNKNFRK.L
0.6838





IPI00147583
M.LGSEM*XGQN#VSNPAPSPSLSGVSWPDNVPK.I
0.6936





IPI00147583
R.VWQN#LSEPIR.P
0.5571





IPI00147633
R.KN#ASALYEKIR.G
0.5294





IPI00147702
K.HTGSGILSMANAGPNTN#GSQFFICTAK.T
0.6152





IPI00148050
K.GACN#GSVDCEDTTNHNILQAR.D
0.7687





IPI00149695
K.QVGEKAM*N#ASAN#ITSDGVEVLGKMVR.S
0.9947





IPI00151777
M.SSHFYINDVN#FTRKMLLM*FFEVSAHE.S
0.6298





IPI00151888
M.N#GSGQSPSVLKGILHEAAMQYPK.Q
0.9394





IPI00151982
M.KENPAKEQLWALEQDN#CSLANLVCK.V
0.6234





IPI00152048
M.VVLCASTLPDWRNAAADN#RSLDDR.S
0.7416





IPI00152075
R.FVRLGTASMLTSPDGPFIN#LSR.L
0.911





IPI00152101
K.KDGEN#VSM*KDPPDLLDRQK.C
0.6088





IPI00152101
K.N#ETVSSN#SSN#NTGN.S
0.7436





IPI00152101
K.VLQAMGYPTGFDADIECMSSDEKSDN#ESKN#ET.V
0.7046





IPI00152254
R.QRN#ASRDQ.V
0.6481





IPI00152295
K.VRRPSPN#RSKLSNVARK.A
0.7394





IPI00152316
M.TWSFGWN#SSLPVYYIR.E
0.5125





IPI00152391
K.VKFGMN#VTSSEK.V
0.5162





IPI00152410
K.LKTN#VTFPLDILLLSFK.A
0.6682





IPI00152418
K.TLSTKTPSAAQNPMMTN#ASATQATLTAQK.F
0.5389





IPI00152427
R.CDKAFN#QSAN#LTK.H
0.9383





IPI00152440
K.EKDSN#SSSGSFNGEQEPIIGFQPMDSTR.A
0.828





IPI00152468
L.YN#DSTYNQQLIIPSIGLPLK.T
0.9822





IPI00152474
K.N#TSNKEISRDTLLTIENNP.C
0.7336





IPI00152510
R.SRATIFEIN#ASSRDLCSQVMRAKR.Q
0.6619





IPI00152513
R.GNIYPGN#DTFDIDPEIE.T
0.9361





IPI00152524
M.NRRNILVMKHN#YSQDAADACDIDEIEEVPTTSHR.L
0.9451





IPI00152527
A.IYFENLQN#SSNDLGDHSMKER.D
0.8129





IPI00152540
K.FDILMTSNEIN#ATGHQQTLLVPSEDGA.T
0.6607





IPI00152540
M.EAVQKIN#YTVPQSGTFK.I
0.7268





IPI00152542
R.M*DDVPSHSKALSDGN#GSSGIEWS.N
0.5941





IPI00152542
L.IHALATN#SSSELFRLAAHPLNNR.M
0.791





IPI00152581
Q.RN#ISLQLM*SNM*N#ISNKIR.N
0.9822





IPI00152602
K.MFFETNENN#DTTYQNLWDA.F
0.597





IPI00152602
K.N#LTQSHSTTWKLNNLLLNDYWVHNEMK.A
0.9032





IPI00152615
L.KLGVVPVYYGSPSITDWLPSN#KSAILVSEFSHPR.E
0.756





IPI00152627
A.HN#MSGPN#SSSEWSIEGRR.L
0.5616





IPI00152627
K.ALATSMLTGEAGSLPSTHMVVAGMAN#STPQ.Q
0.5357





IPI00152642
R.VQPAQN#HSSLSN#VSQAVASTTPLPPPK.P
0.5464





IPI00152647
K.N#LTAVKSGGTSDSFVKGYLLP.D
0.7705





IPI00152661
M.DFGDSSGVEM*RLHN#M*SEAMAVTAYHQYSK.G
0.627





IPI00152696
K.LPHN#GSTGSTPLLR.N
0.7825





IPI00152720
P.FPGN#M*SSMTPSSPGM*SQQGGPGMGPPMPTVNR.K
0.741





IPI00152788
L.VISGLSAAEGGN#TSDTQSSSSVNIVMGPSAR.A
0.7899





IPI00152797
K.DNKYTLN#QTSAVFDSIPEVVHYYSNEK.L
0.7721





IPI00152818
K.LSDSN#QTLKVIGEFILER.N
0.7604





IPI00152849
K.N#PTTEETVLTK.T
0.8801





IPI00152944
R.LM*AFGCVSGSVQVYTIDN#STGAMLLSHK.L
0.837





IPI00152985
K.M*IGLEDFVADN#YSK.I
0.9678





IPI00154162
K.ELFGDDSEDEGASHHSGSDN#HSER.S
0.9015





IPI00154451
K.SGN#YTVLQVVEALGSSLENPEPRTR.A
0.7456





IPI00154528
M.RGIETVLLIKN#NSVARAVM*QSQK.P
0.963





IPI00154588
R.IAQKGGAEAM*LVVN#NSVLFPPSGN#R.S
0.5979





IPI00154813
K.EANIN#STSISDDNSASLR.C
0.5682





IPI00155227
K.AKAGFSEWLAVDGLGSPSN#NSKE.D
0.5323





IPI00155647
M.VDAASYAAN#LTDSAEAPKGSPGSWWKK.E
0.7446





IPI00155729
R.LVVGDFSDYN#NSYVGAFADAR.S
0.5716





IPI00156651
R.YQQLAVALDSSYVTNKQLN#ITIEK.L
0.6814





IPI00157364
K.NYEDEPNNYRTMHGRAVN#GSQLGK.D
0.687





IPI00157589
R.KN#ITNDIR.T
0.6462





IPI00157790
R.YIRTLMSSGQMAPSSSN#K.S
0.5034





IPI00157790
R.QN#SSSAQGSSSNSGGGSGIPQP.P
0.6873





IPI00158615
T.PKGN#SSNGNSGSNSNK.A
0.7669





IPI00158615
K.LYDQCHDTLVQFGGFLASN#LSTEDY.I
0.589





IPI00159049
S.PARQN#VSSASNPEN#DSSHVR.I
0.6941





IPI00159322
K.GNKNGDN#NSNHNGEGNGQSGHS.A
0.5747





IPI00160130
R.FQFCGRN#ASAVPVFYSSM*STAMVIFKSGVVNR.N
0.794





IPI00160130
K.LCSSVN#VSNEIK.S
0.7188





IPI00160131
K.ISNVALDSMHWQN#DSVQ.I
0.8062





IPI00160131
V.ERPSSLLSLN#TSNK.G
0.6142





IPI00160265
R.N#ITIMASGNTGGEK.D
0.5234





IPI00160290
R.TNSRLSHMPPLPLN#PSSN#PTS.L
0.6013





IPI00160316
N.#LTQNLMQN#LTQSLSQKENR.E
0.7429





IPI00160348
T.N#ASPEKTTYDSAEEENKENLYAGK.N
0.5938





IPI00160395
K.AIIN#STVTPN.M
0.5471





IPI00160432
K.VDPETNKN#ITRGQSLDNLIK.V
0.5003





IPI00160566
K.AFSQN#ISLVQHLR.T
0.7411





IPI00160901
K.SSEFASIPAN#SSRPLSN#ISKSGR.M
0.7207





IPI00162732
R.EQQN#DTSSELQNR.E
0.5727





IPI00163147
R.DNGPDGMEPECVIESNWNEIVDSFDDMN#LSESLLR.D
0.8212





IPI00163207
R.LYHFLLGAWSLN#ATELDPCPLSPELLGLTK.E
1





IPI00163207
R.GFGVAIVGN#YTAALPTEAALR.T
1





IPI00163207
R.LEPVHLQLQCMSQEQLAQVAAN#ATK.E
1





IPI00163328
T.PVPGYMN#NTVNTM*R.L
0.5923





IPI00163446
R.EVN#TSGFAPARPPPQPGSTTFWAWSVLR.V
1





IPI00163446
R.TLLN#ASR.S
0.9762





IPI00163504
K.VLEAN#ATPLDRGDGVLRTCALR.P
0.9855





IPI00163507
R.TRSTSSAGSN#NSAEGAGLTDNGCR.R
0.7505





IPI00163644
K.GILYGTMTLELGGTVN#ITCQK.T
0.5468





IPI00163749
R.KQAGPLLSGDPHLLPPAASPKGASVSINVN#TSLEDMRS.N
0.5218





IPI00163782
K.RPLEDGDQPDAKKVAPQN#DSFGTQLPPMH.Q
0.9462





IPI00163866
K.QKN#SSDQEGNN#ISSSSGHRVR.L
0.6176





IPI00163904
K.NTNQN#SSAHPPHLNMDDTVN#QSNIELKNVNR.N
0.7566





IPI00164104
I.QIRN#VSQLPATWRM*K.E
0.7807





IPI00164104
F.TQNLLLEYTN#QTTQAR.P
0.5026





IPI00164246
R.DGEQSPN#VSLM*QRMSDM*LSR.W
0.7974





IPI00164345
R.KQSESSFISGDIN#STSTLNQGLTSHGLR.A
0.7627





IPI00164356
K.SFLNAFSEEIN#NSMIILSLSPTTFK.N
0.5919





IPI00164550
M.DGN#DSDYDPK.K
0.5836





IPI00164623
K.TVLTPATNHMGN#VTFTIPANR.E
1





IPI00164623
K.HYLMWGLSSDFWGEKPN#LSYIIGK.D
1





IPI00164623
K.VVPEGIRM*N#K.T
0.8373





IPI00164755
K.GEPGAPGEN#GTPGQTGAR.G
0.8206





IPI00164831
K.RYEDGTISSN#ATHVEHPLCPPK.P
0.6156





IPI00164930
R.HIANSIRTHGTGIMN#TTKWAFTAWRGG.P
0.6579





IPI00164998
N.#KTTSLGQMENNNLDELN#KSKIIVKKK.P
0.6713





IPI00165024
M.IQNTFN#FSLK.Q
0.9781





IPI00165024
K.SKEQN#VSDDPESTGFLYPYNDLLVWAVLM*KR.Q
0.5517





IPI00165064
R.RYTN#SSADNEECRV.P
0.6205





IPI00165171
R.VGGFGFVATPSPAPGVN#ESPM*MTWGEVENTPLR.V
0.5058





IPI00165210
K.LAKIRDNLAISLDN#QSSPSPPVL.I
0.5037





IPI00165246
R.FM*GPASGM*N#M*SGMGGLGSLGDVSK.N
0.8641





IPI00165250
L.GNTKDFIISFDLKFLTN#GSVSVVLETTEK.N
0.6943





IPI00165319
K.TSIAQSVLQSLPSSQWSVLVVN#MSAQ.T
0.869





IPI00165357
K.CSVALLN#ETESVLSYLDKE.D
0.9629





IPI00165438
R.GPECSQN#YTTPSGVIK.S
0.9998





IPI00165598
R.N#PSQLPALSSSPAHSGM*MGINSYGSQLGVSI.S
0.6384





IPI00165934
R.EPAQGLFGTVTVQFIVTEVN#SSN#ESK.D
0.6157





IPI00165934
M.TSWISPAVN#NSDFWTYRK.N
0.6995





IPI00165934
F.QLM*N#ITAGTSHVMISR.R
0.5155





IPI00165934
N.DQLSEIEEFFYIN#LTSVEIRGLQK.F
0.5067





IPI00165979
V.KPYVN#GTSPVYSR.E
0.9069





IPI00165981
R.HDQEN#DTR.W
0.6783





IPI00166010
K.DVPPSIN#TTNIDTLLVAT.D
0.5707





IPI00166010
M.LLN#GTPFAFVIDLAALASRR.E
0.513





IPI00166010
R.N#LTAGMAMSTCR.E
0.5019





IPI00166031
K.TRPQN#GSM*ILYNRK.K
0.8987





IPI00166078
K.HPENNQKSENNQKLLTGAN#SSR.F
0.7187





IPI00166078
L.RTTNGRLNIDNLN#LSFRK.E
0.604





IPI00166086
L.NRIPGVPGSM*PN#ASWTGNLR.A
0.9053





IPI00166121
K.LVGLN#LSPPMSPVQLPLR.A
0.7296





IPI00166145
R.LLN#LSFCGGISDAGLLHLSHM*GSLRSLNLR.S
0.8326





IPI00166161
R.QKEN#DTQIFN#DSAVDN#HSK.C
0.816





IPI00166161
K.SIEN#DSDEVEERAENFPR.T
0.8327





IPI00166201
M.PTFCIPENHCGTHAPVWLN#GSHPLEGDGIVQR.Q
0.7812





IPI00166283
R.RGAIKHQVN#FSSGGVAPLGGSWHR.L
0.8876





IPI00166301
S.PQRSSM*NN#GSPTALSGSKTNSPK.N
0.6801





IPI00166323
K.WLPN#STTTCSLSPDSAI.L
0.7488





IPI00166392
R.FQLLN#FSSSELK.V
0.9999





IPI00166500
S.VN#GSGALGSTGGGGPVGSM*ENGK.P
0.6749





IPI00166533
R.FLNN#DSSGAEANSEK.Y
0.772





IPI00166652
K.TDEKLN#VSDENTASCPLSPIK.M
0.8775





IPI00166705
R.GM*YLVFDGSVDLHYN#CSAKCK.S
0.9101





IPI00166713
K.AYAGRKQHYIAGN#CSSNGR.G
0.5749





IPI00166729
R.FGCEIENN#R.S
0.9998





IPI00166729
K.DIVEYYN#DSN#GSHVLQGR.F
1





IPI00166729
R.GDVLHNGN#GTYQSW.V
0.8111





IPI00166842
S.TSGLLN#STWPLPSATQR.C
0.787





IPI00166861
K.VIQM*DVALFEMN#QSDSK.E
0.5371





IPI00166863
K.FEALKEENMDLNNM*N#QSLTL.E
0.9357





IPI00166930
R.LEDLEVTGSSFLN#LSTNIFSN#LTSLGK.L
1





IPI00166930
K.LYLGSNN#LTALHPALFQN#LSK.L
1





IPI00166930
K.LGSLQELFLDSNN#ISELPPQVFSQLFCLER.L
0.9989





IPI00166930
R.AFGSNPN#LTK.V
0.9987





IPI00166930
R.WLNVQLSPWQGSLGLQYN#ASQEWDLR.S
0.9721





IPI00166930
R.NAITHLPLSIFASLGN#LTFLSLQWNM*LR.V
0.7729





IPI00166972
M.SGREETEKVN#TSPSVNTKTTTESK.A
0.6357





IPI00166979
K.WN#FSSGFIEAVFK.H
0.5225





IPI00167009
M.KN#ATSSKQLPLEPESPSGQVGPRPAP.P
0.8009





IPI00167036
M.RKLGHLNN#FTK.L
0.7118





IPI00167074
K.RSVLPPDGN#GSPVLPDKR.N
0.9653





IPI00167103
R.SAPSGGGASFN#LSLTEEHSGN#YSCEANNGLGAQR.S
0.6969





IPI00167131
R.NLDPEN#GSGMALQPLQAAPEPGAQGQR.E
0.7197





IPI00167172
R.KLFQEILN#TSR.E
0.657





IPI00167196
K.HLSDYCIGPN#ASINVIM*QPLEK.M
0.5303





IPI00167238
K.EIKGIQIGREEVN#LSLLADDMILYLENPVVSAQR.P
0.8465





IPI00167254
D.PLTFNFISSLKAICTEIAN#CSLK.V
0.703





IPI00167513
R.DCYYDN#STTCPKCARLSLR.K
0.5354





IPI00167549
T.QIIN#GSVDVDTEDRQK.R
0.5016





IPI00167560
K.N#ESNLGDLLLGFLK.Y
0.5532





IPI00167574
M.LFNVEN#GTPASR.E
0.9511





IPI00167574
V.PTVFAFQDPTQQVRENTDPASERGN#ASSSQK.E
0.8038





IPI00167706
G.CNHN#STQILVNCLR.A
0.5296





IPI00167778
M.QTTDLEQTSPPVNQAPN#QTKLEVK.A
0.8726





IPI00167801
K.M*PPGIN#SSQSLPVDNHE.K
0.7964





IPI00167830
R.TSNGQPVKTAGEITQHN#VTELLR.D
0.8741





IPI00167841
R.VFTEEAKDSLN#TSEN#DSEHQ.T
0.944





IPI00167841
M.LISVESPN#LTTPITSN#PTDTR.K
0.667





IPI00167860
R.TSHGEPKSAVPFNQYLPN#KSN#QTAYVPAPLRK.K
0.8829





IPI00167867
D.SSPEHN#LTKIANGVPNSK.G
0.7867





IPI00167908
Q.QTTN#TTSTQMTNIGVYVSN#M*TDK.L
0.7188





IPI00167910
R.NINGLFLPPSSN#ITLQK.E
0.6072





IPI00167941
K.ILQPN#TTDEFVIPLDPR.W
0.528





IPI00168043
M.GTPSQTSQDTSLETGQGYEDEQDGWN#SSSKTTR.V
0.8964





IPI00168056
K.SYRN#SSYENARENSQMN#ESAPGTYVVQNPH.S
0.8354





IPI00168060
M.KDFLTDRSN#QSHLVGVPKPGVPQTPVNK.I
0.5068





IPI00168154
M.RANGN#TTSNKNSAAM*DAEIVLR.S
0.9437





IPI00168255
R.FGSGAAGGSGSSN#SSGDALVTRISILLR.D
0.6684





IPI00168280
R.SLTYLSIN#CTSISLNMFSLLHDILHE.P
0.8199





IPI00168352
M.TN#GTLEPAAEWSVLLGVHSQDGPLDGAHTR.A
0.575





IPI00168406
K.N#NSYSLAFLAGKLNSKVERS.Q
0.8794





IPI00168431
K.DYPSN#TTSSTSNSGN#ETSGSSTIGETSKKK.R
0.924





IPI00168442
R.HM*DM*LTAADRLPTQAPLSTSQSVSGKN#M*TASQGP.C
0.6251





IPI00168475
P.DRN#CSWALGPPGAALELTFR.L
0.5633





IPI00168525
K.NKAQN#ITAPESEAICWQ.L
0.7609





IPI00168526
R.KATM*AGGLANLQDLEN#TTPAQPK.N
0.5775





IPI00168526
R.SPTQGYRVTPDAVHSVGGN#SSQSSS.P
0.7164





IPI00168627
R.GRDGGEGCSWM*FQPM*N#NSKM*R.V
0.9536





IPI00168627
K.VDTNTENSVNTMN#R.S
0.961





IPI00168632
K.QHLQIN#WTGLTNLLDAPGINDVSDS.L
0.9894





IPI00168728
R.EEQFN#STFR.V
1





IPI00168745
K.M*DFLLFN#YSAPSYLRLL.-
0.6143





IPI00168759
M.N#ISLAFFLYDLLSLM*DR.G
0.7668





IPI00168839
E.ALAAMQDPEVMVAFQDVAQNPAN#MSK.Y
0.9109





IPI00168868
R.ATPTPSPANAHVN#GSADAPENALHLAEAGGLCGESR.A
0.8598





IPI00168931
K.VANN#VTEFIFLGLSQDSGM*R.W
0.8801





IPI00168954
M.GDVN#QSVASDFI.L
0.7879





IPI00169020
-.MTLVSFFSFLSKPLIMLLSN#SSWR.L
0.8434





IPI00169030
S.N#LSFIDVCYISSTVPK.M
0.7937





IPI00169113
R.YPIIM*NKVVYVLLTSVSWLSGGIN#STVQTSLAM*R.W
0.718





IPI00169156
-.MSFLN#GTSLTPASFILNGIPGLE.D
0.8803





IPI00169179
R.CPQCDCITLQN#VSAGLNHHQTF.S
0.7436





IPI00169288
R.AN#NSDFGLVAAVFTNDINK.A
0.5559





IPI00169303
R.FRTVN#STSWMEVNFAKNRK.D
0.7314





IPI00169325
K.FN#KSLGHGLINIKK.R
0.8613





IPI00169385
K.GNCEDYLMISCN#NSDGIENR.N
0.8012





IPI00169401
K.ERPISMINEASNYN#VTSDYAVHPM*SPVGR.T
0.9183





IPI00169420
R.GVEGPQGSPRPPAPIQQLN#RS.S
0.5758





IPI00169440
V.FNILFVTSEN#GSR.N
0.8134





IPI00170428
E.DDFQHSSN#STYR.T
0.7862





IPI00170549
K.ERIINYAN#SSDPTSGVSKRK.S
0.9595





IPI00170594
K.SM*ADVLGDGGN#SSLTISEGP.I
0.8441





IPI00170605
R.WQALVQVQPSVDPTN#ATGLDGR.E
0.7801





IPI00170667
K.ASPSENNAGGGSPSSGSGGN#PTN#TS.G
0.5378





IPI00170675
M.RKLHLGSSLDSSN#ASVSSSLSLASQK.D
0.9167





IPI00170730
R.SSSFGSVSTSSN#SSK.G
0.6301





IPI00170766
K.DPRNLLAN#QTLVYSQDLGEMTK.L
0.6412





IPI00170778
K.TGTDSN#STESSETSTG.S
0.9363





IPI00171002
K.RTIYLN#ITNTLN#ITNNNYYSVE.V
0.8805





IPI00171015
K.AGHQVMVFVHARN#ATVRTAMSLIER.A
0.619





IPI00171052
R.VKVQDLVLEPTQN#ITTKGVSVRRKR.Q
0.9171





IPI00171111
M.NSNLPAEN#LTIAVN#MTK.T
0.6397





IPI00171111
W.EDTQN#ASQNKIKIVGLGLLR.V
0.7109





IPI00171134
K.RRKELGAMAFSTTAIN#FSTVN#SSAGFR.S
0.7412





IPI00171134
K.KLCGENDRLN#HTYSQLL.K
0.6624





IPI00171134
M.NQNAQLLIQQSSLENEN#ESVIKER.E
0.5445





IPI00171176
K.N#FSSLHTVFCATGGGAYK.F
0.6267





IPI00171183
C.LN#LSN#TTITN#R.T
0.8748





IPI00171206
R.YM*IYEFWEN#SSVWNSHLQTN#YS.K
0.533





IPI00171211
M.ASFLKN#VSATVSIN#GSGISGNTAINYK.H
0.6028





IPI00171312
K.N#SSEFPLFSYNNGVVMTSCR.E
0.8799





IPI00171509
K.KRQEENSQN#SSEKVM*FQSTHILPDEEKMVK.E
0.5659





IPI00171537
R.NMYTVQN#NSGPYFNPR.S
0.555





IPI00171636
K.AKAVALDSDN#ISLK.S
0.5793





IPI00171636
R.QN#SSDSISSLNSITSHSSIGSSKDADAK.K
0.7472





IPI00171636
K.QKSLTN#LSFLTDSEKK.L
0.7166





IPI00171678
R.LEVHYHNPLVIEGRN#DSSGIR.L
0.999





IPI00171678
R.SLEAIN#GSGLQM*GLQR.V
1





IPI00171678
K.ALYSFAPISMHCN#K.S
0.9956





IPI00171716
K.MNM*NVMEEAIGYFEQQLAM*LQQLSGN#ESVLDR.G
0.5175





IPI00171768
R.FVEGTNIN#RSLLALGNVINALADSK.R
0.5511





IPI00171791
S.LSNIVRN#LTPAPLTSTPPLRS.-
0.7344





IPI00171921
R.GHN#LSRDELR.G
0.6891





IPI00171928
R.LFLGN#YTGNVGNDALQYHN#NTAFSTK.D
0.5025





IPI00172422
K.YKPLN#TTPN#ATK.E
0.7977





IPI00172530
P.DFRN#MTGLVDLTLSRNAITRIGAR.A
0.5919





IPI00172636
K.LKGAILTTMLATRN#FSAAK.S
0.8405





IPI00173346
M.ASYLETMN#ITLKQQLVKVYEK.Y
0.5949





IPI00173359
K.LLKEQAHN#LTIEM*K.N
0.7444





IPI00173359
M.MSNQYVPVKTHEEVKMTLN#DTLAKTNR.E
0.5601





IPI00173448
M.N#NSLDYLAYPVIVSNHRQSTTFR.K
0.9327





IPI00173492
G.DYEPIDATGFIN#ISSLRLK.E
0.579





IPI00173844
K.EMEEFVQSSGENGVVVFSLGSMVSN#M*TAER.A
0.778





IPI00173934
K.HTGPGILSM*ANAGLNTN#GSQFFICTAK.T
0.6632





IPI00173934
K.GSCFHSIIPGFMCQGGDFTLLN#GTGGK.S
0.9033





IPI00174153
R.LGTFTTQN#ASAPRNPETPGSPVPPSGR.P
0.5624





IPI00174771
M.HSSN#FSSSN#GSTEDLFR.D
0.5344





IPI00174772
K.QEN#SSQENEN#KT.K
0.6531





IPI00174837
K.NIKHSGN#ITFDEIVNLAR.Q
0.6773





IPI00174865
M.ERESLKSPFTGDTSM*NNLETVHHN#NSKADKLK.E
0.772





IPI00174978
P.FKYIYELNN#VTPLDNLLN#LSNEILN#AS.-
0.976





IPI00175108
K.ALRTDYN#ASVSVPDSSGPEHILSISAGIDTIGEIL.K
0.523





IPI00175146
M.DQMAVLLVSNIN#ESK.G
0.6722





IPI00175151
R.DLHNMQN#GSTLVCTLTR.E
0.9403





IPI00175296
K.SFNCN#SSLIKHWRVHTGER.P
0.5582





IPI00175421
K.SFSLN#RTLTVHQRIHTGEK.P
0.8543





IPI00175439
K.GDFESQN#SSLESSISQVINLEK.N
0.7617





IPI00175448
R.ESTGAQVXM*AGDMLPN#STEQAITIAGIPQSIIECVK.Q
0.6594





IPI00176188
-.MDPN#CSCAASDSCTCAGSCK.C
0.68





IPI00176196
L.LKAN#NTLLKMGYHFELPGPRM*VVTNLLTR.N
0.8041





IPI00176210
K.HGNLRNVLILMDQSAWDSN#ATLR.Q
0.5051





IPI00176376
K.N#GSGNAIIIVVGGAAESLSSM*PGK.N
0.9906





IPI00176482
K.GTSSSPLAVASGPAKSSSMTTLAKN#VTN.K
0.8454





IPI00176482
I.LGKNEEAN#VTIPLQGFPRK.E
0.5105





IPI00176568
R.WHIN#FTTFFIDCM*AAFGLAYDQK.K
0.6687





IPI00176590
R.GGN#FSGRGGFGGSHGGGGYGGSGDGYNG.F
0.5039





IPI00176709
K.KLSN#GSIVPLEDSLNLIEVATEVPKRK.T
0.7248





IPI00176843
R.SQSANQVCGYVKSNSLLSSN#CSTWKYFICEK.Y
0.9477





IPI00177323
E.NIM*AGATVLFLN#ATDLDR.S
0.581





IPI00177394
M.SQSMGGDN#LSSLDTNEAEIEPENMR.E
0.5416





IPI00177498
R.KENSFLTHQHGN#DSEAEGEVVCR.L
0.5182





IPI00177509
K.EN#STLNCASFTAGIVEAVLTHSGFPAK.V
0.6072





IPI00177824
R.TPN#SSCSTPSRTSSGLFPR.I
0.8676





IPI00177884
M.QQFLYEISNLDTLTN#SSSFEGY.I
0.658





IPI00177884
R.LN#SSSVSNLAAVGDLLHSSQASLTAALGLR.P
0.5714





IPI00177940
R.RLEGTN#VTVNVLHPGIVR.T
0.5013





IPI00177967
D.SFSQASN#VTSQLPGFPK.Y
0.5069





IPI00178015
K.LNQLYN#CSSSLSFM*DS.C
0.7591





IPI00178140
Y.TPTGEPVFGGLPQN#ASLIAHLAR.T
0.5825





IPI00178319
H.GRYIASIMEN#GSLNIYSVQALTQEINK.E
0.6701





IPI00178324
M.IMIMN#GTLYIAAR.D
0.9405





IPI00178349
R.EDCNGIFRIN#VSVSKNLNLKLR.P
0.8474





IPI00178386
E.VFENLDGDLGN#STEK.Q
0.7858





IPI00178386
K.YFEEGLQDGN#DTFALLGK.A
0.8505





IPI00178415
Q.STM*LDTNSWIFACIN#STSM*CLQGVDLSWK.A
0.8056





IPI00178607
R.SCRAAQAM*DCEVNN#GSSLR.D
0.7522





IPI00178667
L.APNQYVISGEVAILN#STTIEISELPVRTWTQTYK.E
0.5461





IPI00178673
R.TALFPDLLAQGN#ASLR.L
0.5432





IPI00178675
M.M*LGDAKIGN#NSVSSLK.N
0.554





IPI00178676
K.N#ITDELGVLGVAGPQARK.V
0.7784





IPI00178767
M.LQYYLN#LTEANLKGESIWK.L
0.71





IPI00178926
R.EN#ISDPTSPLR.T
0.9997





IPI00179053
P.PNN#VSVPLLM*PLVTLMER.Q
0.5958





IPI00179057
K.LN#SSSSSSSN#SSNER.E
0.8713





IPI00179071
K.QN#NTNANKPK.K
0.9727





IPI00179071
K.QQFNTQN#QSNVM*PGPAQIMRGPTPN.M
0.8669





IPI00179131
K.INCIRPDAFQDLQN#LSLLSLYDNK.I
0.9323





IPI00179193
K.WSCTEASN#TSPTMSAAQNAE.-
0.9954





IPI00179193
N.QAGDTSN#QSSGP.H
0.635





IPI00179326
K.LLEEN#ETEAVTVPTPSP.T
0.5796





IPI00179357
K.N#ASGTKAVSVMVK.V
0.5661





IPI00179357
E.SFVEMSSSSFM*GISN#MTQLESSTSK.M
0.9308





IPI00179357
K.WRRPDYDGGSPN#LSYHVERR.L
0.8427





IPI00179357
K.VNRYDAGKYTIEAEN#QSGKK.S
0.6046





IPI00179357
R.AN#HTPESCPETKYK.V
0.5494





IPI00179377
K.LVQDVAN#NTNEETGDGPTTATVLAR.S
0.7937





IPI00179415
K.ALTSETN#GTDSN#GSN.S
0.5723





IPI00179453
M.FCNQQSVCDPPSQNNAAN#ISMVQAASAGPPSLR.K
0.7732





IPI00179468
R.NIYQPPEGN#ASVIQDFTEDGHLLHTFYLGTGRR.V
0.8474





IPI00179582
K.LRPVTLTEMN#YSKYGAK.E
0.7547





IPI00179721
R.SCNDFGSYNN#QSSNFGPMK.A
0.9302





IPI00179972
G.VGAFN#LTLSMLPTR.I
0.5056





IPI00180034
R.FN#GSGSGTDFTLK.I
0.9981





IPI00180178
K.N#KTTCLRGSDTAALVPVPLATPLLLEGR.S
0.7197





IPI00180305
C.ALSLFLMAVNIKTPVVVEN#ITLM*CLR.I
0.5363





IPI00180305
K.AM*EEFFSDSGELVQIMMATANEN#LSA.K
0.5895





IPI00180403
R.ADKGPVTSILPSQVN#SSPVINHLLLGKK.M
0.6594





IPI00180404
K.REEEEEEEGSIM*N#GSTAEDEEQTR.S
0.9289





IPI00180462
K.YLKEAPLASSAN#GTEK.N
0.7163





IPI00180465
-.MMATPN#QTACNAESPVALEEAK.T
0.7847





IPI00180466
R.HPQVLQATQETLQRHGVGAGGTRN#IS.G
0.5021





IPI00180625
R.DFDQNM*N#DSCEDALAN.K
0.7645





IPI00180627
R.FCTQTLGVDKGYKN#QSFYRK.H
0.9555





IPI00180687
R.GNVN#GTFIIHPDSGN#LTVAR.S
0.6572





IPI00180707
R.LVLGTPQSNSPFGAAVGEQN#ETLIR.I
0.7764





IPI00180712
K.YPLM*QRMTN#SSSSPSLLN#DSAK.P
0.5241





IPI00180719
K.GHPN#RSALSLPPGLRIGPSGIPQAGLGVWNEASDLPL.G
0.921





IPI00180730
K.DGN#ASGTMLLEALDCILPPTR.P
0.623





IPI00180919
G.KGFICEFCQN#TTVIFPFQTATCRR.C
0.529





IPI00181081
V.IVGVPPDSQN#LSMNPMLLLTGR.T
0.9548





IPI00181160
E.NYLEFGLETGFTN#FSDSAMQFLEK.Q
0.7756





IPI00181174
T.ITMIPNTLTGM*QPLHTFNTFSGGQN#STNLPHGHSTTR.V
0.5768





IPI00181260
R.NEKCNEN#YTTDFIFNLYSEEGK.G
0.5859





IPI00181285
K.GIVVLIDPLAAN#GTTDMHTSVPR.V
0.9997





IPI00181285
R.KAASTLSDTKNM*EIIN#STIETLAPDSPFDH.K
0.6375





IPI00181306
K.QHGVN#VSVN#ASATPFQQPSG.Y
0.9438





IPI00181703
K.HN#SSSSALLNSPTVTTSSCAGASEKKK.F
0.5105





IPI00181743
K.LALLN#ASLVKGN#LSR.V
0.9041





IPI00181743
R.AN#GTAGPTEDHTDDFLGCLNIPVR.E
0.876





IPI00181921
P.TSSM*N#VSMM*TPINDLHTADSLNLAK.G
0.8415





IPI00181944
W.AQN#GSMSQPLGESPATATATATATTRPSPTTPAM*PK.M
0.7741





IPI00182027
L.ATLGTTALN#NSNPK.D
0.9443





IPI00182116
M.QKSTNSDTSVETLN#STR.Q
0.5329





IPI00182164
K.LASN#GTPM*GTFAPLWEVFR.V
0.674





IPI00182194
R.CN#ISLPMENGLNSIEWR.L
0.5171





IPI00182233
K.VN#ATNFQALAAEFGGESFTSTFQTQSPPSFYR.A
0.8446





IPI00182469
R.YQEAAPNVAN#NTGPHAASCFGAK.K
0.6337





IPI00182545
R.ECFNIGNFNSMMAIISGM*N#LSPVAR.L
0.9661





IPI00182601
R.DN#TSVYHISGKK.K
0.8755





IPI00182768
A.RTTFN#FSIGVLQAECLTSKGR.E
0.6009





IPI00182811
K.CPKPM*EEN#HSVSHKKSKK.K
0.9412





IPI00182840
R.GRPALPNPEGRAREPCPN#R.T
0.5505





IPI00183110
K.EM*YQPEDDN#NSDVTSDDDM*TRNR.R
0.9663





IPI00183230
M.VHM*PDSLGGGPEGPCFCPTPCN#LTR.Y
0.5918





IPI00183414
A.HVCN#DTNKMTLINPQGAKLNIYKRK.V
0.9007





IPI00183445
K.QTESSFM*AGDIN#STPTLNR.G
0.5272





IPI00183526
K.TLVLSN#LSYSATEETLQEVFEK.A
0.5981





IPI00183568
K.KDAENHEAQLKN#GSLDQGSR.I
0.9744





IPI00183606
R.GRPFPLALLGWAPSN#ITFALLFGRR.F
0.689





IPI00183706
K.SLIEGVISGYN#ATVFAYGPTGCGK.T
0.7301





IPI00183804
K.TFKN#ESENTCQDMTFSTWTPPPGVHSQTLSR.F
0.9775





IPI00183933
D.VN#LSKTEKM*GNTVESEHLSELTEEEYEAHYIR.R
0.727





IPI00183965
R.LGSSKSGDN#SSSSLGDVVTGTRRPT.P
0.8717





IPI00184048
K.LLVNLADHNGNTALHYSVSHSN#FSIVK.L
0.6851





IPI00184048
R.N#FSLPDICEEDPGAPAGAVELPGAWVPGAGQR.H
0.8796





IPI00184160
R.SMPEASDQEEHLSPLDFLHSAN#FSLGSINQRLNKR.E
0.8483





IPI00184441
K.KHELKPNN#PTEEGLASIHSVLFRKDP.F
0.6678





IPI00184533
K.QLFTLQTVNSN#GTSDR.T
0.6054





IPI00184997
K.SLTTECHLLDSPGLN#CSNPFTQLER.R
0.7415





IPI00185036
K.SHISN#HTALENCVSLLCIRADEL.Q
0.988





IPI00185088
K.AFHTEISSSDN#NTLTSSNAYNSR.Y
0.5178





IPI00185198
K.SVSTSSPAGAAIASTSGASN#NSS.S
0.9922





IPI00185234
K.DRIATIN#YTVLTSVLNPFIYSLRNK.D
0.8774





IPI00185251
R.RCIIVGNGGVLAN#KSLGSR.I
0.5341





IPI00185256
R.N#TTSTCIATVVGLTGAR.L
0.9065





IPI00185518
-.MEN#FTALFGAQADPPPPPTALGFGPGK.P
0.5147





IPI00185526
D.DSTEAHEGDPTN#GSGEQSK.T
0.6032





IPI00185649
L.LSPN#LTDEQAM*LEDTLVALFDLEK.V
0.7918





IPI00185878
R.MSMLASQQN#QSGPSGNN#QSQGNM*QR.E
0.6421





IPI00185878
R.N#NSYSGSNSGAAIGWESASGNGFNGGSGSSMDSQSSGWEM.-
0.8281





IPI00186101
G.NYN#NSSNFGTM*KVGNFGGRNSGSYGVGGQYFAKPR.H
0.5471





IPI00186157
R.REN#NSPSNLPR.P
0.6346





IPI00186315
R.SVTLQIYN#HSLTLSAR.W
1





IPI00186315
R.FDFQGTCEYLLSAPCHGPPLGAEN#FTVTVANEHR.G
0.9836





IPI00186525
M.MLQNILQIN#RSK.R
0.996





IPI00186843
R.CSHGMVEANGLIYVCGGSLGNN#VSGR.V
0.7732





IPI00186850
K.APLN#ETGEVVNEKAK.T
0.5488





IPI00187002
K.IEEEEEEENGDSVVQNN#NTSQMSHKK.V
0.5503





IPI00187149
R.KMLLWAMSVTLEQN#LTCPGSDLKPFTTR.L
0.5972





IPI00215608
K.LLNSN#KSGAAFN#QSKSLTLPQTCNR.E
0.582





IPI00215613
R.GENAYSTVLN#ISQSANLQFASLIQK.E
0.7158





IPI00215613
L.FTM*HNN#RSLTIHQAMR.G
0.9898





IPI00215699
D.DN#STFN#STQSHMDWGK.V
0.6856





IPI00215761
M.LFTNEDNPHGN#DSAKASRAR.T
0.5418





IPI00215770
R.RGAQSPGVM*N#GTPSTAGFLVAWP.M
0.5903





IPI00215869
K.MEN#ESATEGEDSAMTDMPPTEEVTDIVEM*R.E
0.8853





IPI00215900
K.VPWYVLAGNHDHLGN#VSAQIAYSK.I
0.5019





IPI00215979
K.HLEGISDEDIIN#ITLPTGVPILLELDENLR.A
0.6224





IPI00215995
R.CQKLELLLM*DNLRDKLRPIIISMN#YSLPLR.M
0.6812





IPI00216047
R.HQGTVTEDKNN#ASHVVYPVPGNLEEEEWVRPVM*.K
0.8674





IPI00216133
K.MSN#YSLLSVDYVVDK.A
0.8387





IPI00216142
K.AIN#NSFAPEKLQELAFQTIQEIR.H
0.9499





IPI00216143
R.KN#KSVWITISS.T
0.6859





IPI00216151
R.LM*RQLLVIN#ESIESIK.W
0.6777





IPI00216171
K.LDNLMLELDGTEN#KSK.F
0.764





IPI00216184
L.ANLVGNLGIGN#GTTK.N
0.8756





IPI00216219
D.KAPVN#GTEQTQK.T
0.9349





IPI00216253
E.NN#VSKGDNGELAK.E
0.6856





IPI00216269
R.TLHSTFQPN#ISR.Y
0.9532





IPI00216283
R.FGKQAALDPFILLNLLPN#STDK.Y
0.6984





IPI00216311
-.MPKPINVRVTTMDAELEFAIQPN#TTGK.Q
0.7673





IPI00216315
R.N#RTFVLNFIK.I
0.9256





IPI00216315
K.EVFVHPN#YSK.S
0.9993





IPI00216317
M.DFN#LSGDSDGSAGVSESR.I
0.9879





IPI00216362
Y.RPPDRSAPSWN#TTGEVVVTM*EPEVPIKK.L
0.7216





IPI00216529
H.DVTN#ISTPTHVVFSSSTASTTVGFEW.-
0.7403





IPI00216560
I.RVGN#ATIDR.E
0.9979





IPI00216560
E.FIHLLSN#ITGAIVNTDNVQFHVDK.K
0.9153





IPI00216560
R.VLDINDNDPVLLNLPMN#IT.I
0.6244





IPI00216560
L.SVIDN#ASDLPERSVSVPNAK.L
0.5203





IPI00216587
K.TRIIDVVYN#ASNNELVR.T
0.5021





IPI00216702
R.QNIAIEVDAFGTRN#GTDDPSYNGAIIVSGDEK.D
0.5627





IPI00216711
M.SFN#CSTRN#CSSRPIGGR.C
0.692





IPI00216721
R.N#CSHWAVGVASWEM*S.R
0.8429





IPI00216722
D.SAN#YSCVYVDLKPPFGGSAPSER.L
0.9987





IPI00216722
R.EGDHEFLEVPEAQEDVEATFPVHQPGN#YSCSYR.T
1





IPI00216722
R.FQSPAGTEALFELHN#IS.V
0.8918





IPI00216722
Q.PSLWAESESLLKPLAN#VTLTCQAHLETPDFQLFK.N
0.8198





IPI00216744
R.RSKSPADSAN#GTSSSQLSTPKSKQSPISTPTSPGSLR.K
0.7204





IPI00216750
R.IGVSFIDDGSN#ATDLLR.K
0.9589





IPI00216752
K.FN#PSLNVVDK.I
0.5155





IPI00216752
R.FYISKGAVVDQLGGDLN#STPLHWAIR.Q
0.5394





IPI00216798
K.NEEIDEMIKEAPGPIN#FTVFLSMFGEKLK.G
0.9564





IPI00216803
R.KTTSNN#FTHSR.A
0.7493





IPI00216803
R.NSN#YTYPIKPAIENWGSDFLCTEWKAS.N
0.9624





IPI00216869
R.SPAAAILELFEEQN#GSLQELHYLMTVMER.L
0.818





IPI00216889
K.N#ITLLPATAATTFTVTPSG.Q
0.9734





IPI00216890
I.ELN#DSVNENSDTVGQIVHYIM*K.N
0.8381





IPI00216984
R.DGN#GTVDFPEFLGMMARK.M
0.5129





IPI00216990
K.LMLVSAPSILSSGN#GTAIN#M*.T
0.7066





IPI00216990
K.IGLNIGQAIVN#TSGTVPAIPSINILQN#VTPKGEDK.S
0.8975





IPI00217002
R.LPINGANTVIGSN#NSVQNVPTPQTFGGK.H
0.6506





IPI00217002
K.QSSNRPAHN#ISHILGHDCSSAV.-
0.8209





IPI00217005
R.HEKMGSN#ISQLTDKNELLTEQVHK.A
0.8253





IPI00217013
K.EVLLKTN#LSGRQS.P
0.9496





IPI00217013
M.HVLTAPLLAN#TTEDKPSK.D
0.9588





IPI00217032
-.M*SSKPEPKDVHQLN#GTGPSASPCSSDGPGR.E
0.5652





IPI00217051
R.SSTSSIDSN#VSSK.S
0.5088





IPI00217051
P.TKIGSGRSSPVTVN#QTDK.E
0.8504





IPI00217051
M.EGFNSGLNSGGSTN#SSPK.V
0.8461





IPI00217051
R.YATQSN#HSGIATSQ.K
0.7705





IPI00217051
K.YHFSNLVSPTN#LSQFNLPGPSMM*R.S
0.5912





IPI00217055
R.IVESYFMLN#STLYFSYTHMVCR.T
0.8907





IPI00217093
R.RQISQKAFLFN#SSEQVAEFVISR.P
0.5277





IPI00217110
R.VGLFCGIFIVLN#ITLVLAAVFK.L
0.8825





IPI00217162
K.TKLPEYTREALCPPACRGSTTLYN#CSTCK.G
0.9307





IPI00217163
R.N#RSYVFSSLATSAVSFATGALGMWIPLYLHR.A
0.7188





IPI00217164
K.LVPSSSYVAVAPVKSSPTTSVPAVSSPPMGN#QSGQSVP.-
0.8555





IPI00217267
K.IENYIN#ESTEAQSEQK.E
0.7729





IPI00217267
K.LHCNSACLTN#TTHCPEEASVGNPEGAFMKVLQARKN.Y
0.72





IPI00217272
M.GHN#FSLPVYKGEIQAR.N
0.5381





IPI00217309
R.VLYM*FNQMPLN#LTNAV.A
0.8516





IPI00217355
R.EAFFGGNGKIN#LTVFK.L
0.869





IPI00217355
K.DN#STACSHPVTK.H
0.9644





IPI00217370
K.HELGITAVMNFQTEWDIVQN#SSGCNR.Y
0.6828





IPI00217378
K.KVDAQSSAGKEDM*LLSKSPSSLSAN#ISSSPK.G
0.9212





IPI00217391
L.FDNAAQPYSN#LSNLDVLNQVIRERDTK.L
0.8792





IPI00217438
M.AKSALREN#GTNSETFRQRFR.R
0.9696





IPI00217442
S.QELNFVM*DVN#SSK.Y
0.8408





IPI00217446
R.VSTVYANN#GSVLQGTSVASVYHGK.I
1





IPI00217465
K.ALAAAGYDVEKN#NSR.I
0.5791





IPI00217542
R.SCCEGM*ICNVELPTN#HTNAVFAVM*HAQR.T
0.5205





IPI00217544
K.HM*PPPN#MTTNERR.V
0.513





IPI00217652
K.FN#STQIAAM*APEHEEPR.I
0.7554





IPI00217652
H.PYYGKTGVNSGVMLM*N#M*TRM*RRK.Y
0.9849





IPI00217669
C.LQKGSLTIQQVNDLLDSIASN#NSAK.R
0.9484





IPI00217710
K.GNSKAGN#GTLENQK.G
0.6136





IPI00217710
K.EVDIEGTTVIEVGLDPSNN#MTLAVDCVGILKLR.N
0.9291





IPI00217766
K.ANIQFGDN#GTTISAVSNK.A
0.698





IPI00217797
K.HSAGSGAEESN#SSSTVQK.Q
0.9156





IPI00217809
K.GFN#WSSALTKHK.R
0.5579





IPI00217851
K.TVN#LSVTPSPAPR.T
0.6436





IPI00217872
K.FN#ISNGGPAPEAITDK.I
0.8006





IPI00217876
R.VEN#GSSDEN#ATALPGTWR.R
0.6182





IPI00217884
T.ERLLGEASSN#WSQAK.R
0.8245





IPI00217897
R.GPVSSDVEEN#DSLNLLGILPN#NSDSAKK.N
0.7341





IPI00217937
R.VEYTGHPLEIAVFLNYCTVCN#VTK.K
0.8099





IPI00217975
M.N#TSTVNSAR.E
0.8875





IPI00217991
K.DKLDETN#NTLRCLK.L
0.9003





IPI00217998
R.AAEN#ASLGPTN#GSKLM*NR.Q
0.5164





IPI00218052
K.AFAADTGM*N#RSQSEYCNVGTKT.Y
0.7731





IPI00218064
K.SWN#KSQNDCAIN#NSYLMVIQDITAM*VR.F
0.5421





IPI00218081
R.FIDSSNPGLQISLNVN#NTEHVVS.I
0.7522





IPI00218093
K.GRIGVVISSYM*HFTN#VSASADQALDR.F
0.8862





IPI00218130
R.GLAGVEN#VTELK.K
0.9988





IPI00218132
R.EGGHDVPSNKDVTSLDWNTN#GTLLATGSYDGFAR.I
0.8776





IPI00218135
K.KHHHHAVGLN#LSHVRKR.C
0.9298





IPI00218189
R.DVMWEN#YSNFISLGPSISKPDVITLLDEER.K
0.7125





IPI00218192
K.LPTQN#ITFQTESSVAEQEAEFQSPK.Y
1





IPI00218192
K.AFITN#FSMNIDGM*TYPGIIK.E
1





IPI00218288
R.RLRIHNLGLN#CSSQLADLYKSC.E
0.8439





IPI00218337
R.VFPYISAMVNN#GSLSYDHERDGR.P
0.9949





IPI00218413
K.DVQIIVFPEDGIHGFN#FTR.T
1





IPI00218413
R.YQFNTNVVFSNN#GTLVDR.Y
1





IPI00218413
K.NPVGLIGAEN#ATGETDPSHSK.F
1





IPI00218413
R.FN#DTEVLQR.L
0.9997





IPI00218413
K.WNVNAPPTFHSEMMYDN#FTLVPVWGK.E
0.5565





IPI00218490
K.CVVEMEGN#QTVLHPPPSNTK.Q
0.5427





IPI00218490
D.YQVTLQIPAAN#LSANR.K
0.6812





IPI00218529
R.ASLN#HSTAFNPQPQSQMQDTR.Q
0.6734





IPI00218571
K.YNN#GSTELHSSSVGLAK.A
0.5342





IPI00218648
K.NEKN#GTDELDNMN#STERISFLQEKLQEIRK.Y
0.7548





IPI00218676
K.FIHNENGAN#YSVTATR.S
0.9775





IPI00218725
D.LLRTLN#DTLGKLSAIPN#DTAAKLQAVK.D
0.8184





IPI00218725
K.N#ESGIILLGSGGTPAPPR.R
0.876





IPI00218725
R.YM*QN#LTVEQPIEVK.K
0.7963





IPI00218731
K.FVDTAGN#FSFPVN#FSLSLL.N
0.7538





IPI00218732
R.VVAEGFDFANGIN#ISPDGK.Y
1





IPI00218732
K.VTQVYAEN#GTVLQGSTVASVYK.G
1





IPI00218732
K.HAN#WTLTPLK.S
1





IPI00218762
R.LSSSGSN#CSSGSEGEPVALHAGICVR.Q
0.697





IPI00218795
R.DN#YTDLVAIQNK.A
1





IPI00218795
K.IGGIWTWVGTN#K.S
0.9987





IPI00218803
R.CATPHGDN#ASLEATFVK.R
1





IPI00218829
R.EN#LSAAFSRQLNVNAKPFVPNVHAA.E
0.8352





IPI00218832
K.YHVMAPALSFHMSPWSWSN#CSRK.Y
0.5001





IPI00218888
R.SGQVEVN#ITAFCQLIYPGK.G
0.8154





IPI00218889
M.IN#NTKAFIHHELLAYLYSSADQSSLMEESADQAQR.R
0.8667





IPI00218916
K.AN#ATGGGGHVQMVQR.A
0.6597





IPI00218924
G.EN#GTLSR.E
0.551





IPI00218925
R.N#GSLQEKLWAILQATYIHSWNLARFVFTYK.G
0.8472





IPI00218964
K.GFSQLSN#LTK.H
0.5542





IPI00218987
I.FN#ETKN#PTLTR.R
0.8742





IPI00218987
S.FSWSGGAFLYPPN#MSP.T
0.6366





IPI00219050
D.RPPSPTDN#ISRYSFDNLPEK.Y
0.7622





IPI00219074
M.TLTN#LSGPYSYCN#TTLDQIGTCWPR.S
0.8586





IPI00219078
M.TM*ALSVLVTIEMCNALNSLSEN#QSLLR.M
0.5952





IPI00219130
R.MIRTNEAVPKTAPTN#VSGRSGRR.H
0.6745





IPI00219131
K.TVVTYHIPQN#SSLENVDSR.Y
1





IPI00219173
K.EN#PSTVGVER.V
0.8501





IPI00219294
A.DGAAASNAADSAN#ASLVNAK.Q
0.5289





IPI00219314
R.N#PSSAAPVQSRGGIGASENLENPPKMGEEE.A
0.5677





IPI00219336
K.EN#ITDPPRGCVGNTNIWKTGPLFK.R
0.562





IPI00219336
R.TM*N#FTYEVHLVADGK.F
0.5344





IPI00219418
P.PTLHATAASVAVPN#KTC.-
0.5068





IPI00219425
R.PVDKPIN#TTLICN#VTNALGAR.Q
1





IPI00219438
R.LVRVTYVSSEGGHSGQTEAPGN#ATSAM*LGPLSSSTTYTVR.V
0.6163





IPI00219546
R.AGVVFMAGHVYAVGGFN#GSLR.V
0.727





IPI00219561
R.SQSLIFLN#LSTNNLLD.D
0.7636





IPI00219561
K.M*N#LTQNTLGYEGIVKLYKVLK.S
0.6044





IPI00219567
M.TAM*DN#ASKN#ASEMIDKLTLTFN#R.T
0.6677





IPI00219616
R.N#CTIVSPDAGGAKRV.T
0.6361





IPI00219677
F.IKTSTGKETVN#ATFPVAIVM*LR.A
0.5344





IPI00219678
K.EALRAGLN#CSTENMPIK.I
0.6587





IPI00219695
K.LQNAENDYIN#ASLVDIEEAQR.S
0.7258





IPI00219753
M.LQYGGRN#RTVATPSHGVWDMRGK.Q
0.9978





IPI00219778
G.VSLSSYLEGLMASTISSN#ASKGREAMEWVIHK.L
0.7098





IPI00220106
K.EIYHQNVQN#LTHLQVVEVLK.Q
0.9044





IPI00220113
R.LATN#TSAPDLK.N
0.5931





IPI00220279
K.ARKSIAQSGVNM*CNQN#SSPHK.N
0.5215





IPI00220289
K.VLN#HSPMSDASVNFDYK.S
0.5346





IPI00220289
K.LILSQN#HSDEEEEEEENEEENLAMAVGM*GE.R
0.7406





IPI00220289
R.EHGAQAGEGALKDSNN#DTN.-
0.5987





IPI00220327
E.ESRM*SGECAPN#VSVSVSTSHTTISGGGSR.G
0.9876





IPI00220391
N.EINN#MSFLTADN#K.S
0.6322





IPI00220477
K.WRLSN#NSVVEIASLR.F
0.5223





IPI00220573
K.N#PTDEYLDAM*M*NEAPGPIN#FT.M
0.956





IPI00220630
K.VLN#GTLLM*APSGCK.S
0.6459





IPI00220817
K.GRAN#HSAFLFGFGDGGGGPTQTM*LDR.L
0.9349





IPI00220830
K.SPIIPECSTNVQTAAGGSN#SSQYNSN#LTIRLSVSWK.G
0.7428





IPI00220901
R.QSSSEQCSN#LSSVR.R
0.9976





IPI00221035
K.LGVNN#ISGIEEASNMFT.N
0.5057





IPI00221055
T.TN#STN#PSPQGSHSAIGLSGLN#PSTG.-
0.5081





IPI00221130
M.FCINICTVYCN#NSFPIHSSN#STK.K
0.8358





IPI00221193
R.N#VTVGPPENIEVTPGEGSLIIR.F
0.682





IPI00221224
R.N#ATLVNEADKLR.A
0.9987





IPI00221224
R.PSAIAAGHGDYALN#VTGPILNFFAGHYDTPYPLPK.S
1





IPI00221224
K.GPSTPLPEDPNWN#VTEFHTTPK.M
1





IPI00221224
K.AEFN#ITLIHPK.D
0.9998





IPI00221224
K.VPVTLALN#NTLFLIEER.Q
0.9152





IPI00221224
E.KNKNAN#SSPVASTTPSASATTNPASATTLDQSK.A
0.6663





IPI00221234
R.EENEGVYN#GSWGGR.G
0.518





IPI00221246
H.AATTQYAN#GTVLSGQTTNIVTHR.A
0.8126





IPI00221307
R.GTELDDGIQADSGPIN#DTDANPR.Y
0.6039





IPI00221325
S.QSGHMLLN#LSR.G
0.6875





IPI00221332
K.AENDENGQAEN#FSM*DPQLERQVETIR.N
0.5238





IPI00221338
M.LTTHPSLYRVDN#LSDEGALN#ISDR.T
0.504





IPI00232047
R.IVTTN#VTMPEGPPQNCVTGN#ITGK.S
0.6369





IPI00232311
L.TKRTNMDFSICISN#ITPADAGTYYCVK.F
0.6504





IPI00232837
R.RKLAIENTMAXLVSVGANSAVN#NTAESK.M
0.6462





IPI00232917
K.RSPIFFNYLYSPLEIEALKPNVN#VSSLK.K
0.5956





IPI00232917
R.ACLGLIYTVYVDSLN#VSLESLIANLCACLVPAA.G
0.6628





IPI00233062
P.TN#ETTFAK.L
0.5199





IPI00233501
R.RIN#MSFVEVKDK.K
0.5329





IPI00233618
K.YALIIVM*M*TIM*TATDIQLLN#QTMENTR.Q
0.8842





IPI00234002
K.VGAERNVLIFDLGDDTFN#VSILTTEDGIFEVK.S
0.9519





IPI00234035
K.KEIYM*HTGN#SSTPRGEGGSC.Y
0.6357





IPI00234091
R.IPSYN#LTVSVSDNYGAPPGAAVQAR.S
0.9418





IPI00234337
K.YFWN#DTIHNFDFLK.G
0.869





IPI00234446
R.QYKDLWN#MSDDKPFLCTAPGCGQ.R
0.9067





IPI00235307
K.N#SSLAEFVQN#LSQ.I
0.7697





IPI00235412
P.VKLGIIGVVN#RSQLDINNKK.S
0.516





IPI00235721
M.RPHEDLSEDN#SSGEVVMRVTSV.-
0.6184





IPI00235756
K.ALDPSQPVTFVTN#STYAADKGVNK.E
0.8329





IPI00235832
T.DDTN#VTWLQLETEIEALKEELLLM*KK.N
0.5479





IPI00236481
R.DRLALAN#ESGVTLMPDGSLHLAALPSR.R
0.5621





IPI00236852
K.VLTPEELLYRAVQSVN#VTHDAVH.A
0.6419





IPI00238209
M.FN#ISPGAVQF.-
0.5901





IPI00238575
R.NSINVFASPAHYTSTTGSCNFETSSGN#WTTA.C
0.8781





IPI00238781
R.EACANILIDSGADPNIVGVYGNTAVHYAVNSEN#LSVVAK.L
0.7623





IPI00239216
K.N#SSSEQLFSSARLQNEK.K
0.5697





IPI00239405
R.TNVLNDAYEN#LTRYK.E
0.6296





IPI00239992
M.CVETFSN#YSLLGHFAVR.H
0.6302





IPI00240401
V.ILSNNN#HTEIQEISLALR.S
0.6262





IPI00240812
R.M*ETVSN#ASSSSN#PSSPGR.I
0.663





IPI00240988
K.ECQHGGQCQVEN#GSAVCVC.Q
0.849





IPI00241148
R.VLYM*FNQMPLN#LTNAVATAL.Q
0.9888





IPI00241313
K.QPVESSEDSTDDSN#SSSGEEE.R
0.622





IPI00241390
K.LINYN#NSITNSVYSR.F
0.5989





IPI00241390
W.NEDYCKLFKN#ITVEEMNELER.Q
0.8937





IPI00241802
R.YTLVFN#SSSERN#VSLTEHKKK.Q
0.9834





IPI00241809
R.N#MTLLATIM*SGSTM*SLNHE.A
0.8965





IPI00242956
R.SVTLQIYN#HSLTLSAR.W
1





IPI00242956
R.FNFQGTCEYLLSAPCHGPPLGAEN#FTVTVANEHR.G
0.9999





IPI00242956
K.VTVRPGESVM*VN#ISAK.A
0.9997





IPI00242956
R.VITVQVAN#FTLR.L
0.9991





IPI00242956
R.YLPVN#SSLLTSDCSER.C
0.9957





IPI00242956
R.VVTVAALGTN#ISIHK.D
0.7561





IPI00242956
R.GLCVLSVGAN#LTTFDGARGA.T
0.6825





IPI00242960
R.KPSPQDIAQAVLRN#FSGK.D
0.8685





IPI00242960
R.SHN#ASLHPTPEQCEAVSKFIGECK.I
0.6224





IPI00243275
K.NNGFFQKLN#VTEGAMQDLLKEIIK.V
0.5003





IPI00243295
K.LVSSSNAMEN#ASHQASVQVESLQEQLNV.V
0.5118





IPI00243423
K.HTVSGILSM*ANAGPNAN#SSQFFICAAK.T
0.8311





IPI00243451
R.YSKETNIDPSEN#STSNLPNCLINQMLSLN#R.T
0.7589





IPI00243595
R.CRELRN#FSSLRAILSALQSNPIYR.L
0.546





IPI00243984
K.N#KTSTASSMVASAEQPSGSVEEELSK.K
0.9238





IPI00244043
K.HGIEAAFLAMLGLQGNKQVLDLEAGFGAFYAN#YSPK.V
0.9357





IPI00244116
K.NYNDHENN#LSAICLVK.L
0.7134





IPI00244243
S.QCGKM*ANKAN#TSGDFEK.D
0.8987





IPI00244477
R.RGASVN#RTTR.T
0.7576





IPI00244477
R.RGASVN#RTTRTN#STPLR.A
0.7364





IPI00244574
R.NPPAFGN#VSVIALELLNSGYEFDEGSIIFNQFK.S
0.9118





IPI00245135
K.TNNVN#VSSR.V
0.9087





IPI00246001
R.KSEIHGAPVLFQN#LSGVHWGYEETK.T
0.504





IPI00246053
R.IIPGFMCQGGGFTCHN#GTGGK.S
0.5369





IPI00246067
R.LESGM*RN#M*SIHSK.T
0.5097





IPI00246067
R.WLGSTGVTCGVRRQISEMNGN#ISR.L
0.9315





IPI00246676
R.DSFGAHTYELLAKPGQFIHTN#WTGHGGSVSSSSYNA.-
0.6455





IPI00246686
K.IIMLPSALDQLSQLN#IT.Y
0.7462





IPI00247110
R.KCQLN#LTDSEN#R.T
0.8279





IPI00247535
K.ENIPGDFLCISLVN#SSVQLRYNLGDR.T
0.8588





IPI00247535
M.RNLQFTTISLN#FSTTK.T
0.5147





IPI00247601
K.YDNSLKIISN#ASCTTNCLAPR.A
0.659





IPI00247616
M.DN#VTGGMETSR.Q
0.9515





IPI00247641
R.NTFTPGEKVVFTTEINN#QTSKCIK.T
0.7698





IPI00247659
-.MDSVAFEDVAVN#FTQEEWALLDPSQK.N
0.9716





IPI00248101
K.NAPQN#STQAHSENK.C
0.605





IPI00248307
R.SEASN#GSTVAAGTSKSEEGLSSGLGSGVGGK.P
0.8167





IPI00248651
G.AEVKFVLKHQN#VSEFASSSGGSQLLFK.Q
0.8866





IPI00248881
R.KN#CSQIALFQK.R
0.7556





IPI00248896
K.STN#ISFTDMVSADER.L
0.515





IPI00248930
K.MN#SSIMAN#VTKAFVGDSK.D
0.6629





IPI00249283
K.HGSNNVGLSEN#LTDGAAAGNGDGGLVPQR.K
0.8945





IPI00249584
M.SVTFISN#NTAIQELFRFR.C
0.8754





IPI00249629
K.NRVQSKISN#LTDAKNPNLR.K
0.9153





IPI00249660
R.NRDLN#NSSIN#LTKVK.I
0.9934





IPI00249983
M.ATRTLN#LSFFPR.S
0.638





IPI00251351
R.GTRARLLSSFLSFLN#GSSANQAVGQGPEAGEGR.G
0.7762





IPI00252768
R.NILDALM*LN#TTR.I
0.9998





IPI00252944
L.TRLQLDGNQITN#LTDSSFGGTNLHSLR.Y
0.6688





IPI00254338
R.ELAITDSEHSDAEVSCTDN#GTFN#LSR.G
0.7141





IPI00255107
K.IKLRSAMYLSN#TTVTILANLVPFTL.T
0.8915





IPI00255653
R.DN#LSGLSADM*QDYGLIIDGAALSLIM*KP.R
0.7665





IPI00256859
K.EEEELAYDWSDN#NSN#ISAKR.N
0.9261





IPI00257076
K.RYGFYN#NSVIIFSSDNGGQTFSGGSNWPLRGR.K
0.9458





IPI00257239
R.ESWGQESNAGN#QTVVR.V
0.7542





IPI00257508
R.TTQRIVAPPGGRAN#ITSLG.-
0.5053





IPI00257544
R.LN#TTNAWDAAPPSLGSQPLYRSSLS.H
0.8571





IPI00257544
K.SIGPEHN#GSMVRNK.C
0.5589





IPI00257717
T.LTHATNFLNVMLQSN#K.S
0.5343





IPI00258331
M.YVDNN#RSWFMHCNSHTN#R.T
0.5311





IPI00258407
-.MEN#GSYTSYFILL.G
0.516





IPI00258462
K.DSESMSFSDLENWAVAN#SSEPQLEDAKR.E
0.5437





IPI00258993
R.VMISAGNLQLPVEAGLVEFTN#ISQK.L
0.6373





IPI00259549
K.SNGLMFTNIM*M*QNTN#PSASPEYMFSSNIEPEPK.D
0.6018





IPI00260178
R.GGLGGGYGGASGMGGITTVTVN#QSLLSPLNLEVDP.H
0.6815





IPI00260211
K.GLYQGFN#MSVQGIIIYR.A
0.5976





IPI00260230
K.YTEVTDINSVDANYN#SSVLVSGDDFGLVKLFK.F
0.7909





IPI00260367
K.TPCMPQAASN#TSLGLGDLR.V
0.9941





IPI00260715
R.GGSGGGGGGGGGGYN#R.S
0.5968





IPI00260916
R.RGASVN#CTTRTN#STPLR.A
0.8966





IPI00288960
-.M*M*QESATETISN#SSM*NQNGM*STLSSQLDAGSR.D
0.6344





IPI00289006
R.DGKEPQPSAEAAAAPSLAN#ISCFTQK.L
0.9174





IPI00289033
R.YDN#VTILFSGIVGFNAFCSKHASGEGAM*KIVNL.L
0.9169





IPI00289082
R.N#YSKSTELPGKN#ESTIEQIDK.K
0.526





IPI00289083
R.FYKFN#TSLAGDLTNLVHGSH.C
0.5808





IPI00289083
A.ENRN#PSCEVHQEPVTYTAIDPGLQDALHQCVNSR.C
0.6401





IPI00289123
R.M*WRRATVAAGNSVVQVVN#VSRLEGDDNPVQL.I
0.6161





IPI00289169
R.SMQQQETNLLAN#LTTNDAR.D
0.9053





IPI00289171
R.SITN#ASAAIAPKDNLFIRFLK.P
0.8389





IPI00289258
R.CSVGTYN#SSGAYR.F
0.5269





IPI00289301
K.IM*CLDEKIDN#FTR.Q
0.7027





IPI00289334
K.HVGNQQYN#VTYVVKER.G
0.876





IPI00289346
R.VLN#ASAEAQRAAAR.F
0.7325





IPI00289438
R.AFSQNAN#LTK.H
0.7426





IPI00289499
R.N#LTALGLNLVASGGTAKALR.D
0.5452





IPI00289561
K.KHAYCSN#LSFR.L
0.5106





IPI00289561
R.VLN#ASTLALALANLN#GSR.Q
0.9283





IPI00289709
M.N#NSQGRVTFEDVTVN#FTQGEWQR.L
0.5278





IPI00289776
K.VN#GTITFIDEIHNDDGVWLRLN.D
0.8766





IPI00289787
K.CNLCLAM*NLQGRHKCIEN#VSR.Q
0.5624





IPI00289799
K.IKRN#FSSGTIPGTPGPNGEDGVEQTAIK.V
0.8639





IPI00289802
R.HCSVN#GTWTGSDPECLVINCGDPGIPANGLR.L
0.5171





IPI00289809
K.LLKSIPLDVVLSNNN#HTEIQEISLALR.S
0.9424





IPI00289831
P.RFSILPMSHEIM*PGGNVN#ITCVAVGSPM*PYVK.W
0.9504





IPI00289866
M.MQQTPCYSFAPPN#TSLNSPSPNYQK.Y
0.6239





IPI00289880
R.GSQSYYTVAHAISEWVEKQSALLIN#GTLK.H
0.823





IPI00289914
L.SQFADN#TTYAK.V
0.931





IPI00289944
K.FIKNQHCTN#ISELSN#TSEN.D
0.9668





IPI00289961
L.LEGQDSGNSNGN#ASIN#ITDISR.N
0.8835





IPI00290032
Q.N#ITEEIPM*EVFK.E
0.8058





IPI00290033
Q.GWPRPLTPPAAGGLQN#HTVGIIVK.T
0.5019





IPI00290035
R.GSSNPLLTTEEAN#LTEK.E
0.5068





IPI00290043
Q.ALEN#HTEVQFQK.E
0.936





IPI00290135
K.AVSLSVTVPVSHPVLN#LSSPEDLIFEGAK.V
0.9684





IPI00290155
R.EHMESNLFLSCATN#QSPVEK.D
0.7117





IPI00290158
K.TQLN#SSSLQKLFR.E
0.5534





IPI00290283
R.FGYILHTDN#R.T
0.998





IPI00290283
K.M*LNN#NTGIYTCSAQGVWM*NK.V
1





IPI00290283
R.LEPEGPAPHM*LGLVAGWGISNPN#VTVDEIISSGTR.T
0.9919





IPI00290292
R.ELDLPSQDN#VSLTSTETPPPLYV.G
0.914





IPI00290328
R.YN#ATVYSQAAN#GTEGQPQAIEFR.T
1





IPI00290328
K.IHVAGETDSSNLN#VSEPR.A
0.9948





IPI00290350
V.N#LSLIFIIALGSIAGILFVTM*IFVAIKCK.R
0.6995





IPI00290391
D.DVNVEIVFLHN#ISPNLELEALFK.R
0.7585





IPI00290459
V.M*FLFQGNN#GTVLYTGDFR.L
0.9278





IPI00290546
R.KEGN#FSDLK.E
0.7401





IPI00290547
R.SYFVVVN#HSQSQDTVTTGEALNVIPGAQEKK.A
0.7896





IPI00290561
K.QNPMAN#YSSIPAEIM*DHSISPFM*R.K
0.5321





IPI00290652
K.SEEQPMDLEN#RSTANVLEETTVK.K
0.6119





IPI00290671
A.RDSN#VTLAPSGPK.G
0.7713





IPI00290837
R.EENN#ISGLNQDITDVCFSPEK.D
0.6274





IPI00290854
R.GTSGQPPEGCAAPTVIVSNHN#LTDTVQNK.Q
0.8369





IPI00290856
K.ANQQLN#FTEAK.E
0.9998





IPI00290856
I.ETKVVKEEKAN#DSNPNEESKK.T
0.5241





IPI00290889
K.EMTNEEKNIITN#LSK.C
0.625





IPI00290928
R.VFSN#VSIILFLN#K.T
0.8545





IPI00290952
T.ATHPPGPAVQLN#KTPSSSK.K
0.5596





IPI00290954
K.GVHSFYNN#ISGLTDFGEK.V
1





IPI00291003
R.SN#KTLADSLDNANDPHDPIVNR.L
0.9961





IPI00291170
T.VKGN#PSSSVEDHIEYHGHR.G
0.564





IPI00291200
M.IFETTTKN#ETIAQEDK.I
0.9155





IPI00291235
R.RFIPPARMMSTESANSFTLIGEASDGGTMEN#LSR.R
0.631





IPI00291262
R.LAN#LTQGEDQYYLR.V
1





IPI00291262
K.ELPGVCN#ETM*M*ALWEECKPCLK.Q
1





IPI00291262
R.EILSVDCSTNN#PSQAK.L
0.9997





IPI00291262
K.MLN#TSSLLEQLNEQFNWVSR.L
0.9994





IPI00291262
R.HN#STGCLR.M
0.9992





IPI00291262
K.EDALN#ETR.E
0.9978





IPI00291262
R.QLEEFLN#QSSPFYFWMNGDR.I
0.9732





IPI00291316
M.CYACN#KSITAKEALICPTCN#VTIHNR.C
0.5668





IPI00291387
K.NIGDDGGGDDNTFN#FSWK.V
0.7116





IPI00291410
K.WFN#NSAASLTM*PTLDNIPFSLIVSQD.V
0.9022





IPI00291539
K.QRM*EPLYSLN#VSVSDGLFTSTAQVHIR.V
0.9622





IPI00291596
R.QHN#NTGYIYSRDQWDPEVIENHRKK.K
0.9347





IPI00291827
R.TIGIFWLN#ASETLVEINTEPAVEYTLTQM*GPVAAKQK.V
0.9627





IPI00291834
R.SASLSSLLITPFPSPN#SSLTRSCASSYQR.R
0.757





IPI00291860
R.GPHHLDN#SSPGPGSEARGINGGPSRMSPK.A
0.6965





IPI00291866
R.DTFVN#ASR.T
0.9997





IPI00291866
R.VLSN#NSDANLELINTWVAK.N
1





IPI00291866
K.VGQLQLSHN#LSLVILVPQNLK.H
1





IPI00291866
K.M*LFVEPILEVSSLPTTN#STTNSATK.I
1





IPI00291866
R.ASSNPN#ATSSSSQDPESLQDR.G
0.9404





IPI00291867
R.SIPACVPWSPYLFQPN#DTCIVSGWGR.E
0.9998





IPI00291867
K.LISN#CSK.F
0.7403





IPI00291897
K.FSIAILPFSIKAMAEAN#VSLRRMK.K
0.8243





IPI00291910
R.CN#TTQGNEVTSILRW.A
0.5105





IPI00291916
K.HSKALNTLSSPGQSSFSHGTRN#NSAK.E
0.8113





IPI00291916
K.KRN#RSSSVSSSAASSPERK.K
0.7713





IPI00291919
K.AN#FSIGPMMPVLAGT.Y
0.9331





IPI00291922
K.ARVETQNHWFTYN#ETM*TVESVTQAVSNLALQF.G
0.8769





IPI00291929
K.TN#RSSVKTPKPVEPAASDLE.P
0.9952





IPI00291936
M.RVN#NSTMLGASGDYADFQYLK.Q
0.6561





IPI00291990
R.LLGHSPVLRN#ITNSQAPDGRR.K
0.8077





IPI00292011
R.N#GSDDPSYNGAIIVSGDQK.D
0.6457





IPI00292043
R.ISWEEYN#RTNTRVTHYLPN#VTLEYR.V
0.6417





IPI00292071
K.LEKN#ATDN#ISK.L
0.814





IPI00292218
R.GTAN#TTTAGVPCQR.W
0.9841





IPI00292218
K.GTGN#DTVLNVALLNVISNQECNIK.H
1





IPI00292218
R.AFHYN#VSSHGCQLLPWTQHSPHTR.L
0.9996





IPI00292300
P.SLLLFIN#SSSQDFVVVLLCK.N
0.9834





IPI00292323
R.NVNFN#GSAGTPVMFNKNGDAPGR.Y
0.6716





IPI00292393
K.EGLLANTM*SKMYGHENGN#SSSPSPEEK.G
0.8317





IPI00292471
R.SITKNPKIGGLPLIPIQHEGN#ATLAR.K
0.7607





IPI00292487
M.LQDIQEVLN#RSK.S
0.7645





IPI00292496
K.MSATFIGN#NTAIQELFK.R
0.9893





IPI00292499
R.IRN#ISNTVM*KVKQILGR.S
0.6243





IPI00292530
K.ICDLLVANNHFAHFFAPQN#LTNMNK.N
0.9997





IPI00292530
R.AN#LSSQALQM*SLDYGFVTPLTSMSIR.G
1





IPI00292537
K.LM*PN#FSDSFGGGSGAGAGGGGMFG.S
0.8399





IPI00292674
K.SQLGFLN#VTNYCHLAHELRLSCMERK.K
0.6708





IPI00292723
M.FEHFLLHREGMFN#DTLR.L
0.9872





IPI00292723
S.VTGN#PSNSWPSPTEPSSETGNPR.H
0.576





IPI00292737
L.PLN#ESADITFATLNTKGNEGDIVR.D
0.5968





IPI00292746
R.LN#TTNAWGAAPPSLGSQPLYR.S
0.7378





IPI00292819
R.EGELCSLLKEN#VSELRILSSGNDHGNWCIIAEKK.G
0.7925





IPI00292824
R.NTPWTPWLPVN#VTQGGARQEQR.F
0.9102





IPI00292859
K.EAPYFYN#DTVTFK.C
0.9999





IPI00292859
K.TPNGN#HTGGNIARF.S
0.5538





IPI00292907
Y.LFVIFDFLIGVLIFATIVGNVGSM*ISNM*N#ATR.A
0.7059





IPI00292928
R.TKDAGLGVYSLALLNN#VSYNVVEFSK.S
0.5167





IPI00292946
K.VTACHSSQPN#ATLYK.M
1





IPI00292946
K.TLYETEVFSTDFSN#ISAAK.Q
1





IPI00292946
K.TTTVQVPMMHQM*EQYYHLVDM*ELN#CTVLQMDYSK.N
0.9936





IPI00292950
K.DFVN#ASSK.Y
0.9968





IPI00292950
K.N#LSM*PLLPADFHK.E
0.9996





IPI00292953
R.RAELVCLN#NTEISEN#SSDLSQKLK.E
0.8791





IPI00293057
K.QVHFFVN#ASDVDNVK.A
1





IPI00293057
K.AHLN#VSGIPCSVLLADVEDLIQQQISN#DTVSPR.A
1





IPI00293086
R.NN#QTIFEQTINDLTFDGSFVK.E
0.7167





IPI00293173
R.GYLQALASKMTEELEALRN#SSLGTR.A
0.8526





IPI00293183
M.QAPAFRDKKQGVSAKNQGAHDPDYEN#ITLAFK.N
0.6116





IPI00293203
M.FTMATAEHRSN#SSIAGK.M
0.6155





IPI00293274
R.LPQDGDN#VTVENGQLLLLDTN#TSILNLLHIK.G
0.7351





IPI00293274
R.WQIVPN#ASSPFGFWS.Q
0.7022





IPI00293328
R.ETGDN#FSDVAIQGGIMGIE.I
0.5343





IPI00293381
M.GMIFTLFTIN#VSTDM*R.H
0.9229





IPI00293426
K.RLAYLLQQTDEYVAN#LTELVPQHK.A
0.685





IPI00293471
M.NKWAGLLGPISN#HSFGGSFRTASNK.E
0.909





IPI00293471
K.LFSDIEN#ISEETSAEVHPIS.L
0.9214





IPI00293471
K.LSNNLNVEGGSSENN#HSI.K
0.6898





IPI00293520
K.SRMAIWAATDHNVDN#TTEIFR.E
0.9955





IPI00293565
K.VLLLHEVHAN#DTGSYVCYYK.Y
0.9993





IPI00293575
K.SVN#VSSNLVTQEPSPEETSTKR.S
0.6597





IPI00293583
K.AGHSNKYLKM*AN#NTKELEVCEQANK.L
0.9328





IPI00293590
K.VLAAKVLNLVLPN#LSLGPIDSSVLSR.N
0.7033





IPI00293602
R.NYQRIEQN#LTSTASSGTNVHGS.P
0.7657





IPI00293616
R.VGNLGLATSFFNEKNM*N#ITK.D
0.7548





IPI00293714
I.DN#TTNSMKKTK.S
0.6257





IPI00293714
S.LPMSIN#VTDDIVYISTHPEASSR.T
0.8565





IPI00293748
K.FLTEVEKN#ATALYHVEAFK.T
0.9999





IPI00293748
R.AN#STSDEL.-
0.6105





IPI00293773
R.AGM*VYMAGLVFAVGGFN#GSLRVR.T
0.9811





IPI00293849
I.TN#LSPYTN#VSVKLILMNPEGRK.E
0.502





IPI00293921
R.DLN#VSVTHLIAGEVGSKK.Y
0.5572





IPI00293925
R.VELEDFNGN#R.T
0.9981





IPI00293971
R.VINFYAGAN#QSM*N#VTCAGK.R
0.5256





IPI00294004
L.VSGN#NTVPFAVSLVDSTSEK.S
0.8514





IPI00294065
R.LEQQM*NSASGSSSN#GSSIN#MSGIDNGEGTRLR.N
0.9073





IPI00294073
R.FRSSGMTLDN#ISR.A
0.5515





IPI00294125
K.EN#ETESLQILNAK.T
0.6675





IPI00294193
N.QLVDALTTWQN#K.T
0.9572





IPI00294193
K.LPTQN#ITFQTESSVAEQEAEFQSPK.Y
1





IPI00294193
R.NQALN#LSLAYSFVTPL.T
1





IPI00294193
K.AFITN#FSMNIDGMTYPGIIK.E
0.9988





IPI00294395
K.EYESYSDFERN#VTEK.M
1





IPI00294486
K.SN#ISPNFNFMGQLLDFER.S
0.9916





IPI00294578
M.NMGSDFDVFAHITN#NTAEEYVCR.L
0.6102





IPI00294728
K.LDDISSN#YTESFSTLDENDLLN#PSEDIIAVQLK.F
0.9495





IPI00294728
K.QKPSGLTRSTSMLISSGHN#KSSNSLK.L
0.7527





IPI00294739
K.KEWN#DSTSVQN#PTRLR.E
0.7366





IPI00294744
R.SQANGAGALSYVSPN#TSK.C
0.7598





IPI00294776
R.HDYILLPEDALTN#TTR.L
0.992





IPI00294776
R.APSN#VSTIIHILYLPEDAK.G
0.813





IPI00294787
M.PPVSLNHN#LTTPFTSQAGENSLF.M
0.7359





IPI00294798
R.TKSNSLSEQLAIN#TSPDAVK.A
0.9417





IPI00294816
M.VNN#VTPARAVVSLINGGQR.Y
0.5376





IPI00294879
M.QKAFN#SSSFNSNTFLTR.L
0.712





IPI00294903
K.KRGTFIEFRNGMLN#ISPIGRSC.T
0.5352





IPI00294943
M.QQHN#MSWIEVQFLK.K
0.5639





IPI00294997
M.VTEMYSGPCVAM*EIQQNN#ATK.T
0.7213





IPI00295081
R.VSGLM*M*AN#HTSISSLFER.T
0.7492





IPI00295182
K.GGAVAADGRIEPGDM*LLQVNEINFEN#M*SN.D
0.8753





IPI00295339
K.AYSWN#ISR.K
0.5725





IPI00295376
-.M*DQNQHLN#KTAEAQPSENK.K
0.5571





IPI00295380
R.VVNLEALQMLSVN#TTLEELK.I
0.9781





IPI00295387
R.N#DSESSGVLYSRAPTYFCGQTLTFR.Q
0.7118





IPI00295461
K.DDNLEHYKN#STVMAR.A
0.9998





IPI00295502
H.LRQM*GVTEWSVN#GSPIDTLR.E
0.546





IPI00295503
K.MM*N#DSILRLQTWDEAVFR.E
0.5128





IPI00295640
K.SLKHQNILLEVDDFENRN#GTDGLSYNGAIIVSGK.Q
0.6525





IPI00295672
M.KNKRN#VTEFVLTGLTQNPKM*EK.V
0.7847





IPI00295743
K.MADALLFGNFGVQN#ITAAIQLYESLAK.E
0.8936





IPI00295832
M.TLSITSGM*PNN#FSEM*PQQSTTLNLWR.E
0.7745





IPI00295988
P.GNLPPSMN#LSQLLGLRK.N
0.5407





IPI00296053
R.INKLM*N#ESLMLVTALNPHIGYDK.A
0.5051





IPI00296063
K.N#ISNPEAYDHCFEKK.E
0.5907





IPI00296099
G.EDTDLDGWPNENLVCVAN#ATYHCKK.D
0.7692





IPI00296099
K.VVN#STTGPGEHLR.N
1





IPI00296099
K.VSCPIM*PCSN#ATVPDGECCPR.C
0.9875





IPI00296099
K.GCSSSTSVLLTLDNNVVN#GSSPAIRTNYIGHKTK.D
0.5429





IPI00296161
K.FIHNENGAN#YSVTATR.S
0.9775





IPI00296165
N.LLPICLPDN#DTFYDLGLM*GYVSGFGVM*EEK.I
1





IPI00296165
K.EHEAQSN#ASLDVFLGHTNVEELM*K.L
1





IPI00296165
K.MLLTFHTDFSNEEN#GTIM*FYK.G
1





IPI00296165
R.CN#YSIR.V
0.9967





IPI00296170
K.MVSHHN#LTTGATLINEQWLLTTAK.N
1





IPI00296170
K.NLFLN#HSEN#ATAK.D
1





IPI00296211
R.DKYLHTNCLAALAN#M*SAQFR.S
0.5587





IPI00296211
L.LLLLVLAN#LTDASDAPNPYR.Q
0.8206





IPI00296215
K.LAAKCLVMKAEMN#GSK.L
0.503





IPI00296311
R.YMLASPDVTSILLTYN#LSNTNSCN#VSPKK.E
0.9247





IPI00296318
Q.CSSLGAESILSGKEN#SSALSPNHR.I
0.539





IPI00296362
R.SPLQACENLAMNEGGPPTEN#NSLILEENK.I
0.5479





IPI00296421
R.LRN#SSSFSM*DDPDAGAMGAAAAEGQ.A
0.8203





IPI00296449
R.TTSTLSLSAEDSQSTESN#MSVPK.K
0.9536





IPI00296449
K.ENN#LTEDNPN#LSM*AQRR.H
0.603





IPI00296485
M.VDPEM*LPPKTARQTEN#VSR.T
0.9937





IPI00296495
K.CIRCAVVGNGGILN#GSR.Q
0.9495





IPI00296527
K.KNSDGM*EAAGVQIQM*VN#ESLG.Y
0.9403





IPI00296534
R.NCQDIDECVTGIHN#CSIN#ETCFNIQGGFR.C
0.9998





IPI00296534
R.CATPHGDN#ASLEATFVK.R
1





IPI00296573
R.SPASERRPLGN#FTAPPTYTETLSTAPLASWVR.S
0.6423





IPI00296594
K.DPPSEANSIQSAN#ATTKTSETN#HTSR.P
0.9321





IPI00296608
R.N#YTLTGR.D
0.9819





IPI00296608
K.INNDFNYEFYN#STWSYVK.H
1





IPI00296776
K.ERVEN#YSN#VSIHLKNP.E
0.6446





IPI00296845
K.SSSTPFPFRTGLTSGN#VTENLQTYIDK.S
0.7546





IPI00296858
R.KTENAYNAIINGEAN#VT.G
0.523





IPI00296866
K.EIRVLEFRSPKEN#DSGVDVYYAVTFNGE.A
0.7294





IPI00296869
K.ATN#ATLDPR.S
0.8042





IPI00296936
M.VSFVSN#YSHTANILPDIENEDFIKDCVRIHNKFR.S
0.78





IPI00296999
M.HLTTLCN#TSLDN#PTQR.N
0.7143





IPI00297089
K.DISSSEMTN#PSDTLNIETLLN#GSVKRVSENNGNGK.N
0.5533





IPI00297124
N.PPHN#LSVINSEELSSILK.L
0.5489





IPI00297124
R.ETHLETN#FTLK.S
0.9988





IPI00297210
K.AGKPVVAAPGAGN#LTKFEPR.A
0.6356





IPI00297223
H.SDHDN#STSLNGGK.R
0.6658





IPI00297242
R.VLN#TSSLESATDEAGSPLAAAAAAAAAER.C
0.854





IPI00297252
R.LFPN#ASQHITPSYNYAPNPDK.H
0.7442





IPI00297257
T.RGRSISFPALLPIPGSN#RSSVIM*TAK.P
0.5512





IPI00297263
R.ALLSITDN#SSSSDIVESSTSYIK.I
0.7064





IPI00297263
K.SHAASDAPEN#LTLLAETADAR.G
1





IPI00297263
R.SYSESSSTSSSESLN#SSAPR.G
0.995





IPI00297263
R.SN#ISSYDGEYAQPS.T
0.6318





IPI00297277
K.NWIALIPKGN#CTYR.D
0.8069





IPI00297366
K.KM*LYRDFN#MTGWAYK.T
0.6371





IPI00297570
K.EEVQN#LTSVLNELQEEIGAYDYDELQSR.V
0.9997





IPI00297570
R.LPHPWSGTGQVVYN#GSIYFNK.F
0.9999





IPI00297570
K.VQN#M*SQSIEVLDR.R
0.9999





IPI00297570
K.SM*VDFM*NTDN#FTSHR.L
0.999





IPI00297622
K.SDNN#YSTPNER.G
0.5113





IPI00297626
A.MAYDLLPIEN#DTYK.Q
0.9433





IPI00297633
K.ENMN#LSEAQVQALALSR.Q
0.7336





IPI00297633
R.RSSEN#M*TAEPMSESKLNTLVQK.L
0.6802





IPI00297646
R.LM*STEASQN#ITYHCK.N
0.8682





IPI00297671
R.N#LSEGNNAN#YT.E
0.6528





IPI00297723
K.DRGVTRFQEN#ASEGKAPAEDVFKK.P
0.8071





IPI00297763
M.N#VSGGPITREASKEI.P
0.7717





IPI00297763
K.TPSVSPN#ITQLFQK.Q
0.7169





IPI00297763
M.N#YSVSAGLVVGIFIGFQK.K
0.5787





IPI00297897
M.QELSNILN#LSYK.Q
0.9162





IPI00297910
R.THHILIDLRHRPTAGAFN#HSDLDAELR.R
0.5326





IPI00297921
R.ISCRPQTQISNNYGNNPLN#SSLLPQK.Q
0.5078





IPI00297985
R.EIVSQTTATQEKSQEELPTTN#NSVSK.E
0.6891





IPI00298031
K.ISLKIQNCRN#VTSLPCLSLR.K
0.5194





IPI00298031
R.APTFLMN#QTDTHIVEK.M
0.9964





IPI00298216
K.DTNVQVLM*VLGAGRGPLVN#ASLR.A
0.6096





IPI00298285
M.EGTATCN#GSGSDTCAQCAHFR.D
0.6392





IPI00298337
R.SLIASGLYGYN#ATLVGVLMAVFSDK.G
0.8342





IPI00298347
K.KNPMVETLGTVLQLKQPLN#TTR.I
0.5988





IPI00298464
K.M*AAVTLLALAYTQGPVLFN#LTFK.I
0.7319





IPI00298497
R.GTAGNALMDGASQLM*GEN#R.T
0.9775





IPI00298536
R.DVMLEN#YSNLVSLGLLGPKPDTFSQLEKR.E
0.7354





IPI00298673
E.ENTDDN#ITVQGEIRKEDGM*ENLK.N
0.6622





IPI00298828
R.DTAVFECLPQHAMFGN#DTITCTTHGN#WTK.L
0.9998





IPI00298828
R.VYKPSAGN#NSLYR.D
1





IPI00298828
K.LGN#WSAMPSCK.A
0.9996





IPI00298853
K.LCDN#LSTK.N
0.995





IPI00298860
R.TAGWNVPIGTLRPFLN#WTGPPEPIEAAVAR.F
0.9959





IPI00298888
K.NLN#YSVPEEQGAGTVI.G
0.5438





IPI00298902
K.KQSNNDLFQVN#STSDDEIPR.K
0.7548





IPI00298902
-.M*ASQLQEKCIAFIVDN#FSK.I
0.9778





IPI00298902
K.SIHEQDTNVN#NSVLKK.V
0.8003





IPI00298920
K.TGGDN#KTLLHLGSSAPGK.E
0.8688





IPI00298971
R.N#ISDGFDGIPDNVDAALALPAHSYSGR.E
1





IPI00298971
K.NN#ATVHEQVGGPSLTSDLQAQSK.G
1





IPI00298971
K.N#GSLFAFR.G
0.9995





IPI00298980
N.#TSAPPAVSPN#ITVLAPGK.G
0.6924





IPI00298994
R.AATAPLLEAVDN#LS.A
0.5498





IPI00299059
R.VTWKPQGAPVEWEEETVTN#HTLR.V
0.9543





IPI00299059
R.RYHIYEN#GTLQIN#R.T
0.9948





IPI00299122
M.ITMVCCAHSTNEPSN#M*SYVK.E
0.6482





IPI00299158
R.VEDEGN#YTCLFVTFPQGSR.S
0.9958





IPI00299162
F.GSNMGN#GTVFLGIPGDNK.Q
0.5758





IPI00299162
R.IRVDLPLGSPAVN#CTVLPGGIS.V
0.7538





IPI00299299
V.LNKNGM*VEFSVTSN#ETITVSPEYVGSR.L
0.8532





IPI00299377
R.SVN#GTTSDCLVSLVTSVTN.V
0.5324





IPI00299435
R.STERN#VSVEALASALQLLAR.E
1





IPI00299435
R.QGGVN#ATQVLIQHLR.G
0.8233





IPI00299435
K.DAN#ISQPETTKEGLR.A
0.548





IPI00299503
K.LGTSLSSGHVLMN#GTLK.Q
0.9998





IPI00299503
K.LNVEAAN#WTVR.G
1





IPI00299503
K.FHDVSESTHWTPFLN#ASVHYIR.E
1





IPI00299503
R.N#LTTSLTESVDR.N
0.9996





IPI00299503
R.NIN#YTER.G
0.9524





IPI00299503
R.TLLLVGSPTWKN#ASR.L
0.5773





IPI00299507
K.DLQRSLPPVM*AQN#LSIPLAFACLLHLANEK.N
0.5463





IPI00299512
R.YMLMLSFN#NSLDVAAH.L
0.524





IPI00299526
K.QVPLIPDLN#Q.T
0.7161





IPI00299526
K.LRIFYQFLYNN#NTR.Q
0.6424





IPI00299547
K.SYN#VTSVLFR.K
1





IPI00299594
K.RGPECSQN#YTTPSGVIK.S
1





IPI00299594
K.EGFSAN#YSVLQSSVSEDFK.C
1





IPI00299619
K.TSATSVN#LSLLTADLYSLFCGLFL.F
0.5243





IPI00299635
K.FVLNSN#ITNIP.Q
0.5209





IPI00299664
R.VQALDPDEGSNGEVQYSLSN#STQAELR.H
0.7289





IPI00299778
R.VSTVYANN#GSVLQGTSVASVYHGKILIGTVFXK.T
0.603





IPI00299831
K.N#ASDGALMDDNQNEWGDEDLETKK.F
0.6047





IPI00299884
K.LLM*ENPYEGPDSQKEKDSN#SSK.Y
0.9439





IPI00300020
K.KVLVAPPPDEEAN#ATSAVVSLLN#ETVTEVPEETK.M
0.8428





IPI00300078
K.NN#KSDTLPLATRYN.V
0.9648





IPI00300078
R.GNLN#FTCNGNSVISPVGNR.V
0.9113





IPI00300078
K.RFEISCN#LSLDAMEEFLNRRK.M
0.6269





IPI00300117
P.SSEVMN#KSRCESLLFN#ESMLWENAK.M
0.6816





IPI00300117
K.ELQEGN#ETDEAK.T
0.6902





IPI00300173
K.LALRN#NSASTTQHLR.L
0.5401





IPI00300376
S.AMINSNDDNGVLAGN#WSGTYTGGR.D
0.8423





IPI00300384
G.PTQCVN#CSQFLR.G
0.5345





IPI00300408
M.KFRN#SSVAMGASLSCSEYSLK.V
0.7599





IPI00300465
K.LANN#GTVLR.A
0.9589





IPI00300573
R.QFPKLN#ISEVDEQVR.L
0.5062





IPI00300585
K.EDGSGSAYDKESMAIIKLN#NTTVLYLK.E
0.796





IPI00300599
K.VPLSHSRSN#DTLYIPEWEGR.A
0.8356





IPI00300631
R.KRNVDSSGN#KSVLMERL.K
0.5679





IPI00300813
M.IN#FSAFLGAATMYTRYK.I
0.5375





IPI00300838
R.RLLIKKMPAAATIPAN#SSDAPFIR.P
0.5065





IPI00300843
K.QLLRDLSGLQGM*N#GSIQAK.S
0.5379





IPI00300936
K.KKDSLHGSTGAVN#ATRPT.L
0.5997





IPI00301021
K.DLNGNVFQDAVFN#QTVTVIER.E
0.8101





IPI00301031
K.HSSGTSN#TSTAN#RSTHNELEK.N
0.9056





IPI00301107
M.GRVLLQN#TSFFSSLLNEMAHK.F
0.8501





IPI00301143
K.SLPNFPN#TSATAN#ATGGR.A
0.9999





IPI00301143
R.EHYN#LSAATCSPGQM*CGHYTQVVWAK.T
1





IPI00301180
-.MPNN#LTDCEDGDGGANPGDGNPK.E
0.8099





IPI00301180
K.NM*ALFEEEMDTSPMVSSLLSGLAN#YTNLPQGSR.E
0.627





IPI00301248
K.QPTPIAN#TSSQQAVFTSARQLPSAR.T
0.953





IPI00301248
K.DQVN#GTSEDSADGSTVGTAVSSSDDADLPPP.P
0.6801





IPI00301288
R.CGEPPSIMNGYASGSN#YSFGAMVAYSCNK.G
0.993





IPI00301480
K.HPLTAN#ASR.S
0.9126





IPI00301517
K.LLYLTTTN#ESGVFITG.H
0.8678





IPI00301548
M.SSKHN#MSGGEFQGKR.E
0.7001





IPI00301548
M.SGTTTSTNTFPGGPIATLFN#M*SMSIK.D
0.5976





IPI00301610
R.KMAHPAMFPRRGSGSGSASALNAAGTGVGSN#ATSSEDFPPP.S
0.7245





IPI00301793
A.AQN#NTVTVPK.N
0.846





IPI00301793
R.ISKLIN#SSDELQDNFR.E
0.8615





IPI00301968
R.DVMLEN#YSHLVSVGYLVAK.P
0.684





IPI00302029
R.EVN#STDWDSKMGFWAPLVLSHSR.R
0.5398





IPI00302311
-.M*EN#FSLLSISGPPISSSALSAFPDIMF.S
0.7655





IPI00302329
K.RQAEEAEEQSNAN#LSKFR.K
0.7454





IPI00302383
M.NIMSTLQWAVN#SSIDVDSLMRSVSR.V
0.7038





IPI00302409
P.AAEHFN#YSVMVDIRELIEVDDVM.E
0.7079





IPI00302448
R.DGQLLPSSN#YSNIK.I
0.9998





IPI00302453
K.SFGSPPLAVSN#VSAAVMVLMAPRG.R
0.6889





IPI00302503
K.N#DSLIQN#DSILESLLEVL.R
0.7389





IPI00302557
K.EECRLLNAPPVPPRGGN#GSGR.L
0.528





IPI00302592
G.LN#TTGVPASLPVEFTIDAK.D
0.7334





IPI00302652
R.IDRM*FPEMSIHLSRPN#GTSAM*LLVTLGK.V
0.5906





IPI00302717
K.KLSN#FSFLTHR.Q
0.7542





IPI00302807
R.TSEHQVDLKVDPSQPSN#VSHKLWTAA.G
0.6753





IPI00302965
R.N#ASLSQSPR.V
0.9955





IPI00303040
K.WTN#LSDPMPVGQMGTVK.Y
0.7499





IPI00303053
R.ERTSSSIVFEDSGCDN#ASSK.E
0.5301





IPI00303068
K.FLAEHPN#VTLTISAARLYYYR.D
0.917





IPI00303112
K.LELNPHTVEN#VTKNEDSM*TGIEVEKWTQNKK.S
0.5739





IPI00303117
R.FLLNDN#LTLPPEMYVYSTNSDHLPM*TSSFR.K
0.9436





IPI00303135
K.SEEN#STVFSHLM*K.Y
0.9301





IPI00303157
M.ILN#LTQSSGFNGFTPLVTLLLR.H
0.8116





IPI00303163
K.GIAILN#TSVAPMLNPFIYTLR.N
0.9001





IPI00303283
R.AKWDTANNPLYKEATSTFTN#ITYR.G
0.5207





IPI00303313
K.N#VTLILDCKKK.T
0.7314





IPI00303325
K.AGN#ETQISEFLLLGFSEK.Q
0.8122





IPI00303335
K.YRTKIETLN#FTPVDDRVDYVTAK.Q
0.6984





IPI00303335
M.PDTPDILLAKSNSAN#ISQKLYTK.G
0.5824





IPI00303389
-.M*VLASGN#SSSHPVSFILLGIPGLESF.Q
0.9163





IPI00303402
K.AIELLM*ETAEVEQNGGLFIMN#GSR.R
0.5426





IPI00303431
-.MNLDSFFSFLLKSLLM*ALSN#SSWR.L
0.7922





IPI00303452
R.N#LSTCFSSGDL.F
0.7174





IPI00303455
N.VGQN#TTR.F
0.9348





IPI00303458
-.M*TVRNIASICNMGTN#ASALEK.D
0.7048





IPI00303463
M.DTTISIN#NTVITPMLNPIIYSLR.N
0.9337





IPI00303553
M.TTENPN#QTVVSHFFLEGLR.Y
0.9434





IPI00303560
K.EDSGKIKLLLHWPEDILPDVWVN#ESER.H
0.6882





IPI00303581
M.IILAGIN#FTYSLTVIIISYLFILIAILRM*R.S
0.5177





IPI00303582
R.RN#CTLVTEFILLGLTS.R
0.8218





IPI00303583
R.VKKM*AMFVVAGFN#LSSSLFIILLSYLFIFAAIFR.I
0.8499





IPI00303587
K.HPMAN#ITWMAN#HTGWSDFILLGLFR.Q
0.5496





IPI00303699
K.KQPGQPRPTSKPPASGAAAN#VSTSGITPGQAAAIASTTIM*VPF.G
0.5648





IPI00303813
K.CSEN#ATMTLPGIHPPTLNQIM*DWICLLLDAN#FTV.V
0.6397





IPI00303868
R.LNYLLRVN#GSEQTVVAFFIM*PARTNNFN.V
0.839





IPI00303875
-.M*N#NTAASPMSTAT.S
0.9316





IPI00303963
K.LTDTICGVGN#M*SAN#ASDQER.T
1





IPI00303963
K.QSVPAHFVALN#GSK.L
0.9995





IPI00303963
R.LGSYPVGGN#VSFECEDGFILR.G
0.9985





IPI00303963
K.TMFPN#LTDVR.E
0.9745





IPI00303963
K.DHEN#GTGTNTYAALNSVYLMM*NNQM*R.L
0.6754





IPI00303980
K.RFN#GSESIKSSWN#ISVVKFLLEK.L
0.8393





IPI00304023
-.M*N#ISGSSCGSPNSADTSSDFK.D
0.5777





IPI00304023
S.SNKQILINKN#ISESLGEQN#R.T
0.6867





IPI00304030
R.VHLTPVEGVPDSDYIN#ASFINGYQEK.N
0.9971





IPI00304379
R.NKESSDQTGIN#ISGFENK.I
0.889





IPI00304379
K.CESDN#TTNGCGLESPGNTVTPVNVNEVK.P
0.7172





IPI00304452
K.SSLSASTNPELGSN#VSGTQTYPVVTGR.D
0.6096





IPI00304481
R.THGRN#GTENINHR.G
0.8711





IPI00304481
R.RHN#SSDGFDSAIGRPNGGNFGRKEK.N
0.6208





IPI00304527
K.EVNSCTTGSSN#STIIGSQGSETPK.E
0.5151





IPI00304587
R.KLLFLSPDLELN#SSSSHNT.L
0.6322





IPI00304654
R.N#STDENFHASLMSEISPISTSPEISEASLM*SNLP.L
0.7347





IPI00304661
K.FHHLIPAHTFTN#ISTKNPQGSK.S
0.5884





IPI00304670
R.TPM*N#SSWLPGSPMPQAQSPEEGQR.P
0.7905





IPI00304706
H.RVLHNSLGN#ISM*LPCSSFTPNWPVQNPDSR.K
0.5641





IPI00304710
K.IM*N#LTEFSM*VDGMWQAQGYPRNR.L
0.8813





IPI00304849
R.RHKDM*DVDILALVN#DTVGTM*M*TC.A
0.9665





IPI00304895
R.QLN#TSDENGKEELFSLK.D
0.5674





IPI00304911
K.NFINQGPYEN#RSMFESLDLSWK.L
0.7486





IPI00304926
K.HVTM*DQVGTFAGLLIGLAQLN#CSELKLK.R
0.9847





IPI00304972
V.KEM*HTCTVEGCN#ATFPSR.R
0.9354





IPI00304992
K.HSGGGGGGGGGGGADPAWTSALSGN#SS.G
0.8687





IPI00305022
-.M*ILSN#TTAVTPFL.T
0.6979





IPI00305349
P.SSLIQAN#VTVGTCSGFCSQKEFPLAILR.G
0.6627





IPI00305349
R.SLVPTLREM*VAFLN#VSVSEER.L
0.5169





IPI00305374
K.TGEDEDEEDNDALLKEN#ESPDVRR.D
0.848





IPI00305383
K.TIAQGN#LSNTDVQAAKNK.L
0.726





IPI00305442
M.LENPLN#STQWM*NDPETGPVMLQISR.I
0.5715





IPI00305457
K.ADTHDEILEGLNFN#LTEIPEAQIHEGFQELLR.T
1





IPI00305457
R.QLAHQSN#STNIFFSPVSIATAFAMLSLGTK.A
1





IPI00305457
K.YLGN#ATAIFFLPDEGK.L
1





IPI00305461
K.VVN#NSPQPQNVVFDVQIPK.G
1





IPI00305461
K.GAFISN#FSMTVDGK.T
1





IPI00305461
K.ENIQDN#ISLFSLGMGFDVDYDFLK.R
0.8276





IPI00305622
R.VISAM*VNSLDDNGVLIGN#WSGDYSR.G
0.5299





IPI00305656
K.LETKFKSGLN#GSILAER.E
0.5948





IPI00305698
K.EKVEN#GSETGPLPPELQPLLEGEVK.G
0.698





IPI00305715
K.VSGYLNLLANTIDN#FTHGLAVAASFLVSK.K
0.5026





IPI00305725
R.AVNALPQN#MTSQMF.S
0.6692





IPI00305894
R.TSRKSALRAGN#DSAM*ADGEGYR.N
0.8772





IPI00305901
K.EEQHAN#TSANYDVELLHHK.D
0.8009





IPI00305945
R.NWAHN#SSVEASSNLEAPGNER.K
0.7208





IPI00305945
K.CPYSQEAMQRALIGRCQN#VSALPK.G
0.8236





IPI00306152
M.EVNGQNFEN#ITFMK.A
0.7124





IPI00306196
F.EN#KTNLKNQLILGVMGVDVSLEDIKR.L
0.8677





IPI00306196
K.IDVNSWIEN#FTK.T
1





IPI00306196
K.ISDN#NTEFLLNFNEFIDR.K
0.8316





IPI00306346
R.LLAEGVCDN#DTVPSVSSINR.I
0.5678





IPI00306400
R.ETQAIN#SSLSTLGLVIMALSNK.E
0.7104





IPI00306471
K.EAN#PTPLTPGASSLSQLGAYLDSDDSN#GSN.-
0.5005





IPI00306599
R.SCLSCPEN#TSTVKR.G
0.8955





IPI00306642
K.AN#ASEKLGVLTSR.E
0.7759





IPI00306718
R.IYIEDN#ISNSNEVEMEEK.G
0.5926





IPI00306718
R.EGKELLLYFDASLEITN#VTQK.I
0.7916





IPI00306723
R.NLN#DSSLFVSAEEFGHLLDENM*GSK.F
0.6316





IPI00306845
K.WSM*VCLLMN#GSSHSPTAI.N
0.925





IPI00306851
R.KVLIN#NSLDEPR.A
0.827





IPI00306869
K.SLN#DSIQPDPLCLHN#SSLFALQNLQP.W
0.9805





IPI00306929
M.SLDFN#ATGRITAAQLQTMLLEKSR.V
0.8867





IPI00306967
R.YGEEYGN#LTRPDITFTYFQPK.P
1





IPI00306984
R.IVDGIEDGN#SSEESQTFDFGSER.I
0.764





IPI00307017
R.ELRSALLEFACTHNLGN#CSTTAMK.L
0.5199





IPI00307093
K.IIYPKN#HSIEVQ.L
0.9248





IPI00307150
K.AVTVMM*DPN#STQRYR.L
0.665





IPI00307317
R.FGLLFNQEN#TTYSK.T
0.7814





IPI00307405
R.RTSMHSSLN#TSPNQQPD.T
0.5914





IPI00307591
R.GKRM*RPNSNTPVN#ETATASDSKGTS.N
0.7204





IPI00307591
R.KNKPLSDMELN#SSSEDSK.G
0.8995





IPI00307592
K.VSQQLGLDAPN#GSDSSPQAPPPR.R
0.7343





IPI00307611
S.GNKVSITTTPFEN#TSIKTGPARR.N
0.5148





IPI00307611
R.SFSCLN#RSLSSGESLPGSPTHSLSPR.S
0.6572





IPI00307649
R.LHNGN#ASPPR.V
0.7793





IPI00307660
R.CFLQLQPDN#STLTWVKPTTASPASSKAK.L
0.6972





IPI00307665
T.AANN#LSVSNSASSLQK.D
0.7301





IPI00307713
R.KPPLFNMNAM*SALYHIAQN#DSPTLQSNEWTDSFR.R
0.6905





IPI00307829
R.AAGSAQGNNQACN#STSEVK.D
0.7026





IPI00328090
M.TN#TSYSEPAQNSKLSLK.Q
0.5474





IPI00328094
W.VSREPALLCTFPN#PSAPRK.D
0.7148





IPI00328115
P.FLSDIHN#ISTLK.I
0.7296





IPI00328131
R.STVGLSLISPNN#MSFATK.K
0.578





IPI00328142
K.EALGSVVAHSTFSAMKANTMSN#YTLLPPSLLDHR.R
0.5048





IPI00328147
K.RTIN#SSQEPAPGMKPNWPRSR.Y
0.6458





IPI00328183
R.GSGAVAEGN#RTEAGSQDYSLLQAYYSQESK.V
0.676





IPI00328183
K.N#ESSPAPPDSDADK.L
0.6272





IPI00328195
R.YLLQNTALEVFMAN#R.T
0.9065





IPI00328195
R.CYVNGQLVSYGDMAWHVNTN#DSYDK.C
0.7676





IPI00328195
K.SM*IN#TTGAVDSGSSSSSSSSSFVNGATSK.N
0.6068





IPI00328207
K.QN#NSYWR.E
0.6204





IPI00328226
C.YEYFHQDDHNN#LTDK.H
0.5659





IPI00328267
R.NRN#LSGGVLM*GFMLNR.I
0.8592





IPI00328309
K.GLAQPPQAYFN#GSLPPQTVGHQAHGR.E
0.5042





IPI00328318
K.DENSIN#GTPDITVEIR.E
0.6536





IPI00328355
K.ENKGDNNCNHNDPLYEN#SS.-
0.804





IPI00328365
A.SGPVILSELHPICN#KSILR.Q
0.9445





IPI00328434
M.SLFLSN#LSTN#DSSLWK.E
0.914





IPI00328450
R.FN#NSLLPTEPSQQLQAYVAWVNAQLKKR.P
0.8225





IPI00328460
K.EYVKSEVIKLLPNAN#GSNVQLQLK.F
0.7791





IPI00328493
K.GLEWIGYIYYSGSTNYN#PSLKSR.V
0.6115





IPI00328550
K.YRCN#DTIPEDFQEFQTQNFDRFDN.-
0.9769





IPI00328555
R.NLLETGLN#VSDTVTLPTAPNM*NSEPTLQPQTGEITNR.M
0.6081





IPI00328555
M.DLTLN#SSTATPVSPGSVIK.E
0.885





IPI00328584
R.ASAGLN#SSATSTAN#NSRCE.G
0.7296





IPI00328609
R.SQILEGLGFN#LTELSESDVHR.G
1





IPI00328609
K.DFYVDEN#TTVR.V
1





IPI00328609
K.FLN#DTMAVYEAK.L
0.9998





IPI00328609
D.GESCSN#SSHQQILETGEGSPSLK.I
0.998





IPI00328629
K.KPKGINSN#STAN.L
0.8143





IPI00328658
M.TN#YSFHCNVCHHSGNTYFLR.K
0.9698





IPI00328704
K.EQYQVLIQAKDMGGQLGGLAGTTIVN#ITLTDVN.D
0.5168





IPI00328706
R.N#SSLVLHHR.T
0.7457





IPI00328715
K.SGKGDSTLQVSSGLNEN#LTVNGGGWNEK.S
0.5142





IPI00328736
K.SNGLMFTNIMMQNTN#PSASPEYMFSSNIEPEPKD.L
0.6152





IPI00328746
R.ARGN#SSSNHLYGVAEAGAPPADPSTLYR.D
0.6646





IPI00328752
R.AWHN#LTVLATELDSSAQASR.V
0.6333





IPI00328762
M.SGTLVMLLN#DSADLRDLATSMDSIVK.L
0.61





IPI00328762
R.TNGDILVLYN#LSK.H
0.8388





IPI00328809
K.VELPPPDLGPSSALN#QTLMLLR.E
0.9487





IPI00328911
L.KDENTISPYEMCSSGLVQALLTVLNN#VSIFRATK.Q
0.7087





IPI00328911
K.EAASQRPLSSSASNRLSVSSLLAAGAPM*SSSASVPN#LSSR.E
0.5238





IPI00328943
K.AQNGIAIMVYTN#SSNTLYWELNQAVR.T
0.9689





IPI00328960
K.TPASN#ISTQVSHTKLSVEAPDSK.F
0.764





IPI00329007
K.GFN#WSSTLTKHR.R
0.884





IPI00329028
D.AKAQLALSSSAN#QSK.E
0.6857





IPI00329038
A.GLGNGVLPN#VSEETVSPTR.A
0.7932





IPI00329054
R.LCQTCYPLFQQVVSKMDN#ISR.A
0.974





IPI00329070
R.TESQLTPCIRN#VTSPTR.Q
0.5361





IPI00329083
M.QTCGN#VSNQFQLGTCR.L
0.797





IPI00329130
M.AN#VTWPQGPFTTWSTTGDAPV.I
0.639





IPI00329192
R.HVN#LSSLVSCLCVNLCSPYLLLRR.A
0.5882





IPI00329205
K.EPVGCVNN#ISFLASLAGSTSR.N
0.8038





IPI00329244
K.DFAN#MTSLVDLTLSR.N
0.6419





IPI00329264
K.VSIIPPIALN#STDSD.G
0.5697





IPI00329318
S.GEKDESEVISQN#ETCSPAEVESNEK.D
0.8434





IPI00329345
K.GGM*NGYHVNGAIN#DTESVDSLSEGLETLSIDAR.E
0.8529





IPI00329351
K.NIGAKLVQDVAN#NTNEEAG.D
0.8142





IPI00329367
R.LDLSGNALTEDM*AALMLQN#LSSLR.S
0.8238





IPI00329420
R.SKDGPSYFTVSFN#RTFLMMITNK.A
0.5126





IPI00329472
-.MDPN#CSCSTSSSCTCTTSSKSR.E
0.682





IPI00329488
R.SN#STSSMSSGLPEQDRM*AM*TLPR.N
0.9182





IPI00329528
R.RQAPIN#FTSRLNRR.A
0.5127





IPI00329536
N.N#ESSSEGFICPQCMK.S
0.6904





IPI00329536
K.ELVQVQTLMDN#MTLER.E
0.854





IPI00329577
K.KVTCPPTVTVKDEQSGGGN#VSSTLLK.Q
0.5474





IPI00329600
K.M*N#GTLTAVESFLTIHSGPEGLSIHDG.T
0.9825





IPI00329603
K.M*EVGIEDCLHIEFEYN#KSK.Y
0.5164





IPI00329628
R.LN#GSAAGHV.L
0.5541





IPI00329631
K.GTN#VSAPDQLSLALAWNR.V
0.8281





IPI00329637
R.QLVEM*EYTM*QQCN#ASVYM*EAKNR.G
0.6213





IPI00329638
R.SRNKYGRGSISLN#SSPRGR.Y
0.8113





IPI00329662
A.KENEN#SSPVAGAFGVFSTISTAVQSTGK.S
0.5474





IPI00329695
K.ALDFSLDGNIN#LTELTLALEYELLVTK.N
0.6113





IPI00329708
R.YDAQLILEN#NSGIPK.L
0.5184





IPI00329784
D.M*VVM*LLSLLEGNVVN#GTIGK.Q
0.7234





IPI00329784
D.LNKN#CTVTVTLGDERGR.V
0.6606





IPI00332067
K.QM*LIVITDGESHDHDQLN#DTALELRNK.G
0.7899





IPI00332082
K.HTGTIPGAQGLM*N#SSLLHQD.I
0.8619





IPI00332158
K.GKNFNDN#HSFLTNDELAVLP.V
0.6801





IPI00332161
R.EEQYN#STYR.V
1





IPI00332277
K.EVN#SSLHLGHAGSSPHALA.S
0.7475





IPI00332318
S.YFKCGEN#VSQK.N
0.5774





IPI00332333
C.FEN#VTSIMFLVALSEYDRVLVESDNENRM*EESK.A
0.5939





IPI00332345
R.DNAN#NSPYLQMNSLR.A
0.9971





IPI00332346
-.N#ASLLIQN#VTQEDTGSYTLHIIKR.G
0.6811





IPI00332370
K.AGM*NIARLN#FSHGSHEYHAESIANVREAVESF.A
0.5309





IPI00332380
R.NGGTNEESN#SSGNTNTDPPAEDSQK.S
0.5529





IPI00332466
L.CADDAKTHHWN#ITAVKLALVCSSEGSPGGTAR.G
0.9991





IPI00332512
R.SSTSSIDSN#ISSK.S
0.9998





IPI00332512
Q.HSLN#LTESTSLDM*LLDDTGECSAR.K
0.9436





IPI00332565
-.MDPN#CSCAAGDSCTCAGSCKCKECK.C
0.7704





IPI00332722
R.TPYRDMMLEN#YSLLLS.V
0.6869





IPI00332729
R.WEYCN#LTR.C
0.9997





IPI00332845
K.SSSGNENDEQDSDNAN#MSTQSPVSSEEYDR.T
0.9962





IPI00332864
R.KM*SAPAQPPAEGTEGTAPGGGPPGPPPN#MTSNR.R
0.7569





IPI00332961
K.SFSLN#RTLTVHQRIHTGEK.P
0.8543





IPI00333002
R.HAQN#VTVDEVIG.A
0.7239





IPI00333041
R.TGPNPGAGQN#PTRTGPNPGTGQN#PTRTGPNPGTGQN#PTR.T
0.9711





IPI00333112
K.EAFAAALNAN#NSMSK.K
0.6958





IPI00333198
N.M*IN#ATIKQDDPFNIDLGQQSQR.S
0.5736





IPI00333279
K.DVISN#TSDVIGTCEAADVAQKVDEDSAEDTQSND.G
0.937





IPI00333289
K.M*NELENKAEPGTHLCIDVEDAMN#ITR.K
0.7228





IPI00333310
R.AWPKM*HTVNGYVN#RSLPGLIGCHR.K
0.7641





IPI00333334
R.CITCAVVGNGGILN#NSHIGQEIDSH.D
0.6226





IPI00333382
M.IYIPN#ATASLNLALSLLLFLEIYNER.V
0.6007





IPI00333575
R.N#KSSMVVIDVKM*LSGFTPTM*SSIEELENKGQVMK.T
0.8104





IPI00333585
R.RLCTNLVVNCWVLGFIWFLIPIVN#ISQ.M
0.7531





IPI00333592
D.PFDN#SSRPSQVVAETR.K
0.661





IPI00333761
-.M*AAFSVGTAMN#ASSYSAEMTEPKSV.C
0.8233





IPI00333770
Q.VN#QSATALKHVFASLR.L
0.5469





IPI00333825
L.EEDSVVHSVEN#DSQNMMESLSPKK.Y
0.7121





IPI00333858
M.KGLTTTGN#SSLN#STSNTK.V
0.6112





IPI00333858
A.ANN#CTVN#TSSVATSSM*K.G
0.8885





IPI00333870
K.TWN#QSIALR.L
0.9053





IPI00333876
K.DPKEKQIEPAMTSQNSKRN#T.S
0.5583





IPI00333913
K.AVQEDEVGVPGSNSADLLRWTTATTMKVLSN#TTTT.T
0.9611





IPI00333982
R.EEQYN#STFR.V
0.9984





IPI00333985
N.GRENVGIYN#LSKGVNR.F
0.8303





IPI00333985
R.VTNSNANAASPLIVAGYN#VSGSVRSDGEPM.K
0.6708





IPI00334012
M.NTQAPPYSM*APAMVN#SSAASVGLADM*MSPGESK.L
0.6306





IPI00334015
R.HLTSLNLVQNN#FSPK.G
0.5146





IPI00334125
R.DLAELKSSLVN#ESEGAAGG.A
0.7751





IPI00334168
R.GGLGGGYSGASGMGGITAVMVN#QS.L
0.6832





IPI00334245
K.LVGFPAYGHSFLLSN#PSNHGIDAPTTGPGPAGPYTR.Q
0.5359





IPI00334271
S.AN#TTIEDEDAKARK.Q
0.5975





IPI00334273
R.RLTIEGVLDHPWLN#STEALDNVLPSAQLMMDK.A
0.906





IPI00334280
R.RIWEETGN#YTFSS.D
0.8961





IPI00334281
R.FCHEVKIN#YSPYVNYFTRVYWN#R.S
0.6989





IPI00334291
K.VLFICTAN#VTDTIPEPLR.D
0.9053





IPI00334466
K.GRN#TSSAVEMPFRNSKRSR.L
0.8392





IPI00334524
R.LPNTYPN#SSSPGPGGLGGSVHYATMARSAVRPA.S
0.5261





IPI00334587
N.QNGAEGDQIN#ASK.N
0.9303





IPI00334721
R.TLIAPQGYPNPEN#FSWT.E
0.5063





IPI00334743
R.SLAEANN#LSFPLEPLSR.E
0.5787





IPI00334813
G.ECGKCFNN#NSN#LSKHK.K
0.7625





IPI00334829
R.GNCDSSGM*NLNN#ISELIISN#RS.S
0.9642





IPI00334930
R.SILELSPQPKNFN#RTATGWRLQ.-
0.8543





IPI00334985
M.LRN#VTQM*S.K
0.9463





IPI00334996
K.M*SISPN#TTYPSLLEDGR.V
0.9998





IPI00335009
R.LTCN#ATGAPSPTLMWLK.D
0.7553





IPI00335085
R.KFLQEN#ASGR.G
0.7603





IPI00335108
K.TKATQSQRRN#SSK.T
0.9491





IPI00335121
K.RPNEN#SSADISGK.T
0.5276





IPI00335163
K.NEIQSFLVSDPEN#TTWADIEAMVSVTL.-
0.5605





IPI00335210
R.KYGSCSTILLDN#STASQPDLR.H
0.97





IPI00335216
Y.N#FTYTGDGDITLITDNNGNMVNVRR.D
0.6097





IPI00335256
K.NVIFSPLSISTALAFLSLGAHN#TTLTEILK.G
1





IPI00335256
R.TLN#QSSDELQLSMGNAMFVK.E
1





IPI00335256
K.FN#LTETSEAEIHQSFQHLLR.T
1





IPI00335256
K.YTGN#ASALFILPDQDK.M
1





IPI00335256
S.PLDEEN#LTQENQDR.G
1





IPI00335256
K.LINDYVKN#GTR.G
0.9998





IPI00335356
K.STGKPTLYN#VSLVMSDTAGTC.Y
0.5542





IPI00335426
M.NTGMNAGM*NPGMLAAGNGQGIM*PNQVM*N#GSIGAGR.G
0.799





IPI00335543
K.KENVAADIPITETEAYQLLKKATLQDNTN#QTEN.R
0.9668





IPI00335587
K.SSLVN#ESETNQN#SSSDSEAERR.P
0.7004





IPI00335823
K.IDRLDGTPQEPLCGFSKQMVEIVHKHN#ISLAVLM*S.L
0.9407





IPI00335859
K.GKN#LSLSLDALFM*GK.S
0.9266





IPI00335933
M.EN#YSSLVSLETHTGEK.L
0.816





IPI00336019
K.ANQENQALSKKLN#DTHNELNDIKQK.V
0.5412





IPI00336075
K.SSKDGNSVM*SPLFISTFTLN#ISHTASEGATGENLAK.V
0.8814





IPI00336156
R.NDMTYNYANRQSTGSAPQGPAYHGVN#RTDEVLHTDQR.A
0.557





IPI00337426
K.N#ISNPPDMSGWNPFGEDN#FSK.L
0.8699





IPI00337454
K.KKKALSSM*GAN#YSSYLA.K
0.5174





IPI00337558
K.GELN#TSIFSSR.P
1





IPI00337558
K.LLHALGGDDFLGM*LN#R.T
0.9978





IPI00337662
R.LAENSGN#ASTER.N
0.5455





IPI00337691
M.KFRGNGALSN#ISDLPFLAENSAFPK.M
0.6824





IPI00337766
K.RADKYWEYTFKVN#WSDLSVTTVTK.T
0.7534





IPI00339361
R.GHKISDYFEYQGGN#GSSPVR.G
0.6822





IPI00339366
K.VGMHCSGPLGGLLQLAAEVN#VTSR.V
0.8747





IPI00339381
K.KEYNVNDDSMKLGGN#NTSEK.A
0.8946





IPI00339381
K.AGGVGLN#LSAASRVFLM*DPAWNPAAEDQ.C
0.6808





IPI00373782
R.YDFDLFAN#ESVPDHVGYAK.V
0.9424





IPI00373787
R.DDFRQN#PSDVM*VAVGEPAVM*ECQPPR.G
0.5036





IPI00373797
R.KKKIN#GSSPDTATSGGYHSPGDSAT.G
0.9247





IPI00373855
R.YSWQCVN#QSVLCGPSGN#HTDIETK.Q
0.6195





IPI00373875
M.TIWILKVMN#FTIDGMGNLRITEK.G
0.6142





IPI00373895
K.EWFNTDSM*TLN#NTAY.L
0.6588





IPI00373923
M.FPVLFPFN#PSSLTM*DSIHIPACLNLEFLNEV.-
0.5603





IPI00373928
L.ALAN#SSQANDCLDSFASPN#K.T
0.8228





IPI00373928
T.LM*AAFQGPGEDFIGGSIFVN#VTM*FSSGGEMVQAETSGVK.I
0.9188





IPI00373943
K.NM*AQETN#QTPGPMLCSTGCGFYG.N
0.915





IPI00373947
R.CCYSLGN#GSSGFRFLKYGGCGFPSLSYGSR.F
0.5023





IPI00373966
K.NGQDHLN#ISSMTAAQEGTYT.C
0.7317





IPI00374007
K.TTEFDTN#STDIALK.V
0.9573





IPI00374029
R.SPSPSKN#DSFFTPDSNHNSLSQSTTGHLSLPQK.Q
0.6176





IPI00374033
K.ALTN#GSFSPSGNN#GSVNWR.T
0.8303





IPI00374046
K.GLRGPGSIGSEPDFWN#GSGSSRVK.G
0.588





IPI00374078
K.LEEYKEAFAVALKAN#NSM*SK.K
0.646





IPI00374080
K.HTGPGILSMANAGPNTN#G.S
0.9915





IPI00374113
K.HTGPGILSMANAGPNMN#GSQFFICTAK.T
0.9857





IPI00374128
K.RSHN#ASIIDMGE.E
0.565





IPI00374136
L.QLAN#HSGYIK.V
0.5262





IPI00374154
R.N#YSSIHSQSRST.S
0.5242





IPI00374218
K.ADETVTEMN#FSNEYN#KSELMLQENQMIADGK.E
0.9694





IPI00374218
R.RGSEVISN#TTEDTQLTSETQSLTGNK.K
0.8453





IPI00374218
R.EAYSPLELLDN#LSGADVR.Q
0.7892





IPI00374218
K.ITKN#FSEVGFPDILK.A
0.5008





IPI00374219
K.QIKN#SSLLSFDNEDENE.-
0.6397





IPI00374227
R.FARHPFYGSAGVNSGVM*LMN#LTR.I
0.5068





IPI00374341
M.STISCHQDVILSMSFNTN#GSLLATTCKDR.K
0.8314





IPI00374355
K.SPPRKIN#SSPNVN#TTASGVEDLNIIQVTIPDDDNERL.S
0.7092





IPI00374359
I.FKN#ATFTFTWAFQR.T
0.6616





IPI00374378
K.NSLSGIAMNVPASRGSNLN#SSGAN#RTSLSGGTGSGTQGATK.P
0.6461





IPI00374389
K.SSSSLGN#ATSDEDPNTNIM*NINENK.N
0.6864





IPI00374435
R.QHNVIN#LSSLDAM*M*.D
0.6392





IPI00374461
M.GYLCTHQLLFLQLN#QSSFNSK.N
0.8437





IPI00374532
K.FSPSDTDEN#ATNTQSTT.-
0.9426





IPI00374572
T.TAQLSWRPGPDN#HSPITMYVIQAR.T
0.5576





IPI00374646
R.SRDFSAAPQN#TTQNFLVNGRIR.K
0.896





IPI00374681
K.N#MSVTFALDEPMKEGECSR.R
0.7049





IPI00374711
R.NSRMN#FTYQIADCNR.D
0.7444





IPI00374729
R.MDVSSN#SSPSCQASPSQEDVSADMQERR.G
0.6969





IPI00374741
K.N#LSEM*QDLEEIRKITGVCPQFNVQF.D
0.9168





IPI00374749
K.VDM*HDDSLN#TTANLIWNK.L
0.6647





IPI00374755
R.VRRASCEPAN#GSGR.S
0.9067





IPI00374756
K.ILHN#VSEDPSFVISQHIR.K
0.6567





IPI00374770
K.DYN#ASASTISPPSSM*EEDK.F
0.6448





IPI00374793
R.ELAGN#TSSPPLSPGR.P
0.6648





IPI00374836
K.VN#PTLVIQPTN#LSARLETDVECLK.L
0.7367





IPI00374844
M.TN#ASNSQQSISMQQFSQTSN#PSAHFHK.C
0.9382





IPI00374967
K.AIESGTEWN#LSLLK.L
0.6066





IPI00374984
V.FDASAPAHCGVRVGLSAQPCPN#KSSK.A
0.6035





IPI00375011
K.LKM*LTN#PSTANSNLLLHQ.S
0.6447





IPI00375121
K.AAIQGNGDVGAAAATAHNGFSCSN#CSMLSER.K
0.7765





IPI00375139
R.VEGLFLTLSGSN#LTVK.V
0.5812





IPI00375143
R.FAVQLYNTNQN#TTE.K
0.9519





IPI00375144
N.IAPN#ISRAEIISLCK.R
0.8502





IPI00375152
K.ISNN#ITLR.E
0.6838





IPI00375174
K.KSNQLEN#HTIVGTR.S
0.6108





IPI00375179
R.RFGILSNCN#HTYCLKCIRK.W
0.8106





IPI00375210
V.YIVQSGCGEIN#DSLMELLIMINACK.I
0.6179





IPI00375216
K.VARLEQN#GSPMGARGRPNGAVAK.A
0.8406





IPI00375220
R.M*ENANLPTKQEPSWIN#QSEQGIK.E
0.5284





IPI00375253
K.N#VTESPSFSAGDNPPVLFSSDFRI.S
0.676





IPI00375266
K.TGHRMERPDN#CSEEM*YR.L
0.5967





IPI00375294
R.NRKQGVLAVIDAYN#TSNKET.K
0.9321





IPI00375294
R.TIN#VSNLYVGGIPEGEGTSLLTMRR.S
0.7631





IPI00375294
R.QTN#ESLLILRAIPEGIRDK.G
0.5806





IPI00375442
K.VDSEENTLNSQTN#ATSGMNPDGVLSK.M
0.8037





IPI00375455
R.GCNVN#STSSAGNTALHVAVMRNR.F
0.9969





IPI00375473
K.ECCNAFN#QSSALTNHK.R
0.7395





IPI00375498
K.FEEN#TSNSQWHVSLSVSFK.K
0.546





IPI00375506
R.GLN#VTLSSTGR.N
1





IPI00375506
R.FSDGLESN#SSTQFEVK.K
1





IPI00375506
K.N#TTCQDLQIEVTVK.G
0.9998





IPI00375506
K.N#LTVSVHVSPVEGLCLAGGGGLAQQVLVPAGSAR.P
0.8835





IPI00375507
K.LPCSENPRDTEDVPWITLN#SSIQK.V
0.9122





IPI00375559
R.NEMLEIQVFN#YSKVFSNK.L
0.9579





IPI00375628
R.SSDMDQQEDMISGVENSN#VSENDIPFNVQYPGQTSK.T
0.7843





IPI00375662
D.EPTVVPTTSARMESQATSASIN#NSN#PST.S
0.6812





IPI00375674
K.LQLWTN#GSVAYSVAR.E
0.9176





IPI00375747
Q.NSELQAKTN#ETEK.A
0.5652





IPI00375757
R.DGKN#ATTDALTSVLTK.I
0.8482





IPI00375757
K.DEHAQSNEIVVN#DSGSDNVK.K
0.6865





IPI00375772
K.HTGPGILSMANAGPITN#SSQFFICTAK.T
0.7151





IPI00375814
A.GQVLENLPPIGVFWDIEN#CSVPSGR.S
0.7383





IPI00375823
V.IHN#ASIMNAEAAGGYR.Y
0.8084





IPI00375835
M.ILLN#NSQKLLVLYKPLAWSIPESLK.V
0.88





IPI00375881
K.VPPTVCPFHSLNN#VTKAGEGSWLESK.R
0.8137





IPI00375881
K.ASGQVIDEIAGN#FSR.A
0.7828





IPI00375936
K.GLVEGVYCN#LTEAFEIPACK.Y
0.9419





IPI00375947
K.QM*ESSEGSSN#TTEATSGSGVR.G
0.7925





IPI00375951
R.STN#HSTQSALN#QSLHTVGAQPITAHSR.R
0.7436





IPI00375986
R.RRN#ITVGLAVFATGR.F
0.8536





IPI00376019
R.VGECSCQVSLMLQN#SSAR.A
0.9243





IPI00376094
K.IN#SSSVCVSSISENDNGISFTCRLGR.D
0.579





IPI00376147
R.GEN#VSTTEVEGVLSRLLGQTDVAVYGVAVPGK.L
0.9584





IPI00376190
K.KVIFSEETN#LSQMTLNVQGPSCILK.K
0.575





IPI00376192
K.LN#TTISTTSKGTLLPNSIM*TSTLKDQGGISR.T
0.6101





IPI00376199
P.PTLVPLMN#GSATPLPTALGLGGR.A
0.6961





IPI00376202
R.FFVELVGHYSLN#M*TVT.E
0.6697





IPI00376235
M.N#ATNHAILQSLVHLM*KPNAVPKACCAPTK.L
0.5799





IPI00376252
R.FHFQGPCGRMLPEPLAGHEN#ETVS.-
0.755





IPI00376258
R.LYM*LSFLPFLVLLVLIRNLRILTIFSM*LAN#ISML.V
0.7917





IPI00376259
R.RRRPGHGSLTN#ISR.H
0.9843





IPI00376288
G.VN#ATATADR.L
0.8447





IPI00376298
R.TTASTNM*N#ASSSR.S
0.9793





IPI00376301
R.SLSWTM*GMEGLLQN#STNFV.L
0.9409





IPI00376327
R.LKYQAQN#ITSGDTTTILPAACCTM*K.S
0.5563





IPI00376383
K.LDKLLKLRELN#LSYNK.I
0.6894





IPI00376436
K.NEN#ETILNPEEVALLEEYIPTR.H
0.7623





IPI00376539
K.YTGSGILSMANAVLNTN#GSHFFICTAK.T
0.5376





IPI00376550
R.RPAAVGAGLQNMGNTCYVN#ASLQC.L
0.6503





IPI00376566
R.QVYN#ATIAEHAPVG.H
0.5385





IPI00376572
K.N#PTDACLDAVM*NEAPGPIN#FTMLLAM*FGKK.L
0.6754





IPI00376639
P.FRMVN#ETHLDEIFASNTFAPILLTKGLLAK.K
0.6338





IPI00376647
-.M*VN#HTM*FFDVAVDSEPLDHVSFELFAEK.F
0.5373





IPI00376672
K.AREDIFMETLNNIM*EYYN#DSNGQ.-
0.8235





IPI00376675
-.M*DSSCHN#ATTKM*LATAPARGNM*MSTSK.P
0.8437





IPI00376706
P.EVLSPLTLVN#TSGEAQGTVDR.V
0.9205





IPI00376711
R.RPAAVGAGLQNMGNTCYEN#ASLQCL.T
0.7832





IPI00376742
K.AQLIGPLVFGGMN#LTRDELGWK.L
0.6307





IPI00376747
K.HMGSASEDSMGPPRVGRVLPTTN#GTFPVCIWR.G
0.6576





IPI00376770
K.KNTFN#FTLISWHSGLK.D
0.5759





IPI00376784
R.IAIHALATNM*GAGTEGAN#ASYILIR.D
1





IPI00376784
R.YGEEYGN#LTRPDITFTYFQPK.P
1





IPI00376817
K.FLVHDINELEVLMMCN#KSYCAKIAHN#VSSK.N
0.8307





IPI00376829
R.TEGNIFDSLIGGN#ASAEGPEGK.G
0.831





IPI00376832
V.LEM*EEAGSIFACNM*EGRSN#SSGEVK.Y
0.6631





IPI00376877
R.WN#TTYRR.Y
0.8726





IPI00376890
M.RDSEATGSASSAQDSTSEN#SSSVGGR.C
0.7392





IPI00376964
R.VAVVQHAPSESVDN#ASM*PPVK.V
0.9999





IPI00377042
R.KQPMTLTVTSFN#ASTGRVN#ATLSNSNMELLLSGVY.K
0.7414





IPI00377042
R.CEALCGGN#ITAM*N#GTIY.S
0.5896





IPI00377076
K.FVSDATDYAAGFN#LTYK.A
0.956





IPI00377111
P.TFSLPLQLPPPVN#TSK.L
0.7058





IPI00377116
K.AFRN#HSFLLIHQ.R
0.8205





IPI00377188
K.GEERSSCISGNN#FSWSLQWNGK.E
0.6599





IPI00377202
M.DSSLVSQQPPDNQEKERLN#TSIPQKR.K
0.9893





IPI00382394
R.RTPEEAAAGEVN#LS.S
0.7237





IPI00382397
R.SPCSIN#ASISSITSYTCF.-
0.6137





IPI00382411
L.FNSNNFDLGCKQN#GTK.L
0.6054





IPI00382432
K.LNNPKDFQELNKQTKKN#M*TIDGK.E
0.991





IPI00382485
M.LN#LSSYPIWVSLFRGSPR.R
0.7819





IPI00382512
M.PQPGCNLLN#GTQEIGPVGMTENCNRK.D
0.6219





IPI00382532
R.SRHEN#TSQVPLQESRTRKR.R
0.7304





IPI00382556
R.KN#YTSTELTVEPEEPSDSSGIN#LSGFGR.N
0.5475





IPI00382595
C.TADNSYGPVQSM*VLN#VTVR.E
0.5487





IPI00382618
Q.PANSNN#GTSTATSTNNNAK.R
0.5111





IPI00382623
S.AYDSNDPDVESN#SSSGISSPSR.Q
0.8752





IPI00382628
I.FPLLYVELN#DSAK.Q
0.6415





IPI00382629
K.YKDQWGQQGLYHCPN#FSDVMGN#K.T
0.657





IPI00382631
K.VYEN#TTLGFIVEVEGLPVPG.V
0.5381





IPI00382631
K.EKIPSPETLQPDTHN#ISK.S
0.8112





IPI00382631
K.CVAEN#NSGAVESVSDLTVEPVTYR.E
0.6931





IPI00382681
K.YCGLGLQIN#HSIESKG.N
0.6898





IPI00382705
L.QGLPGSSGN#M*T.N
1





IPI00382717
R.LAFATMFN#SSEQSQK.G
0.5353





IPI00382750
K.YEFCPFHN#VTQHEQTFR.W
1





IPI00382792
K.VSLGAVYFFMN#GTYGLAFWYGTSLILNGEPGYTIGTVLAVKR.K
0.5824





IPI00382818
K.HVEVN#GSKTAGAN#TTDK.E
0.7617





IPI00382824
E.QLN#QTLAEM*KAQEVAELKRK.K
0.6018





IPI00382843
P.MDEYSNQNNFVHDCVN#ITIK.Q
0.5824





IPI00382870
R.TITN#VSDEVSSEEGPETGYSLRR.H
0.8717





IPI00382926
S.AAQNPM*M*TN#ASATQATLTAQR.F
0.7783





IPI00382937
R.IYTSGSTNYN#PSLK.S
0.9376





IPI00382937
R.GLTFQQN#ASSMCGPDQDTAIR.V
0.9865





IPI00382990
K.NLNLELNPN#QSVK.V
0.7498





IPI00382995
M.IPCVLQYLN#FSTIIGVGVGAGAYILAR.Y
0.7145





IPI00383015
T.TTATFTTN#TTTTITSGFTVNQNQLLSR.G
0.5639





IPI00383032
K.GDVSLTIEN#VTLADSGIYCCR.I
0.8603





IPI00383040
E.GEKDPWGVSMM*N#TSFAGGQIHQDI.-
0.6457





IPI00383078
R.SAPVPVTTQNPPGAPPN#VSGRR.H
0.9704





IPI00383119
M.IFEN#PSLCASNSEPLK.L
0.5794





IPI00383151
F.TVFTN#NT.H
0.7675





IPI00383197
R.SSN#LTTHKIIHTGEK.P
0.7828





IPI00383221
R.LGPVSTAN#MSR.P
0.7114





IPI00383222
K.QN#TTLGLSER.P
0.99





IPI00383233
R.YDLTGWLHRAKPN#LSALDAPQVLHQSK.R
0.9657





IPI00383317
K.SPLFMGKVVN#PTQK.-
1





IPI00383323
R.NGYGFINRN#DTKEDVFVHQTAIK.K
0.6899





IPI00383351
-.M*SRINKYLFSNSDSN#FSHFSVSN#V.S
0.7104





IPI00383371
E.ILGFNSKGEVHGIN#GTQWGQTLR.M
0.9636





IPI00383425
K.VFISN#STN#SSNPCERR.S
0.8844





IPI00383454
R.SN#LTSFGADQVM*DLGR.D
0.6593





IPI00383455
R.ETALCSLN#SSHGIVAFPSRSR.S
0.8133





IPI00383469
R.FDGILADAGQTVEN#MSWMLVCDR.P
0.7854





IPI00383482
R.EN#M*SDGDTSATESGDEVP.V
0.7247





IPI00383482
K.EMN#KSDLNTNNLLFKPPVESHIQKNK.K
0.8527





IPI00383505
R.LLSNPLLQTYLPN#STK.K
0.5013





IPI00383541
R.YSGVN#MTGF.R
0.5346





IPI00383543
R.KN#STFPQVQM*.R
0.7637





IPI00383580
M.SSDN#DSYHSDEFLTNSK.S
0.5329





IPI00383585
S.PKVTKQNSLNDEGCQSDLEDN#VSQGSSDALLLR.G
0.5234





IPI00383614
K.LN#NTMNACAAIAALERVK.I
0.5876





IPI00383750
R.QDN#GTLLSLEDLNGGILVDVNTAEHST.V
0.7695





IPI00383786
K.ESLIM*NHVLN#TSQLASSYQYKKK.Y
0.7004





IPI00383786
R.VKRNQEN#FSSVLYK.E
0.8509





IPI00383786
K.GRGLNAM*AN#ETPDFMR.A
0.5193





IPI00383794
V.GKM*QSTQTTN#TSN#STN#K.S
0.5906





IPI00383828
R.ELGGAIDFGAAYVLEQASSHIGN#STQATVR.D
0.5605





IPI00383888
M.TATHHFSVDLN#ASRSLSQVAM*DLHEAVSM*KLHRVR.E
0.5144





IPI00383931
Q.TVQRSM*AN#LSVLFGQVVR.G
0.9317





IPI00383973
R.VLYM*FNQMPLN#LTNAVATAR.Q
0.507





IPI00383973
M.IHN#CSLIASALTISNIQAGSTGNWGCHVQTK.R
0.595





IPI00384004
K.AQAEAN#ATAISNLLPFM*EYEVHTQLMNK.L
0.5412





IPI00384031
-.M*PSSTLPGWPGSSGGPVSRPSSLESSRN#TSSN#SSPLNLK.G
0.982





IPI00384063
R.YLFPEVDMTSTN#FTGL.S
0.9761





IPI00384138
K.TLTFLAVMLIVLN#STGPAHQPGR.G
0.7809





IPI00384159
M.KPVN#QTAASNKGLR.G
0.7011





IPI00384159
R.QLEDPN#GSFSNAEMSELSVAQKPEK.L
0.7079





IPI00384193
K.DIKKKNINLQPMWQLLPVEQDTSN#VTEM*K.V
0.5349





IPI00384202
K.N#SSNWKLFK.E
0.8565





IPI00384210
K.KEDYN#ETAPMLEQV.-
0.5565





IPI00384238
R.N#SSLLEPQKSGNN#E.T
0.9755





IPI00384277
K.EIAFLSEKISN#LTIVQAEIK.D
0.9181





IPI00384277
K.TWSNRITEKQDILN#NSLTTLSQDITK.V
0.6615





IPI00384280
K.M*SN#ITFLNFDPPIEEFHQYYQHIVTTLVK.G
0.9985





IPI00384367
K.LGVSSVPSCYLIYPN#GSHGLINVVKPLR.A
0.82





IPI00384413
R.AVQPHNGCFN#WTSR.A
0.947





IPI00384416
K.KINLNHLLN#FTFEPR.G
0.6975





IPI00384441
R.GKMADSSGRGAGKPATGPTN#SSSAK.K
0.5636





IPI00384450
V.TAGILEM*RNALGN#QSTPAPPTGEVADTPLEPGK.V
0.6518





IPI00384456
K.GTQTYSVLEGDPSEN#YSKYLLSLK.E
0.5345





IPI00384470
R.N#FSSVAASSGN#TTL.N
0.5266





IPI00384496
G.CGGGGSYSASSSSAALPVN#KSK.M
0.8121





IPI00384508
K.MAAAN#LTFSQEVVWQR.G
0.838





IPI00384532
V.HEEFNPNQAN#GSYASR.R
0.5909





IPI00384543
K.NTNQGFSSAN#VSEEEER.K
0.5445





IPI00384556
R.ELSEMRAPPAATN#SSK.K
0.5522





IPI00384651
R.LYQQFNEN#NSIGETQARKLSK.L
0.69





IPI00384717
K.LLQAENCDIFQN#LSAKQR.L
0.6254





IPI00384772
R.N#LTGVM*NVAR.P
0.6516





IPI00384785
M.FKM*AKN#WSAAGNAFCQAAKLHM*QLQSK.H
0.8306





IPI00384840
L.SMLN#GTKVLS.D
0.7724





IPI00384877
K.HKGLIEIPSLSEENEIN#DTEVN#VSK.K
0.5927





IPI00384969
K.SSISNNYLN#LTFPRKR.T
0.7225





IPI00384984
K.TDNSLLDQALQN#DTVFLNM*R.G
1





IPI00384984
K.TVVTYHIPQN#SSLENVDSR.Y
1





IPI00385095
R.FEKTNEM*LLNFNN#LSSARLQQMSER.F
0.6078





IPI00385247
K.N#NTIAPKK.A
0.5642





IPI00385263
R.DSFKVYCN#FTAGGSTCVFPDK.K
0.7212





IPI00385264
K.THTN#ISESHPN#ATFSAVGEASICEDDWDSGER.F
1





IPI00385264
K.STGKPTLYN#VSLVMSDTAGTCY.-
1





IPI00385264
R.GLTFQQN#ASSMCGPDQDTAIR.V
0.9865





IPI00385267
R.GGN#NSFTHEALTLK.Y
0.6823





IPI00385280
M.PSN#SSASISKLR.E
0.6522





IPI00385287
R.N#LSSLQPPPPGFK.R
0.9481





IPI00385291
K.QEM*GGIVTEPIRDYN#SSR.E
0.6259





IPI00385317
K.GSTPRNDPSVSVDYN#TTEPAVR.W
0.8716





IPI00385321
R.ISLSDMPRSPMSTN#SSVHTGSDVEQDAEK.K
0.8106





IPI00385334
Q.SLEDILHQVEN#K.T
0.9617





IPI00385341
R.MLRFIQEVN#TTTR.S
0.5871





IPI00385343
R.EHEKLLMEVCRN#CSA.V
0.7115





IPI00385358
R.GNYGGGGNYNDFGN#YSGQQQSNYG.-
0.8778





IPI00385362
R.VFFAGFSN#ATVDNSILLR.L
0.5241





IPI00385404
K.KAVSPLLLTTTN#SSEGLSMGNYMGLINRIAQKKR.L
0.9145





IPI00385446
K.TFAN#SSYLAQHIR.I
0.5827





IPI00385511
L.KGGNN#DSWMNPLAKQFSNMGLLSQTEDN#PSSK.M
0.61





IPI00385511
R.KGALETDNSN#SSAQVSTVGQTSR.E
0.9344





IPI00385511
K.M*WKNHISSRN#TTPLPRPPPGLTN.P
0.7333





IPI00385539
R.NLN#HTKQRLLEVANYVDQVVNSAGDAHG.-
0.6411





IPI00385684
R.GERHGDIFMN#RTENWIGSQYKK.V
0.8302





IPI00385729
K.N#DSDLFGLGLEEAGPK.E
0.7373





IPI00385743
S.LRENSISPEGAQAIAHALCAN#STLK.N
0.879





IPI00385756
P.NHRPTGRGNN#ISSHH.-
0.8353





IPI00385894
K.NYNTN#ITTETSK.I
0.764





IPI00385962
R.DIETFYN#TSIEEM*PPM*LL.-
0.8287





IPI00385973
I.ITEGN#GTESLNSVITSMKTGELEK.E
0.7951





IPI00385980
K.KNKN#SSKPQKNN#GSTWANVPLPPPP.V
0.8485





IPI00385980
E.YKIWCLGN#ETR.F
0.6971





IPI00385980
K.TVRTTEEAPSAPPQSVTVLTVGSYN#STS.I
0.561





IPI00386028
R.KLGYSSLILDSTGSTLFAN#CTDDNIYMFN#MT.G
0.6334





IPI00386099
K.VNAPILTN#TTLNVIR.L
0.5699





IPI00386134
Y.CGTWN#NSLSGWVFGGGTK.L
0.7368





IPI00386139
M.VYN#CTTGSTNPFHWGEVGMILPVFLNVR.I
0.5525





IPI00386145
R.GAAAAPGN#WSSRQRPAHPR.T
0.7285





IPI00386225
R.KALPMEFEAYIN#ASGEHGIVVFSLGSM*VS.E
0.8915





IPI00386236
K.N#NSDISSTR.G
1





IPI00386236
R.GLTFQQN#ASSMCVPDQDTAIR.V
1





IPI00386236
K.THTN#ISESHPN#ATFSAVGEASICEDDWNSGER.F
1





IPI00386257
R.IYPGPTRLAN#STIKDESPPR.Y
0.5319





IPI00386279
F.NQIM*HAFSVAPFDQN#LSIDGK.I
0.6244





IPI00386327
K.GETWATPN#CSEATCEGNNVISLS.P
0.7424





IPI00386389
-.MRQNNN#ITEFVLLGFSQDLDVQK.A
0.5718





IPI00386421
G.NIIN#M*SSVASSVKGGSVSFRGLR.C
0.7712





IPI00386442
K.ADILLDCLLDEDPEN#QTLRKDYEK.T
0.9765





IPI00386532
K.GPIGPGEPLELLCN#VSGALPPAGR.H
0.7379





IPI00386553
M.WSHM*QPHLFHN#QSVLAEQMALNKK.F
0.784





IPI00386566
K.EN#QSIRAFNSEHK.I
0.6513





IPI00386567
R.EWN#GTYHCIFR.Y
0.6039





IPI00386567
M.KVMCDNNPVSLNCCSQGNVN#WSK.V
0.9231





IPI00386567
K.VLQQQWTN#QSSQLLHSVER.F
0.8635





IPI00386731
K.NLPFLEHLELIGSN#FSSAMPR.N
0.8123





IPI00386732
M.SHFPDRGSEN#GTPMDVKAGVR.V
0.7764





IPI00386764
R.TAADN#FSTQYVLDGSGHILSQKPSHLGQGKK.V
0.8748





IPI00386928
K.WQSAIQDFRSN#ATALCHIR.N
0.9172





IPI00386953
R.RAFM*LEPEGMSPM*EPAGVSPMPGTQN#DTGRT.E
0.9674





IPI00387050
R.RARHDSPDPSPPRRPQHN#SSGDCQK.A
0.6349





IPI00394642
T.VTPVSPSFAHNPKRHNSASVEN#VSLRK.S
0.9196





IPI00394646
R.RRKN#M*SEFLGEASIPGQEPP.T
0.6674





IPI00394652
M.EITWTPMN#ATSAFGPNLR.Y
0.8107





IPI00394718
K.RQPATLTVDWFN#ATSSKVN#ATFSEASPVELK.L
0.8689





IPI00394738
K.SN#ISPNFNFM*GQLLDFER.T
0.8923





IPI00394801
M.ENPQEPDAPIVTFFPLIN#DTFR.K
0.8947





IPI00394816
K.N#LSGPDDLLIDK.N
0.9721





IPI00394823
K.PLGPLQTLM*EN#LSSNR.F
0.5646





IPI00394824
K.CQAHSQN#VTFVLRK.V
0.6463





IPI00394845
K.N#LSINNDLNLR.Y
0.8772





IPI00394866
R.SLCCGDISQSAVLFLCQGTLAMLDWQN#GSM*GR.S
0.8122





IPI00395010
M.LQDDN#TSAGLHFMASVK.K
0.8773





IPI00395323
K.ANEQVVQSLN#QTYK.M
0.9987





IPI00395400
N.PDASYNLGVLHLDGIFPGVPGRN#QTLAGEIFHK.A
0.5633





IPI00395488
R.LPASLAEYTVTQLRPN#ATYSVCVM*PLGPGR.V
0.9999





IPI00395488
R.IAQLRPEDLAGLAALQELDVSN#LSLQALPGDLSGLFPR.L
1





IPI00395488
R.LHEITN#ETFR.G
0.9999





IPI00395511
K.AVEVATVVIQPTVLRAAVPKN#VSVAEGK.E
0.5478





IPI00395595
P.SRPSNSN#ISKGESRPK.W
0.7249





IPI00395632
R.VN#RSVHEWAGGGGGGGGATYVFK.M
0.8947





IPI00395659
K.NKIARLGN#GSQDLNHGVDNENGGR.R
0.9099





IPI00395659
K.IARLGN#GSQDLNHGVDNENGGRRGPN#R.T
0.5352





IPI00395737
A.DKASDTSSETVFGKRGHVLGN#GSQVTQAANSGCSK.A
0.8702





IPI00396050
R.RAEMSQTN#FTPDTLAQNEGK.A
0.9957





IPI00396080
K.GRTFN#LTAGNDDSIVMK.A
0.8603





IPI00396096
L.N#RSDSDSSTLAK.K
0.6886





IPI00396103
M.LN#GTTLEAAMLFHGISGGHIQGIMEEMER.R
0.5147





IPI00396166
R.EN#FTQTLPK.M
0.6497





IPI00396200
R.VAGAPAPWAAAHGGAM*MDVN#SSGR.P
0.9741





IPI00396341
K.HYQTVFLM*RSN#STLNKHNENYKQK.K
0.8381





IPI00396433
P.LLPKSSTIEEEEN#M*SGHK.C
0.6374





IPI00396464
Q.N#STQDSGPQESEGSAGNSLTVAK.D
0.6878





IPI00396485
K.GDIGIVPLGLVETAILKPSMWSTFAPVN#TTT.E
0.9221





IPI00396500
K.GQSVSSPPNDCN#ISPAR.V
0.7878

















TABLE 8







N-linked glycosylation sites identified from human serum/plasma



which do not contain the consensus.


N-X-T/S glycosylation motif.










Protein IP #

Peptide



(Version 2.21)
Peptide Sequences
Probability













IPI00004574
K.SGTASVVCLLN*N*FYPR.E
0.9956






IPI00004617
V.SVLTVLHQN*WLDGKEYK.C
0.9847





IPI00006143
K.N#GREVN#GCSGVN#R.Y
0.9503





IPI00009464
K.FDPSTKIYEISN#R.W
0.9255





IPI00010740
R.DM#RM#GGGGAM#N*M#GDPYGSGGQK.F
0.9572





IPI00017648
R.LLPPN*TVNLPSKVRAFTFPSEVPSK.A
0.827





IPI00018311
R.RVTVN*TAYGSN*GVSVLR.I
0.9984





IPI00019571
R.N*AN*FKFTDHLK.Y
0.9542





IPI00019571
K.SPVGVQPILN*EHTFCAGM#SK.Y
0.9972





IPI00019571
K.LRTEGDGVYTLN*NEKQWINK.A
1





IPI00019943
K.DLLRN*CCNTENPPGCYR.Y
1





IPI00021841
R.LAARLEALKEN*GGAR.L
0.9896





IPI00021841
K.LREQLGPVTQEFWDN#LEKETEGLR.Q
0.9969





IPI00021841
K.LLDN*WDSVTSTFSK.L
0.9913





IPI00022229
R.EYSGTIASEAN*TYLNSK.S
1





IPI00022229
Q.FN#N#NEYSQDLDAYNTKDKIGVELTGR.T
0.9947





IPI00022229
K.SNTVASLHTEKNTLELSN#GVIVK.I
0.9107





IPI00022391
R.AYSLFSYN*TQGRDNELLVYK.E
0.9993





IPI00022394
K.TNQVN*SGGVLLR.L
0.9935





IPI00022395
R.AIEDYIN*EFSVR.K
0.991





IPI00022395
K.TSNFN*AAISLK.F
0.9665





IPI00022417
K.LQELHLSSN#GLESLSPEFLRPVPQLR.V
0.9997





IPI00022432
R.YTIAALLSPYSYSTTAVVTN*PKE.-
1





IPI00022432
R.GSPAIN*VAVHVFR.K
0.9987





IPI00022463
R.SM#GGKEDLIWELLN*QAQEHFGKDK.S
0.9891





IPI00022463
R.SAGWN#IPIGLLYCDLPEPR.K
0.9865





IPI00022463
R.N*TYEKYLGEEYVK.A
1





IPI00022463
R.LKCDEWSVN#SVGK.I
0.9999





IPI00022463
R.KPVEEYAN#CHLAR.A
0.9997





IPI00022463
K.SASDLTWDN*LKGK.K
0.9901





IPI00022463
K.LCM*GSGLNLCEPNN#KEGYYGYTGAFR.C
0.978





IPI00022463
K.LCM*GSGLN#LCEPNNKEGYYGYTGAFR.C
0.9989





IPI00022463
K.IN#HCRFDEFFSEGCAPGSK.K
0.9473





IPI00022463
K.IM*N#GEADAMSLDGGFVYIAGK.C
0.994





IPI00022463
K.GDVAFVKHQTVPQN#TGGK.N
0.9999





IPI00022488
R.YYCFQGN*QFLR.F
0.9957





IPI00022488
R.WKN*FPSPVDAAFR.Q
0.9983





IPI00022488
L.PPTSAHGN#VAEGETKPDPDVTER.C
0.9996





IPI00022488
K.SLGPN#SCSAN#GPGLYLIHGPNLYCYSDVEK.L
0.9868





IPI00025426
R.SSGSLLNN*AIK.G
0.9617





IPI00025426
R.N*QGN*TWLTAFVLK.T
0.9985





IPI00025426
K.ATVLN*YLPK.C
0.917





IPI00027482
K.M#N*TVIAALSR.D
0.9953





IPI00032179
R.FATTFYQHLADSKNDNDN*IFLSPLSISTAFAM#TK.L
0.9994





IPI00032179
R.EVPLN*TIIFMGR.V
0.9764





IPI00032179
Q.PLDFKEN#AEQSR.A
0.9972





IPI00032220
R.AAM#VGM#LAN*FLGFR.I
0.9991





IPI00032220
A.SDLDKVEGLTFQQNSLN*WM#KK.L
0.9653





IPI00032256
R.TEVSSN*HVLIYLDK.V
1





IPI00032256
R.SLFTDLEAEN*DVLHCVAFAVPK.S
0.9792





IPI00032256
R.SASN*M#AIVDVK.M
0.9209





IPI00032256
R.HNVYIN#GITYTPVSSTNEKDM*YSFLEDM*GLK.A
0.9991





IPI00032256
K.SSSN#EEVM*FLTVQVKGPTQEFK.K
0.9994





IPI00032256
K.SKAIGYLN*TGYQR.Q
0.9968





IPI00032256
K.QQN#AQGGFSSTQDTVVALHALSK.Y
0.9999





IPI00032256
K.N#EDSLVFVQTDK.S
0.9997





IPI00032256
K.GVPIPN*KVIFIR.G
0.9169





IPI00032256
K.FSGQLN*SHGCFYQQVK.T
0.9998





IPI00032256
K.FRVVSMDEN*FHPLNELIPLVYIQDPK.G
0.9951





IPI00032256
K.EQAPHCICAN#GR.Q
0.9933





IPI00032256
K.ALLAYAFALAGN*QDK.R
1





IPI00032256
K.AIGYLN*TGYQR.Q
0.9984





IPI00032328
R.IASFSQN#CDIYPGKDFVQPPTK.I
1





IPI00032328
R.DIPTN*SPELEETLTHTITK.L
0.9999





IPI00152059
R.VEN*SYGQERRCHLM.-
0.9348





IPI00164623
R.TVM#VNIEN*PEGIPVK.Q
0.9888





IPI00164623
R.TM*QALPYSTVGN#SNNYLHLSVLR.T
1





IPI00164623
R.TM#QALPYSTVGN*SNN*YLHLSVLR.T
1





IPI00164623
R.AVLYNYRQN*QELK.V
0.9544





IPI00164623
K.VHQYFN*VELIQPGAVK.V
0.9942





IPI00164623
K.AGDFLEAN*YM#NLQR.S
0.9398





IPI00167498
V.QRLAHGLHKVN*TLALK.Y
0.9251





IPI00175649
M.KLM*IVGN#TGSGKTTLLQQLM*KTK.K
0.8308





IPI00216315
K.IPVVPHN#ECSEVM*SNM*VSENM*LCAGILGDR.Q
0.944





IPI00216722
H.LETPDFQLFKN#GVAQEPVHLDSPAIK.H
0.987





IPI00216773
K.VFDEFKPLVEEPQNLIKQN#CELFEQLGEYK.F
1





IPI00216773
K.VFDEFKPLVEEPQN*LIK.Q
0.9949





IPI00216773
K.LVN*EVTEFAK.T
0.996





IPI00216773
K.KVPQVSTPTLVEVSRN*LGK.V
0.9626





IPI00216773
K.FQN*ALLVR.Y
0.9105





IPI00218017
R.YN*RQIGEFIVTR.A
0.8035





IPI00218199
K.DKQIITFFSPLTILVGPN#GAGK.T
0.9318





IPI00218732
K.GIETGSEDLEILPN#GLAFISSGLKYPGIK.S
0.9999





IPI00220120
K.NTLYLQMN*SLR.A
0.9772





IPI00220591
E.RAN*SHIFLYGDLR.S
0.9594





IPI00250430
M.VTFSN#TLPRAN#TPSVEDPVR.R
0.8977





IPI00292530
R.VQSWKGSLVQASEAN*LQAAQDFVR.G
0.9955





IPI00292530
R.GRFPLYNLGFGHNVDFN#FLEVMSM*ENNGR.A
1





IPI00292530
K.GSLVQASEAN*LQAAQDFVR.G
1





IPI00294193
R.AISGGSIQIEN#GYFVHYFAPEGLTTM*PK.N
0.9971





IPI00294193
A.EKN*GIDIYSLTVDSR.V
0.9145





IPI00296608
R.YSAWAESVTN*LPQVIK.Q
0.9949





IPI00298828
R.VCPFAGILEN*GAVR.Y
0.9929





IPI00298828
K.CPFPSRPDN#GFVN#YPAKPTLYYK.D
0.9996





IPI00299475
K.SSTLKPTIEALPN#VLPLNEDVN#K.Q
0.9435





IPI00305457
R.TLNQPDSQLQLTTGN*GLFLSEGLK.L
1





IPI00305457
N.KITPN*LAEFAFSLYR.Q
0.9594





IPI00305457
N.ATAIFFLPDEGKLQHLEN#ELTHDIITK.F
0.9995





IPI00305457
L.PDEGKLQHLEN#ELTHDIITK.F
0.9999





IPI00305457
K.TDTSHHDQDHPTFN*KITPNLAEFAFSLYR.Q
1





IPI00305457
K.QIN*DYVEKGTQGK.I
0.9336





IPI00305457
K.LQHLEN*ELTHDIITK.F
0.9989





IPI00305457
K.ITPN*LAEFAFSLYR.Q
0.9708





IPI00305457
K.ELDRDTVFALVN#YIFFK.G
0.998





IPI00305457
I.FFLPDEGKLQHLEN*ELTHDIITK.F
0.9924





IPI00305457
A.TAIFFLPDEGKLQHLEN#ELTHDIITK.F
0.9957





IPI00305461
R.KLWAYLTIN*QLLAER.S
1





IPI00328609
R.GFQHLLHTLN*LPGHGLETR.V
0.9993





IPI00328609
K.IAPAN*ADFAFR.F
0.9553





IPI00332161
V.VSVLTVLHQDWLN*GK.E
1





IPI00332161
K.N*QVSLTCLVK.G
0.9708





IPI00332161
K.GFYPSDIAVEWESN*GQPEN*NYK.T
1





IPI00332161
K.FNWYVDGVEVHN*AK.T
0.9507





IPI00373776
K.NSLYLQMN*SLR.A
0.9973





IPI00375506
R.GLESQTKLVN#GQSHISLSK.A
0.9999





IPI00375506
K.AEFQDALEKLN#M*GITDLQGLR.L
0.9973





IPI00382950
R.FFESFGDLSTPDAVM#GN*PK.V
0.995





IPI00383035
R.MKGLIDEVN*QDFTNR.I
0.9957





IPI00383317
V.FSN#GADLSGVTEEAPLKLSK.A
0.9915





IPI00383317
K.VFSN*GADLSGVTEEAPLKLSK.A
1





IPI00383317
K.SVLGQLGITKVFSN*GADLSGVTEEAPLKLSK.A
0.9986





IPI00383317
K.FNKPFVFLM#IEQN*TK.S
0.9901





IPI00384391
R.DNSKN*SLYLQM#NSLR.A
1





IPI00385298
K.HFLMEN*INNEN*KGSIN*LKRKHI.T
0.9997





IPI00385332
K.DSLYLQMN*SLR.V
0.9943









Example 6
Identification of Early Disease Biomarkers Using Tissue Specimens and Body Fluids

This example describes the identification of disease biomarkers from prostate cancer tissues.


Proteins expressed on the cell surface or secreted from cells in disease tissues are likely to leak to body fluids at an early stage of disease development and can be detected in body fluids as diagnostic markers. This is demonstrated by several tumor biomarkers currently in clinical use (see Table 9). In general, identification of cell surface proteins or secreted proteins of cells is difficult due to contamination with extremely complex mixtures of intracellular proteins of high abundance.









TABLE 9







Known tumor markers.


Current tumor markers










Tumor
Protein




markers
Name/Function
Cancer Site
Glycosylation





CEA
Carcinoembryonic
Colon, Lung
glycoprotein



antigen


AFP
A-Fetoprotein
Liver, germ cell cancer
glycoprotein




of ovaries or testis


PAP
Prostatic acid
Prostate, myeloma, lung
glycoprotein



phosphatase
cancer, osteogenic




sarcoma


HCG
Human chorionic
Gestational trophoblastic
glycoprotein



gonadotropin
tumor


PSA
Prostate specific
Prostate
glycoprotein



antigen


CA125
Ovarian cancer
Ovarian
glycoprotein



marker CA125









Several approaches have been used in an attempt to enrich for cell surface proteins or secreted proteins from cultured cells. These methods includes (1) differential centrifugation (Han et al., Nat. Biotechnol. 19:946-951 (2001)), (2) chemical labeling of cell surface proteins to introduce tags attached to cell surface proteins before lysing cells, and (3) extraction of secreted proteins in cell culture medium secreted from cells (Martin et al., Cancer Res. 64:347-355 (2004)). However, none of these methods can be applied to tissue specimens, which contain potential biomarkers for human diseases.


Most proteins expressed on the cell surface and/or secreted by cells are glycosylated (Durand and Seta, Clin. Chem. 46:795-805 (2000)). Glycoproteins from disease specimens were isolated using a glycopeptide capture method (see Examples 1-5) (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)). Tissue specimens can be obtained from fresh tissues, in which case tissues are minced and digested with collagenase in serum free medium. Both single cells from tissue specimens and cell free supernatants are collected and subjected to glycopeptide capture to enrich for cell surface proteins from cells and/or secreted proteins in the extracellular matrix that are released to the supernatant after collagenase digestion. Tissue specimens can be obtained from frozen sections, in which case tissues are ground with a blender or tissue homogenizer, and the proteins in the microsomal fraction and supernatant are collected. The glycopeptide capture method is then used to isolate membrane proteins from microsomal fractions and/or secreted proteins from the supernatant.


Using the glycopeptide capture method, isolated formerly glycosylated peptides were identified and quantified by tandem mass spectrometry. The expression of these proteins in body fluids was further determined by antibody based assays or stable isotope labeled synthetic peptides originally identified from tissues. The identification of proteins from disease tissues and detection of these proteins in body fluids can be used to determine specific protein changes related to certain disease states or cancer for diagnostic biomarkers or immunotherapy targets.


Proteins in body fluids have been used to discover biomarkers related to disease states for years, and the advancement of proteomic technologies provides the opportunity to identify additional disease markers and/or potential therapeutic targets. Despite the efforts to identify biomarkers in body fluids, most protein markers identified in body fluids using proteomic approaches are abundant proteins and not specific to a particular disease (Diamandis, Mol. Cell. Proteomics 3:367-378 (2004)). This is due to the peculiar protein content of most body fluids, which are highly complex but contain a few abundant proteins representing most of the protein content. In addition, the protein content of body fluids varies over time in an individual due to different physiological and pathological influences. The protein content of body fluids also varies among individuals in a population. Due to these factors, identifying biomarkers in body fluids for specific disease is extremely challenging.


Using the glycopeptide capture method, secreted proteins and cell surface proteins were identified from tissues. It was determined whether the glycoproteins were present in body fluids using targeted proteomic approaches, including antibody based method and synthetic heavy-isotope labeled peptides (Pan et al., Mol. Cell. Proteomics 4:182-190 (2005)). Since cell surface proteins and secreted proteins are highly glycosylated and likely to leak to body fluids in an early stage of disease development, cell surface proteins or secreted proteins can be identified as potential targets for candidate biomarkers in body fluids. A more sensitive and targeted approach can further be used to determine their diagnostic value in body fluids.


Glycoproteins have been isolated from cell free supernatant of prostate cancer tissues. Over 100 proteins have been identified and quantified (Table 10). Most proteins identified are proteins located in the extracellular environment in spite of the high contamination of intracellular proteins in cell free supernatant during tissue sample preparation. It was found that 61% of the identified proteins were secreted proteins, 18% of the proteins were extracellular matrix proteins, 10% of the proteins were transmembrane proteins, and only 11% of the proteins were from intracellular proteins. Protein network analysis showed that 5 out of 6 protein changes were located in one network (FIG. 17). Heavy isotope labeled peptides were synthesized and mixed with N-linked glycopeptides isolated from serum (see FIG. 4). The relative abundances of these peptides were quantified among individuals (see FIG. 16). The protein TIMP1 has also been found to be decreased in prostate cancer patients relative to normal patients (Liu et al., J. Urol. 173:73-78 (2005).










TABLE 10







Identification of proteins and relative abundance changes in cancer



tissues compared to patient matched normal tissues.










Protein IPI #

Ratio



(Version 2.28)
Peptide Sequences
(Cancer/Normal)





IPI00004573
R.LSLLEEPGN*GTFTVILNQLTSR.D







IPI00004617
R.EQQFNSTFR.V





IPI00004618
R.EEQFN*STYR.V





IPI00004641
R.LAGKPTHVN*VSVV.M





IPI00004641
V.QGFFPQEPLSVTWSESGQN*VTAR.N





IPI00005794
K.IVVYNQPYIN*YSR.T





IPI00005794
R.GKIVVYNQPYINYSR.T





IPI00006154
R.LQNNENN*ISCVER.G





IPI00006662
R.ADGTVNQIEGEATPVN*LTEPAKLEVK.F





IPI00007244
R.SCPACPGSN*ITIR.N





IPI00007778
A.NAPYN*QTLTGYNDYIK.M





IPI00009030
R.VQPFN*VTQGK.Y





IPI00009802
R.TLYRFEN*QTGFPPPDSR.F





IPI00010858
R.NKSVILLGR.H
down





IPI00010949
R.ALAYGEKN*LTFEGPLPEKIELLAHK.G





IPI00011229
K.YYKGSLSYLN*VTR.K





IPI00011302
K.TAVNCSSDFDACLITK.A





IPI00011302
S.LQCYNCPNPTADCK.T





IPI00012503
R.NLEKN*STKQEILAALEK.G





IPI00012887
K.YSVANDTGFVDIPKQEK.A





IPI00013179
K.SVVAPATDGGLN*LTSTFLR.K





IPI00013179
K.SVVAPATDGGLN*LTSTFLRK.N





IPI00013446
K.AQVSNEDCLQVEN*CTQLGEQCWTAR.I





IPI00013449
K.ALKQYN*STGDYR.S





IPI00013698
K.ILAPAYFILGGN*QSGEGCVITR.D





IPI00013976
T.AASEETLFN*ASQR.I





IPI00015028
R.SFM#VN*WTHAPGNVEK.Y





IPI00015102
K.IIISPEEN*VTLTCTAENQLER.T





IPI00017601
K.EHEGAIYPDNTTDFQR.A





IPI00017601
K.ELHHLQEQNVSNAFLDK.G





IPI00019571
K.VVLHPNYSQVDIGLIK.L





IPI00019591
R.SPYYN*VSDEISFHCYDGYTLR.G





IPI00020986
R.NNQIDHIDEKAFENVTD.L
down





IPI00021891
K.VDKDLQSLEDILHQVEN*KTSEVK.Q





IPI00022255
R.VNLTTN*TIAVTQTLPNAAYNNR.F





IPI00022418
K.LDAPTNLQFVN*ETDSTVLVR.W





IPI00022429
R.QDQCIYNTTYLNVQR.E





IPI00022431
K.AALAAFNAQNN*GSNFQLEEISR.A





IPI00022431
K.VCQDCPLLAPLNDTR.V





IPI00022463
R.QQQHLFGSNVTDCSGNFCLFR.S





IPI00022488
R.SWPAVGNCSSALR.W





IPI00022488
K.ALPQPQNVTSLLGCTH.-





IPI00022792
R.VDLEDFENNTAYAK.Y





IPI00022892
R.LDCRHEN*TSSSPIQYEFSLTR.E
up





IPI00023673
R.ALGFENATQALGR.A
down





IPI00023673
R.DAGVVCTN*ETR.S





IPI00023673
K.GLNLTEDTYKPR.I





IPI00023673
R.TVIRPFYLTN*SSGVD.-





IPI00023673
R.YKGLN*LTEDTYKPR.I





IPI00024284
R.SLTQGSLIVGDLAPVN*GTSQGK.F





IPI00024284
R.IQGEEIVFHDLN*LTAHGISHCPTCR.D





IPI00024284
R.NLHQSN*TSRAELLVTEAPSKP.I





IPI00024284
R.VAQQDSGQYICN*ATSPAGHAEAT.I





IPI00027482
R.AQLLQGLGFNLTER.S





IPI00027827
R.AKLDAFFALEGFPTEPN*SSSR.A





IPI00027851
K.SAEGTFFIN*KTEIEDFPRFPHR.G





IPI00028908
R.IHQN*ITYQVCR.H





IPI00029739
K.IPCSQPPQIEHGTINSSR.S





IPI00031008
R.CIN*GTCYCEEGFTGEDCGKPTCPHACHTQGR.C





IPI00032256
K.SLGNVNFTVSAEALESQELCGTEVPSVPEHGRK.D





IPI00032292
R.SHN*RSEEFLIAGK.L
down





IPI00032292
R.AKFVGTPEVNQTTLYQR.Y





IPI00032292
K.FVGTPEVNQTTLYQR.Y





IPI00032292
K.FVGTPEVN*QTTLYQRYEIK.M





IPI00032328
K.LNAENNATFYFK.I





IPI00043716
K.KLRLPDTGLYNMTDSG.T





IPI00098026
R.LHNQLLPN*VTTVER.N





IPI00163563
K.VISLLPKENKTR.G





IPI00164623
K.TVLTPATNHM#GN*VTFTIPANR.E





IPI00166729
R.FGCEIENN*R.S





IPI00166729
K.DIVEYYN*DSN*GSHVLQGR.F





IPI00166729
R.FGCEIENNRSSGAFWK.Y





IPI00168520
V.AN*FSQIETLTSVFQK.K





IPI00168728
R.EEQFN*STFR.V





IPI00169285
R.SDLNPAN*GSYPFKALR.Q





IPI00171411
R.LQQDVLQFQKN*QTNLER.K





IPI00178017
R.KFDVNQLQNTTIKR.I





IPI00178926
R.IIVPLNNREN*ISDPTSPLR.T





IPI00215998
R.QQMENYPKNNHTASILDR.M





IPI00215998
K.NRVPDSCCIN*VTVGCGINFNEK.A





IPI00217503
R.TATESFPHPGFN*NSLPNKDHR.N





IPI00221224
K.AEFNITLIHPK.D





IPI00221224
K.GPSTPLPEDPNWN*VTEFHTTPK.M





IPI00221224
K.KLNYTLSQGHR.V





IPI00221224
V.LLNLNVTGYYR.V





IPI00221224
R.N*ATLVNEADKLR.A





IPI00221224
V.TLALNNTLFLIEER.Q





IPI00247063
R.SCIN*ESAIDSR.G





IPI00289489
R.AQQLLAN*STALEEAMLQEQQR.L





IPI00289489
R.KQELSRDN*ATLQATLHAAR.D





IPI00289489
G.LAN*ASAPSGEQLLR.T





IPI00289489
R.LHRLNASIADLQSQLR.S





IPI00289489
K.RLNTTGVSAGCTADLLVGR.A





IPI00289983
R.KFLN*ESYK.H
down





IPI00289983
K.FLNESYKHEQVYIR.S





IPI00289983
R.KFLNESYKHEQ.V





IPI00289983
R.KFLNESYKHEQVYIR.S





IPI00291262
R.LANLTQGEDQYYLR.V





IPI00291866
K.VGQLQLSHN*LSLVILVPQNLK.H





IPI00292069
K.GSQWSDIEEFCN*R.S





IPI00292732
R.LYLDHN*NLTR.M





IPI00293088
R.GVFITNETGQPLIGK.V





IPI00293088
K.VTVLGVATAPQQVLSN*GVPVSN*FTYSPDTK.A





IPI00296141
R.ALAGLVYN*ASGSEHCYDIYR.L





IPI00296141
R.FGN*KTFPQR.F





IPI00296170
K.NLFLNHSEN*ATAK.D





IPI00296170
K.MVSHHN*LTTGATLINEQWLLTTAK.N





IPI00296922
R.CAPNFWN*LTSGHGCQPCACHPSR.A





IPI00298281
R.TLAGENQTAFEIEELNR.K





IPI00298281
R.EGFVGNRCDQCEENYFYNR.S





IPI00298281
R.IASAVQKNATSTKAEAER.T





IPI00298281
R.KIPAINQTITEANEK.T





IPI00298281
K.LLNN*LTSIK.I





IPI00298281
K.QVLSYGQNLSFSFR.V





IPI00298281
K.TANDTSTEAYNLLLR.T





IPI00298828
R.VYKPSAGNNSLYR.D





IPI00298828
K.LGN*WSAM#PSCK.A





IPI00298860
R.TAGWNIPMGLLFN*QTGSCK.F





IPI00298860
K.FGRN*GSDCPDKFCLFQSETK.N





IPI00298971
R.PQPPAEEELCSGKPFDAFTDLKN*GSLFAFR.G





IPI00299547
K.SYN*VTSVLFR.K





IPI00301579
K.GQSYSVNVTFTSNIQSK.S





IPI00305064
K.AFN*STLPTM#AQMEK.A





IPI00305457
K.YLGNATAIFFLPDEGK.L





IPI00328113
R.VLPVNVTDYCQLVR.Y
down





IPI00328113
R.CDSGFALDSEERN*CTDIDECR.I





IPI00328113
K.AWGTPCEM#CPAVNTSEYK.I





IPI00328113
R.NYYADN*QTCDGELLFN*MTKK.M





IPI00328488
R.RPYVSYVNN*SIAR.N





IPI00329482
I.SAQYAN*FTGCISNAYFTR.V





IPI00329482
R.DAVRN*LTEVVPQLLDQLR.T





IPI00329573
R.NLQVYNATSNSLTVK.W





IPI00329573
P.LTDQGTTLYLN*VTDLK.T





IPI00332161
R.EEQYNSTYR.V





IPI00332161
K.TKPREEQYNSTYR.V





IPI00333982
R.EEQYN*STFR.V





IPI00333982
K.TKPREEQYNSTFR.V





IPI00335256
K.FN*LTETSEAEIHQSFQHLLR.T





IPI00374091
R.LHNKLLPNVTTVER.N





IPI00375506
R.GLNVTLSSTGR.N





IPI00375506
R.FSDGLESNSSTQFEVK.K





IPI00375947
S.EGSSNTTEATSGSGVR.G





IPI00382512
K.M#SIQGCVAQPSSFLLNHTR.Q





IPI00383517
R.AVCGGVLVHPQWVLTAAHCIRN*K.S





IPI00383981
R.FVN*VTVTPEDQCRPNNVCTGVLTR.R





IPI00385514
H.VSNVTVN*YN*VTVERM#NR.M





IPI00386236
K.YKNNSDISSTR.G





IPI00386236
R.GLTFQQN*ASSM#CVPDQDTAIR.V









Example 7
Identification of Proteotypic N-linked Glycopeptides for Serum Protein Analysis

Theoretically, one unique peptide per protein that can be observed by mass spectrometry is sufficient for unambiguously identifying and quantifying a parent protein. If such proteotypic peptides can be isolated and selectively analyzed by mass spectrometry, the complexity of proteome profiling could be reduced by one or two orders of magnitude. This increases the sensitivity, throughput and reproducibility of scoring phase studies. Protein glycosylation, especially N-linked glycosylation, is very common post-translational modification for proteins expressed on extracellular surfaces, in cell secretions, and for proteins contained in body fluids. These are the most easily accessible human proteins for diagnostic purposes, and the literature confirms that glycoproteins constitute a large number of clinical biomarkers (Table 11). A method was developed to isolate N-linked glycopeptides (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)). By selectively isolating a subset of N-linked glycopeptides, the procedure achieves a significant reduction in analyte complexity and increases the sensitivity for serum proteomic analysis at two levels: first, a reduction of the total number of peptides due to the fact that every serum protein on average only contains a few N-linked glycosylation sites, and second, a reduction of pattern complexity by removing the oligosaccharides that contribute significantly to the peptide pattern heterogeneity. It is therefore believed that the quantitative analysis of these formerly N-linked glycopeptides has potential use for detecting new diagnostic markers (Zhang et al., Nat. Biotechnol. 21:660-666 (2003); Zhang et al., Mol. Cell. Proteomics 4:144-155 (2005).









TABLE 11







Most known clinical tumor markers are glycoproteins










Tumor





markers
Protein Name/Function
Cancer Site
Glycosylation





CEA
Carcinoembryonic antigen
Colon, Lung
glycoprotein


AFP
A-Fetoprotein
Liver, germ cell cancer of ovaries or testis
glycoprotein


NSE
Neuron specific enolase
Neuroblastoma, small cell lung cancer
unknown


PAP
Prostatic acid phosphatase
Prostate, myeloma, lung cancer, osteogenic
glycoprotein




sarcoma


HCG
Human chorionic
Gestational trophoblastic tumor
glycoprotein



gonadotropin


PSA
Prostate specific antigen
Prostate
glycoprotein


CA125
Ovarian cancer marker
Ovarian
glycoprotein



CA125









For chromatography procedures, HPLC-grade reagents were purchased from Fisher Scientific (Pittsburgh, USA). PNGase F was purchased from New England Biolabs (Beverly, Mass.) and hydrazide resin from Bio-Rad (Hercules, Calif.). All other chemicals and the human serum used in this study were purchased from Sigma (St. Louis, USA).


Purification and Fractionation of Formerly N-linked Glycosylated Peptides from Serum by SCX. 0.75 ml serum was used to isolate N-linked glycopeptides (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)), which were fractionated by strong cation-exchange chromatography into 43 fractions as described previously (Han et al., Nat. Biotechnol. 19:946-951 (2001)).


Analysis of Peptides by Mass Spectrometry. Fractionated peptides were analyzed using a LCQ ion trap mass spectrometer (Finnigan, San Jose, Calif.) or ESI-qTOF mass spectrometer (Waters, Milford, Mass.) as described previously (Pieper et al., Proteomics 3:422-432 (2003)). Using SEQUEST, acquired MS/MS spectra were compared against the International Protein Index (IPI) human protein database (version 2.28). For MS/MS spectra acquired by the ESI-qTOF mass spectrometer, the mass window of each peptide was given a tolerance of 0.4 Da between the measured monoisotopic mass and calculated monoisotopic mass; the b and y ion series of database peptides were included in the SEQUEST analysis. For MS/MS spectra acquired via the Finnigan mass spectrometer, the mass window for each peptide was given a tolerance of 3 Da between the measured average mass and calculated average mass; the b and y ion series were included in the SEQUEST analysis. The database sequence tool was set to the following modifications: carboxymethylated cysteines, oxidized methionines, and an enzyme-catalyzed conversion of Asn to Asp at the site of carbohydrate attachment. No other constraints were included in the SEQUEST searches. Search results were further analyzed with a suite of software tools that included INTERACT (Han et al., Nat. Biotechnol. 19:946-951 (2001)) and PeptideProphet (Keller et al., Anal. Chem. 74:5383-5392 (2002)). All MS/MS spectra were manually checked to verify the validity of the database search results.


Amino acid preference around the glycosylation sites. Position-independent amino acid abundance ratios were first calculated for each protein corresponding to one or more peptides from the set of all identified N-linked glycopeptides using the sequence information contained in the human International Protein Index version 2.28. This yielded a mean abundance and variance for each amino acid in the set of all identified proteins. The relative abundance of each amino acid was then calculated for all positions plus or minus twenty residues from the asparagine in the NX(T/S) motif using the set of identified N-linked glycopeptides, where the asparagine was taken to be at position zero. A “probability” score describing the bias for each amino acid at each position was generated by calculating the deviation of the observed abundance for that amino acid at that position from its position-independent abundance, then dividing by the standard deviation in the position-independent abundances for that amino acid in all identified proteins.


Subcellular Localization of Identified Proteins. Signal peptides were predicted using signalP 2.0 (19). Transmembrane (TM) regions were predicted using TMHMM (version 2.0) (Krogh et al., J. Mol. Biol. 305:567-580 (2001)). The TMHMM program predicts protein topology and the number of TM helices. Information from signalP and TMHMM were combined to separate proteins into the categories: 1) membrane bound, 2) soluable, 3) secreted and 4) membrane proteins anchored by an uncleaved signal peptide also predicted to be a trans membrane helix. All protein sequences were taken from IPI version 2.28.


Identification of Serum Peptides Using SPEG and Tandem Mass Spectrometry. To assess the potential of the proposed glycopeptide capture method for serum protein profiling, four 0.75 ml of serum was processed using SPEG as described previously (Zhang et al., Nat. Biotechnol. 21:660-666 (2003)). Formerly N-linked glycosylated peptides were fractionated by two dimensional chromatography using cation exchange fractionation and reverse phase liquid chromatography (RP-LC). Peptide mixtures were sequentially analyzed by electrospray ionization tandem mass spectrometry (ESI-MS/MS) (Han et al., Nat. Biotechnol. 19:946-951 (2001)). The resulting collision induced dissociation (CID) spectra were used to perform searches within the human International Protein Index sequence database (IPI version 2.28 with 41100 entries); database search results were statistically analyzed using PeptideProphet (Keller et al., Anal. Chem. 74:5383-5392 (2002)).


Most cancer-specific serum biomarkers consist of low-abundance serum proteins. According to these results, a significant number of proteins identified in the present study belong to low-abundance serum protein groups such as growth factors, cell surface receptors, and channel or transporter proteins. Several previously identified serum markers were also identified, such as the MAC-2 binding protein and the ovarian cancer-related tumor marker CA125. The MAC-2 binding protein belongs to a family of beta-galactoside-binding proteins (also known as galectins) that are thought to modulate cell-cell and cell-matrix interactions. MAC-2 binding protein is present in normal serum in the μg/ml range and elevated levels of MAC-2 binding protein (≧11 μg/ml) have been found in the sera of cancer patients (Bresalier et al., Gastroenterology 127, 741-748 (2004): Marchetti et al., Cancer Res. 62:2535-2539 (2002)). An increase in serum CAl25 is considered an accurate and reliable measure of responses to treatment and relapses in ovarian cancer patients (Guppy et al., Oncologist 7:437-443 (2002)).


Identification of Nonredundant N-linked Glycopeptides as Proteotypic Peptides. N-linked glycosylation sites in peptide sequences are generally fall into the N—X-T/S sequon (Bause, Biochem. J. 209:331-336 (1983)). From the set of all peptides identified above, a list of non-redundant N-linked glycopeptides for each sequon was generated as follows. First, the identified sequences were filtered for the presence of the N—X-T/S sequon to remove peptides not containing the sequon. Non-sequon-containing peptides can come from two sources. The first is peptides from non-specific isolation of N-linked glycopeptides (selectivity of the method) and the second is peptides that are incorrectly identified by SEQEST search (false positive identifications). In the present analysis, the false positive error rate was estimated by the PeptideProphet statistical model (Zhang et al., Mol. Cell. Proteomics 4:144-155 (2005)). Second, a minimum probability score of 0.5 was used to filter out low probability sequon-containing peptides. And finally, redundant peptides with overlapping sequences containing the same sequons were resolved in favor of those sequences which contained the greater number of tryptic ends. Using the two-dimensional peptide separation protocol for analyzing formerly N-linked glycopeptides, we identified 3244 nonredundant N-linked glycosylation sites were identified, representing 2585 unique proteins with a PeptideProphet score at least 0.5 (Table 7). 2106 peptides are unique to a single database entry, and thus selected as experimentally identified proteotypic peptides, representing a total of 1671 proteins.


This indicates that the combination of solid-phase N-linked glycopeptide capture and tandem mass spectrometry is able to identify a large number of peptides with consensus N-linked glycosylation sites from serum with high confidence. These peptides can now be used as standard peptides to identify and quantify the same peptides from samples isolated by glycopeptide capture method with different biological or physiological relevance (Pan et al., Mol. Cell. Proteomics 4:182-190 (2005)).


Determination of amino acid preference around N-linked glycosylation sequon using the experimentally identified N-linked glycopeptides. While each protein containing multiple N-linked glycosylation sequons can generate multiple possible tryptic peptides, not all potential N-linked tryptic glycopeptides were identified by the large scale mass spectrometry analysis (Table 7). The reasons for this are that not all NXT/S sequons are occupied (Petrescu et al., Glycobiology 14:103-114 (2004)) and that only a portion of a protein's possible peptides exhibit particular physico-chemical properties such that they are consistently observed by a mass spectrometer (Mallick, P. et al., In Preparation (2005)). Determining the amino acid specificity around N-linked glycopeptides detected by a mass spectrometer offers the possibility of developing a refined N-linked glycosylation motif to predict occupation of the glycosylation sequon. This refined motif can then be used to scan protein databases to computationally predict proteotypical glycopeptides for the subsequent use in the scoring phase analysis of serum proteins. In general, a proteotypic N-linked glycopeptide is determined by a short linear sequence motif that occurs around the N-linked glycosylation and trypsin cleavage sites. The large number of N-linked glycopeptide sequences identified here allows statistical characterization of the preference for each amino acid at each position around the NXT/S motif. Specifically, the relative occurrence of each amino acid at each position around identified N-linked glycosylation sites, from −20 to +20 (where position 0 is taken to be the asparagine that oligosaccharide is formerly attached to), has been calculated. This region was chosen to include residues immediately around the glycosylation site that may interact with the translocon complex where glycosylation occurs (glycosylation occurring approximately 30 residues from the ribosome (Varki, Essentials of Glycobiology, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., (1999).). The occurrence of finding each amino acid at each sequence position (Fpos) was compared with the average occurrence (Fave) of each amino acid at any position in the set of identified proteins. The probabilities (P) of each amino acid occurrence in each position were determined in standard deviations (s) relative to the average occurrence:






P=(Fpos−Fave)/s


It was found that significant biases in amino acid occurrence only appear in the immediate vicinity of the glycosylation site (−3 to +5). There is a marked preference for non-charged amino acids and discrimination against charged amino acids (D, E, R, K) as well as proline on either side of the glycosylation site (FIGS. 18A and 18B). With the exception of W, there is also an increased probability of finding bulky hydrophobic amino acids, such as M, F, and Y, immediately before a glycosylation site (−3, −2, and −1), and there is an increased probability of finding small, non-charged amino acids (L, S, V, I, A) at positions +1, +3, +4, and +5. In addition, at either side of the glycosylation site, the identified N-linked glycopeptides appear selective against amino acids that are likely to be modified (W and C) at either sides of the glycosylation site. These data indicate that there is well-defined specificity for a protetypical N-linked glycopeptide that is likely to be detected by mass spectrometry.


Computational prediction of N-linked glycopeptides as proteotypical peptides. Next the large number of N-linked glycopeptides identified in this study was used to generate predictors to score all the theoretical tryptic N-linked glycopeptides from human IPI database (version 2.28). It allowed us to predict the likelihood of occupancy for an N—X-T/S sequon (Yaffe et al., Nat. Biotechnol. 19:348-353 (2001)) and its detection possibility by mass spectrometer (Mallick, P. et al., In Preparation (2005)). A web interface, UniPep, was developed for displaying N—X-T/S sequon containing peptides in the human IPI database for predicted or experimentally identified proteotypic N-linked glycopeptides. This is of particular relevance with respect to those genes or proteins that have been shown to change their abundance in disease tissues compared to normal tissues using genomic or proteomic approaches. The detection of these proteins in serum, especially secreted proteins or extracellular surface proteins which are most likely to make their way into blood serum, is a critical step in the development of these proteins as disease biomarkers. In this case, the proteotypical N-linked glycopeptides are predicted by their sequences and heavy isotopic labeled peptides can be synthesized as candidates to determine their presence and quantify their abundance in serum.


Four different types of information were used to predict proteotypical N-linked glycopeptides when scanning the IPI protein database. First, since N-linked glycosylation is likely to occur on the extracellular surface or secreted proteins, the subcellular localization of each protein was predicted using a combination of hidden Markov model (HMM) algorithms Nielsen et al., Protein Eng. 10:1-6 (1997). and transmembrane (TM) region predictions using a commercial version of the TMHMM algorithm Krogh et al., J. Mol. Biol. 305:567-580 (2001). By so doing, the subcellular localizations of each protein was able to be categorized as being either a) extracellular—proteins that contained predicted non-cleavable signal peptides and no predicted transmembrane segments; b) secreted—proteins that contained predicted cleavable signal peptides and no predicted transmembrane segments; c) transmembrane—proteins that contained predicted transmembrane segments and extracellular loops and intracellular loops; and d) intracellular—proteins that contained neither predicted signal peptides nor predicted transmembrane regions. The predicted protein subcellular localization is displayed in UniPep along with other protein information from database annotations (FIG. 19, Protein infor), and the signal peptides and transmembrane sequences are highlighted in the protein sequence to give a general indication of the protein topology. NXS/T score for predicted peptides). For all predicted peptides that have also been experimentally identified in the dataset, the Peptide ProPhet score and the tissue resources from which the peptides were identified are indicated as well. Third, the experimentally identified N-linked glycopeptides were used to calculate peptide frequencies that are likely to be detected by mass spectrometry and identify a set of physico-chemical properties that distinguish observed peptides by MS from unobserved peptides (Mallick, P. et al., In Preparation (2005)). The physico-chemical properties determined from the identified peptides were used to score the likelihood of a potential N-linked glycopeptide to be detected by MS (FIG. 19, detection probability). Fourth, the uniqueness of each predicted N-linked glycopeptide was determined by searching for each sequence within the entire IPI protein database. Peptides present in multiple proteins were indicated by multiple database hits (FIG. 19, Number of other proteins with the peptide). Uniqueness of a peptide sequence to a particular protein was taken to be a necessary condition for being a proteotypic peptide.


Applying the protein subcellular localization prediction method to all 40,110 protein entries in the IPI database, it was predicted that 14041 proteins are exposed to extracellular environment as secreted, transmembrane, or extracellular surface proteins (Table 12). Of these, 76% contain at least one N-linked glycosylation sequon that is potentially N-linked glycosylated and can be detected by a proteotypic N-linked glycopeptide (Table 14). In other words, profiling proteotypical N-linked glycopeptides can capture a large number of proteins in the extracellular environment that derive from variety of cells and tissues. The glycopeptide capture method significantly enriches in extracellular, secreted, and transmembrane proteins, these are the same proteins considered most easily accessible in the human body for diagnostic and therapeutic purposes.









TABLE 12







Predicted subcellular localizations of proteins from human protein


database and their potential N-linked glycosylation











Total
NXT/S
%














All proteins in database
40110
29908
75%


Extracellular/secreted/membrane proteins
14041
10664
76%


Secreted proteins
3947
3017
76%


Extracellular proteins
3415
2358
69%


Transmembrane proteins
6679
5289
79%









Since analyses of serum proteins using SPEG focus on information-rich subproteomes, it should be pointed out that non-glycosylated proteins are transparent to this system. While it is believed that the majority of serum-specific proteins are glycosylated (Durand and Seta, Clin. Chem. 46:795-805 (2000)), intracellular proteins that are non-glycosylated may represent a rich source of biomarkers in the dead cells of diseased tissue. The data suggest that cell-specific surface proteins that are mostly glycosylated are also released into serum and are therefore identifiable using the glycopeptide capture method.


Validation of the experimentally identified or computational predicted glycopeptides by synthetic peptide standard. Peptide identification using tandem mass spectrometry is based on the matching of experimentally determined CD spectra with theoretical spectra generated from all possible peptide sequences from a protein database. Therefore, the peptide sequence assignments using database search algorithms include a certain degree of error, and in this study, statistical methods were used to objectively estimate the probability of an identified peptide being a correct peptide (Keller et al., Anal. Chem. 74:5383-5392 (2002)). An identified peptide with a peptide probability of 0.9 indicates that this peptide has a 90% chance to be correct. Using medium probability score cut-off, 3244 unique glycosylation sites were identified. Of these peptides, it is estimated that 2502 unique N-linked glycopeptides are predicted to be correct identifications.


The identified peptides were validated with additional evidence. Since MS/MS spectra from the same peptide sequence are highly reproducible (Rush et al., Nat. Biotechnol. 23:94-101 (2005)), a heavy isotope labeled peptide corresponding to the identified peptide of interest was synthesized. The MS/MS spectrum of the synthetic peptide was then compared with the one that was used to make the sequence assignment. The heavy isotope labeled peptide versus regular peptide was synthesized, which allowed differentiation of the synthetic standard from its native form by mass spectrometry and could be used to quantify the same peptide from biological sample using the high throughput platform we developed recently (Pan et al., Mol. Cell. Proteomics 4:182-190 (2005)).


One of the identified N-linked glycopeptides from plasma serine protease inhibitor shown in FIG. 19 was synthesized and the phenylalanine residue was replaced with heavy Phenylalanine (using 13C) in the peptide sequence. This heavy isotope labeled peptide standard produces 9 mass unit difference from the native peptide. The signature of the CID spectra of the native light and synthetic heavy forms of the peptide were highly reproducible, and the correctness of the sequence assignment of this peptide can be determined by 1) the co-elution of this heavy isotope labeled peptide with its light form of native peptide and 2) the similarity of the OD spectra (FIG. 20).


In the present study, a list of a large number of serum proteins and their N-linked glycopeptides from serum were identified using SPEG followed by MS/MS. The list of identified proteins confirmed the presence of a number of candidate marker proteins in plasma and serum, indicating that the quantitative analysis of serum proteins using SPEG increases the sensitivity and has the potential to identify disease markers. The increased sensitivity is achieved by focusing on only N-linked glycopeptides versus all tryptic peptides from whole proteins and avoiding the analysis of highly abundance proteins such as albumin.


As demonstrated in our recent publication (Pan et al., Mol. Cell. Proteomics 4:182-190 (2005)), this list of glycopeptides can be synthesized as a heavy isotope labeled standard and used to identify and quantify native glycopeptides using the recently developed mass spectrometry-based screening technology. This allows specific targeting of certain peptides/proteins with biological significance in a complex sample for identification and quantification. For each candidate marker, the identified formerly N-linked glycopeptide was chemically synthesized, labeled with at least one heavy isotope amino acid, and spiked into peptides isolated from serum using SPEG. During MS analysis, this representative stable isotope labeled peptide standard distinguishes itself from the corresponding native peptide by a mass difference corresponding to the stable isotope label. Knowing the exact mass, sequence and quantity of the standard peptide, the peptide standard and its isotopic pair isolated from serum can be located and selectively sequenced for identification. The quantification of the native peptide is determined by the ratio of the abundance of the spiked peptide, whose identify and quantity are known, to that of the native peptide (Pan et al., Mol. Cell. Proteomics 4:182-190 (2005)). Since this approach transforms proteomic analysis from traditional data dependant discovery phase to validation scoring phase and directly focusing on interesting peptides/proteins for identification and quantification, it technically increases the sample loading capacity, avoids some difficult issues associated with sample complexity and thus significantly improves the throughput and sensitivity.


Using the identified N-linked glycosylation sites from this study, further refinement was performed on the N-linked glycosylation motif by identifying amino acid preference around the glycosylation sites that are likely to be identified by mass spectrometry. It was found that amino acid positions −3 to +5 showed a significant bias for non-charged amino acids and against charged amino acids (K, R, D, E), as well as proline, tryptophan, and cysteine. The amino acid sequence before the glycosylated Asparagine (−3, −2, and −1) had preference for bulky hydrophobic amino acid (Y, F, M), and amino acid sequence after the glycosylated Asparagine (+1 to +5) had preference for small non-charged amino acids such as V, L, I, S and A. These amino acid preferences are in general agreement with the previous studies with the exception that the K, and R are less preferred around the NXT/S sequon (Petrescu et al., Glycobiology 14:103-114 (2004); Apweiler et al., Biochim Biophys Acta 1473:4-8 (1999)). The less represented K and R might be due to less efficient cleavage of tryptic digest around the N-linked glycosylation sites.


The selected amino acid preference around N-linked glycosylation site and the physico-chemical properties of the identified peptides by mass spectrometry in this study allow us to predict proteotypical N-linked glycopeptides from proteins exposed to extracellular environment that likely to be detected by mass spectrometry. A software tool, UniPep, has developed to output the known and unknown proteotypical N-linked glycopeptides from queried proteins in database. Theoretically, the experimentally identified or computationally determined proteotypic N-linked glycopeptides for quantitative analysis of serum proteins will capture majority of proteins designated to extracellular environment, which is likely to be detected in serum as disease biomarkers.


Throughout this application various publications have been referenced. The disclosures of these publications in their entireties are hereby incorporated by reference in this application in order to more fully describe the state of the art to which this invention pertains. Although the invention has been described with reference to the examples provided above, it should be understood that various modifications can be made without departing from the spirit of the invention.

Claims
  • 1-40. (canceled)
  • 41. A composition comprising a plurality of peptides containing the glycosylation sites referenced as SEQ ID NOS: 1-3482, wherein said peptides each correspond to peptide fragments derived by cleavage of polypeptides using the same cleavage reagent.
  • 42. The composition of claim 41, wherein said cleavage reagent is a protease.
  • 43. The composition of claim 42, wherein said protease is trypsin.
  • 44. A kit comprising a plurality of peptides containing the glycosylation sites sh referenced as SEQ ID NOS: 1-3482, wherein said peptides each correspond to peptide fragments derived by cleavage of polypeptides using the same cleavage reagent.
  • 45. The kit of claim 44, further comprising a pair of differentially labeled isotope tags.
  • 46. The kit of claim 44, further comprising the cleavage reagent corresponding to said peptide fragments.
  • 47. The kit of claim 46, wherein said cleavage reagent is a protease.
  • 48. The kit of claim 47, wherein said protease is trypsin.
  • 49. The kit of claim 44, further comprising a hydrazide resin.
  • 50. The kit of claim 44, further comprising a glycosidase.
Parent Case Info

This application claims the benefit of priority of U.S. Provisional application Ser. No. 60/573,593, filed May 21, 2004, the entire contents of which is incorporated herein by reference.

Government Interests

This invention was made in part, with government support under grant number N01-1-1V-28179 awarded by the National Heart, Lung, and Blood Institute, National Institutes of Health, under Contract No. N01-HV-28179 and from grant number R33 from the National Cancer Institute. The government has certain rights in the invention.

Provisional Applications (1)
Number Date Country
60573593 May 2004 US
Continuations (1)
Number Date Country
Parent 11134871 May 2005 US
Child 12723574 US