COMPOSITIONS AND METHODS FOR POLYPEPTIDE ANALYSIS

REFERENCE TO AN ELECTRONIC SEQUENCE LISTING

The contents of the electronic sequence listing (R070870150WO00-SEQ-MKN.xml; Size: 908,570 bytes; and Date of Creation: Dec. 21, 2022) are herein incorporated by reference in their entirety.

BACKGROUND

Measurements of the proteome provide deep and valuable insight into key biological processes. In adjacent fields, like genomics, advances in DNA sequencing technology have proven extremely valuable in improving understanding of the progression of complex human disease. Applying similar approaches to proteomics has been challenging for a number of reasons, including the large number of different proteins and even larger number of proteoforms, the wide dynamic range of protein abundance in cells and biological fluids, and the inability to copy or amplify proteins. Accordingly, improved approaches are needed.

SUMMARY

Methods and systems for determining chemical characteristics of polypeptides are generally described.

In some aspects, the application provides a method for determining chemical characteristics of a polypeptide. In some embodiments, the method comprises contacting a polypeptide with one or more amino acid recognizers. In certain embodiments, the one or more amino acid recognizers comprise a first set of one or more amino acid recognizers that bind to the polypeptide. In some embodiments, the method comprises detecting a first series of signal pulses indicative of a first series of binding events between the first set of one or more amino acid recognizers and the polypeptide. In some embodiments, the method comprises determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide based on at least one characteristic of the first series of signal pulses.

In some aspects, the application provides a device comprising at least one processor and at least one non-transitory computer-readable storage medium having instructions encoded thereon that, when executed by the at least one processor, cause the at least one processor to perform a method for determining chemical characteristics of a polypeptide. In some embodiments, the method comprises detecting a first series of signal pulses indicative of a first series of binding events between a first set of one or more amino acid recognizers and the polypeptide. In some embodiments, the method comprises determining at least one chemical characteristic of at least two amino acids of the polypeptide based on at least one characteristic of the first series of signal pulses.

In some aspects, the application provides at least one non-transitory computer-readable storage medium having instructions encoded thereon that, when executed by at least one processor, cause the at least one processor to perform a method for determining chemical characteristics of a polypeptide. In some embodiments, the method comprises detecting a first series of signal pulses indicative of a first series of binding events between a first set of one or more amino acid recognizers and the polypeptide. In some embodiments, the method comprises determining at least one chemical characteristic of at least two amino acids of the polypeptide based on at least one characteristic of the first series of signal pulses.

In some aspects, the application provides a method comprising obtaining data during a degradation process of a polypeptide. In some embodiments, the method comprises analyzing the data to determine portions of the data, each portion corresponding to at least one amino acid of the polypeptide. In certain embodiments, at least a first portion of the data corresponds to a first amino acid and comprises a first plurality of signal pulses indicative of a series of binding events between a first type of amino acid recognizer and the first amino acid. In certain embodiments, a second portion of the data corresponds to a second amino acid and does not comprise signal pulses indicative of binding events between any type of amino acid recognizer and the second amino acid. In some embodiments, the method comprises determining at least one chemical characteristic of the first amino acid and/or the second amino acid based on at least one characteristic of the first portion of the data and at least one characteristic of the second portion of the data. In some embodiments, there is provided at least one non-transitory computer-readable medium having instructions encoded thereon that, when executed by at least one process, cause the at least one processor to perform the method. In some embodiments, there is provided a device comprising at least one processor and the at least one non-transitory computer-readable medium.

In some aspects, the application provides a method for determining chemical characteristics of a polypeptide. In some embodiments, the method comprises detecting a first series of signal pulses indicative of a first series of binding events between a first set of one or more amino acid recognizers and a polypeptide. In some embodiments, the method comprises determining at least one characteristic of the first series of signal pulses. In some embodiments, the method comprises comparing the at least one characteristic of the first series of signal pulses with known characteristics of a plurality of amino acid segments that comprise at least two amino acids. In some embodiments, the method comprises determining at least one chemical characteristic of at least two amino acids of the polypeptide based on the comparing. In some embodiments, there is provided at least one non-transitory computer-readable medium having instructions encoded thereon that, when executed by at least one process, cause the at least one processor to perform the method. In some embodiments, there is provided a device comprising at least one processor and the at least one non-transitory computer-readable medium.

In some aspects, the application provides a method comprising obtaining data during a degradation process of a polypeptide. In some embodiments, the method comprises analyzing the data to determine at least three portions of the data, each portion corresponding to an amino acid of the polypeptide and comprising a plurality of signal pulses indicative of a series of binding events between one or more amino acid recognizers and the amino acid. In some embodiments, the method comprises determining one or more characteristics of each of the at least three portions of the data. In some embodiments, the method comprises identifying the polypeptide based on the order of the at least three portions of the data and the one or more characteristics of each of the at least three portions of the data. In some embodiments, there is provided at least one non-transitory computer-readable medium having instructions encoded thereon that, when executed by at least one process, cause the at least one processor to perform the method. In some embodiments, there is provided a device comprising at least one processor and the at least one non-transitory computer-readable medium.

In some aspects, the application provides a method for determining at least one chemical characteristic of an amino acid of a polypeptide. In some embodiments, the method comprises detecting a first series of signal pulses indicative of a series of binding events between one or more amino acid recognizers and a first amino acid of the polypeptide. In some embodiments, the method comprises determining at least one chemical characteristic of a second amino acid of the polypeptide based on at least one characteristic of the first series of signal pulses. In some embodiments, there is provided at least one non-transitory computer-readable medium having instructions encoded thereon that, when executed by at least one process, cause the at least one processor to perform the method. In some embodiments, there is provided a device comprising at least one processor and the at least one non-transitory computer-readable medium.

In some aspects, the application provides a method for determining at least one chemical characteristic of an amino acid of a polypeptide. In some embodiments, the method comprises detecting a first series of signal pulses indicative of a series of binding events between a first set of one or more amino acid recognizers and a first amino acid of the polypeptide. In some embodiments, the method comprises detecting a second series of signal pulses indicative of a series of binding events between a second set of one or more amino acid recognizers and a second amino acid of the polypeptide. In some embodiments, the method comprises determining at least one chemical characteristic of the second amino acid of the polypeptide based on at least one characteristic of the first series of signal pulses and at least one characteristic of the second series of signal pulses. In some embodiments, there is provided at least one non-transitory computer-readable medium having instructions encoded thereon that, when executed by at least one process, cause the at least one processor to perform the method. In some embodiments, there is provided a device comprising at least one processor and the at least one non-transitory computer-readable medium.

In some aspects, the application provides a method of identifying a disease or disorder in a subject. In some embodiments, the method comprises digesting a protein in a sample from the subject to produce a plurality of polypeptides. In some embodiments, the method comprises contacting a polypeptide of the plurality of polypeptides with one or more amino acid recognizers and a cleaving agent. In some embodiments, the method comprises detecting one or more series of signal pulses indicative of binding events between the one or more amino acid recognizers and the polypeptide as amino acids are progressively cleaved from a terminus of the polypeptide by the cleaving agent. In some embodiments, the method comprises determining at least one chemical characteristic of the polypeptide based on at least one characteristic of the one or more series of signal pulses. In certain embodiments, the at least one chemical characteristic is indicative of a modification of the protein. In certain embodiments, the modification of the protein is indicative of the disease or disorder in the subject. In some embodiments, there is provided at least one non-transitory computer-readable medium having instructions encoded thereon that, when executed by at least one process, cause the at least one processor to perform the method. In some embodiments, there is provided a device comprising at least one processor and the at least one non-transitory computer-readable medium.

The details of certain embodiments of the disclosure are set forth in the Detailed Description. Other features, objects, and advantages of the disclosure will be apparent from the Examples, Drawings, and Claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

The accompanying Drawings, which constitute a part of this specification, illustrate several embodiments of the disclosure and, together with the accompanying description, serve to explain the principles of the disclosure.

FIG. 1 shows an example overview of real-time dynamic protein sequencing. Protein samples are digested into polypeptides, immobilized in nanoscale reaction chambers, and incubated with a mixture of freely-diffusing N-terminal amino acid (NAA) recognizers and cleaving agents (e.g., aminopeptidases) that carry out the sequencing process. The labeled recognizers bind on and off to the polypeptide when one of their cognate NAAs is exposed at the N-terminus, thereby producing characteristic pulsing patterns. The NAA is cleaved by a cleaving agent, exposing the next amino acid for recognition. The temporal order of NAA recognition and the kinetics of binding enable polypeptide identification and are sensitive to features that modulate binding kinetics, such as post-translational modifications (PTMs).

FIGS. 2A-2G show an example of NAA recognition and dynamic sequencing. FIGS. 2A-2C show example traces demonstrating single-molecule N-terminal recognition by PS610 (FIG. 2A), PS961 (FIG. 2B), and PS691 (FIG. 2C); scatter plots of the number of pulses per recognition segment (RS) v. RS mean pulse duration (PD) are displayed for each peptide in FIGS. 2A-2C, with median PD indicated. FIG. 2D shows example traces from dynamic sequencing of the synthetic peptide FAAWAAYAAAADDD (SEQ ID NO: 813); median PD is indicated above each RS. FIGS. 2E-2G show dynamic sequencing of the synthetic peptide LAQFASIAAYASDDD (SEQ ID NO: 793) using PS610 and PS961. FIG. 2E shows example traces. FIG. 2F shows a scatter plot of RS mean PD v. bin ratio illustrating discrimination of recognizers by bin ratio and NAAs by pulse duration. FIG. 2G shows a scatter plot of the number of pulses per RS v. RS mean PD, grouped by the amino acid label assigned to the RS.

FIGS. 3A-3G show an example of dynamic sequencing of diverse peptides with high-precision kinetic outputs. FIGS. 3A-3E show dynamic sequencing of the peptide DQQRLIFAG (SEQ ID NO: 794). FIG. 3A shows an example trace of DQQRLIFAG (SEQ ID NO: 794). FIG. 3B shows a scatter plot of RS mean PD v. bin ratio. FIG. 3C shows additional example traces of dynamic sequencing of DQQRLIFAG (SEQ ID NO: 794). FIG. 3D shows distributions of the duration of each RS and non-recognition segment (NRS) acquired during sequencing, with mean durations indicated. FIG. 3E shows kinetic signature plots summarizing the characteristic sequencing behavior of DQQRLIFAG (SEQ ID NO: 794) peptide. FIGS. 3F-3G show dynamic sequencing of the synthetic peptides DQQIASSRLAASFAAQQYPDDD (SEQ ID NO: 795) (top), RLAFSALGAADDD (SEQ ID NO: 796) (middle), and EFIAWLV (SEQ ID NO: 797) (bottom). FIG. 3F shows example traces for each peptide. FIG. 3G shows corresponding kinetic signature plots of DQQIASSRLAASFAAQQY (SEQ ID NO: 856), RLAFSAL (SEQ ID NO: 857), and EFIAWLV (SEQ ID NO: 797).

FIGS. 4A-4E show an example of detection of single amino acid changes and PTMs. FIGS. 4A-4B show dynamic sequencing of synthetic peptides that differ by a single amino acid: RLAFAYPDDD (SEQ ID NO: 798) (top), RLIFAYPDDD (SEQ ID NO: 799) (middle), RLVFAYPDDD (SEQ ID NO: 800) (bottom). FIG. 4A shows example traces. FIG. 4B shows scatter plots of RS mean PD v. bin ratio. FIGS. 4C-4D show detection of oxidized methionine using the peptide RLMFAYPDDD (SEQ ID NO: 801). FIG. 4C shows distributions of mean PD for leucine; labels indicate populations with leucine followed by methionine (LM) or methionine sulfoxide (LMo). FIG. 4D shows example traces in which methionine is recognized by PS961 and leucine exhibits long PD (top, RLMFAYPDDD (SEQ ID NO: 801)), or in which methionine is not recognized due to oxidation and leucine exhibits short PD (bottom, RLMoFAYPDDD (SEQ ID NO: 858)). FIG. 4E shows scatter plots of RS mean PD v. bin ratio for runs in which oxidation was not controlled (top) or in which methionine was fully oxidized (bottom).

FIGS. 5A-5C show an example of discrimination of peptides in mixtures and mapping peptides to the human proteome. FIG. 5A shows example traces from sequencing a mixture of the peptides DQQRLIFAG (SEQ ID NO: 794) and RLAFSALGAADDD (SEQ ID NO: 796) on the same chip; the chip window indicates the location of reaction chambers producing a sequencing readout for each peptide. FIG. 5B shows example traces from the dynamic sequencing of two peptides, DQQRLIFAGK (SEQ ID NO: 802) (top) and EFIAWLVK (SEQ ID NO: 803) (bottom), isolated from the recombinant human proteins ubiquitin and GLP-1, respectively. FIG. 5C shows a diagram illustrating identification of the protein ubiquitin as a match to the kinetic signature from DQQRLIFAGK (SEQ ID NO: 802) peptide in an in silico digest of the human proteome based on kinetic information. SEQ ID NOs: 804 (IVNFSRLIFHHLK), 805 (DIRLIFSNAK), 806 (GQSRLIFTYGLTNSGK), 807 (DQQRLLIFAGK), and 808 (DEHCLRLIFLK) are shown.

FIGS. 6A-6F show an example of chip operation. FIG. 6A shows an exploded view of the compact benchtop instrument designed to support the custom semiconductor chip and protein sequencing assay. FIG. 6B shows that the chip achieves electronic rejection by discarding photoelectrons from the pulsed laser before shifting to collect fluorescence photoelectrons from bound NAA recognizers; the timing of the rejection and collection windows cycles between two modes (Bin 1 and Bin 0, example waveforms shown) in alternate frames to provide a bin ratio estimate of the fluorescence lifetime of the dye. FIG. 6C shows that the chip achieves >10,000-fold attenuation of incident laser light within 1 ns from initiation of a rejection mode. FIG. 6D shows example pulses for dyes with short and long fluorescence lifetime, illustrating the difference in signal collection in Bin 0 and Bin 1. FIG. 6E shows distributions of mean RS bin ratio collected for three dyes with different fluorescence lifetime. FIG. 6F shows dye channel identification accuracy increases with the number of pulses captured per RS.

FIGS. 7A-7H show an example of recognizer properties. FIGS. 7A-7E show recognizer kinetic characterization using polarization assays (Example 1, Methods). FIGS. 7A-7B show affinity (K_D) (FIG. 7A) and off-rate (k_off) (FIG. 7B) of PS610 for peptides with N-terminal phenylalanine, tyrosine, and tryptophan. In FIG. 7B, SEQ ID NOs: 809 (FAKLK(FITC)DEESILKQ), 810 (YAKLK(FITC)DEESILKQ), and 811 (WAKLK(FITC)DEESILKQ) are shown. FIG. 7C shows affinity of PS961 for peptides with N-terminal leucine, isoleucine, and valine. FIGS. 7D-7E show affinity of PS691 for a peptide with N-terminal arginine (FIG. 7D) and single-point polarization data measured for peptides with N-terminal arginine, lysine, and histidine using 2000 nM PS691 (FIG. 7E). FIG. 7F shows binding energy was calculated using a computational model (Example 1, Methods) for peptides of initial sequence LAX and LXA, where X=all 20 amino acids; boxplots show the fraction of total binding energy contributed by the amino acid at position 1 (P1), position 2 (P2), and position 3 (P3), with an exponentially decreasing trend from P1 to P3 (R²>0.97). FIG. 7G shows RS mean PD determined in single-molecule assays for LXA and LAX peptides using PS961 and for FXA and FAX peptides using PS610. FIG. 7H shows the non-polar solvation energy term from the computational binding model with PS961 exhibits high correlation with actual RS mean PD values observed in single-molecule assays with peptides containing N-terminal leucine and varying amino acids at the P2 position. Peptides LVFA (SEQ ID NO: 859), LIFA (SEQ ID NO: 860), LVAR (SEQ ID NO: 861), LAFA (SEQ ID NO: 862), LQAR (SEQ ID NO: 863), LDAA (SEQ ID NO: 864), LCAR (SEQ ID NO: 865), LGAA (SEQ ID NO: 866), LMFA (SEQ ID NO: 867), LSAR (SEQ ID NO: 868), and LEFA (SEQ ID NO: 869) are shown.

FIGS. 8A-8E show an example of binding and cleavage rates. FIGS. 8A-8B show interpulse duration (IPD) decreases with increasing recognizer concentration. Scatter plots of RS mean PD v. RS mean IPD are displayed for PS961 binding to LIF (FIG. 8A) and IFA (FIG. 8B) in dynamic sequencing assays at a concentration of 125 nM (orange) or 250 nM (blue); median IPD values are indicated. Recognizer concentration did not affect RS mean PD. FIG. 8C shows single exponential decay curves fit to the RS duration distributions for arginine, leucine, isoleucine, and phenylalanine acquired from dynamic sequencing of the synthetic peptide DQQRLIFAG (SEQ ID NO: 794). FIGS. 8D-8E show that increasing the aminopeptidase concentrations in dynamic sequencing runs of the synthetic peptide DQQRLIFAG (SEQ ID NO: 794) resulted in decreased NRS (FIG. 8D) and RS (FIG. 8E) durations; median RS duration values are indicated.

FIGS. 9A-9G show an example of kinetic signatures from single amino acid changes and PTMs. FIG. 9A shows kinetic signature plots for three peptides: RLAFAYPDDD (SEQ ID NO: 798) (top) , RLIFAYPDDD (SEQ ID NO: 799) (middle), and RLVFAYPDDD (SEQ ID NO: 800) (bottom). FIGS. 9B-9C show incomplete RS information observed in dynamic sequencing of RLIFAYPDDD (SEQ ID NO: 799) peptide. FIG. 9B shows percentage of reads and example traces of each type of observed deletion of one or more RSs in traces beginning with arginine and ending with tyrosine recognition. RLIFY (SEQ ID NO: 812) is shown. FIG. 9C shows percentage of reads and example traces of each type of observed truncation of one or more RSs in traces beginning with arginine. RLIFY (SEQ ID NO: 812) is shown. FIG. 9D shows affinity of PS961 for a peptide with N-terminal methionine measured a polarization assay (Example 1, Methods). FIG. 9E shows binding energy prediction for peptides with N-terminal methionine and methionine sulfoxide (Mo) from computational modeling with PS961 (Example 1, Methods). FIG. 9F shows kinetic signature plots for DQQRLIFAG (SEQ ID NO: 794, residues 1-7 shown) and RLAFSALGAADDD (SEQ ID NO: 796, residues 1-7 shown) peptides mixed and run on the same chip. FIG. 9G shows kinetic signature plots for DQQRLIFAGK (SEQ ID NO: 802, residues 1-7 shown) and EFIAWLVK (SEQ ID NO: 803, residues 1-6 shown) peptides obtained from digestion of recombinant human ubiquitin and GLP-1.

FIGS. 10A-10M show an example of peptide identification using modeled proteome-wide kinetic signatures. FIGS. 10A-10C show heatmaps of predicted pulse durations for PS961 binding tripeptide targets having leucine (FIG. 10A), isoleucine (FIG. 10B), or valine (FIG. 10C) at the N-terminal position. FIGS. 10D-10F show heatmaps of predicted pulse durations for PS610 binding tripeptide targets having phenylalanine (FIG. 10D), tyrosine (FIG. 10E), or tryptophan (FIG. 10F) at the N-terminal position. FIG. 10G shows a heatmap of predicted pulse durations for PS1122 binding tripeptide targets having arginine at the N-terminal position. FIG. 10H shows plots demonstrating high correlation of predicted pulse durations with actual pulse durations from on-chip experiments for PS961 (left plot) and PS610 (right plot). FIGS. 10I-10K show the results from an analysis of the human proteome. FIGS. 10L-10M show the results from an analysis of the E. coli proteome.

FIGS. 11A-11D show example results showing direct identification of arginine PTMs. FIG. 11A shows different arginine PTMs, including symmetric dimethylarginine (SDMA), asymmetric dimethylarginine (ADMA), and citrullinated arginine. FIG. 11B shows an exemplary workflow for collecting samples, preparing libraries of digested peptides, loading on a chip, and conducting on-chip sequencing and data analysis. FIG. 11C shows sequencing data demonstrating that kinetic signatures distinguish peptides containing arginine, ADMA, and SDMA. FIG. 11C-A shows example protein sequencing traces for three synthetic P38MAPKa-derived peptides containing arginine, ADMA, or SDMA at position 2. Full length peptide sequences are indicated for each example trace: YRELRLLK (SEQ ID NO: 834) (top), YRADMAELRKKL (SEQ ID NO: 894) (middle), YR_SDMAELRLLK (SEQ ID NO: 895) (bottom). FIG. 11C-B shows the distribution of recognition segment (RS) mean pulse duration (PD) for RSs corresponding to the initial 4-residue sequence of each peptide: YREL (SEQ ID NO: 814) (left), YRADMAEL (SEQ ID NO: 815) (middle), and YRSDMAEL (SEQ ID NO: 816) (right). Median values are indicated for each distribution. FIG. 11C-C shows interpulse duration (IPD) for arginine v. ADMA detection by PS621. FIG. 11D shows sequencing data demonstrating that kinetic signatures distinguish peptides containing arginine and citrulline. FIG. 11D-A shows example protein sequencing traces for two synthetic peptides containing arginine or citrulline at position 2: peptide sequence LRLAFAYPDDDK (SEQ ID NO: 817) (QP707) and citrullinated peptide sequence LRCitLAFAYPDDDK (SEQ ID NO: 818) (QP789). Full length peptide sequences are indicated for each example trace. FIG. 11D-B shows the distribution of RS mean PD for RSs corresponding to the initial 5-residue sequence of each peptide: LRLAF (SEQ ID NO: 819) (left) and LCitLAF (SEQ ID NO: 820) (right). Median values are indicated for each distribution.

FIGS. 12A-12G show example methods for using kinetic signature information. FIG. 12A shows an example method for determining chemical characteristics of a polypeptide. FIG. 12B shows an example method for determining chemical characteristics of a polypeptide where one or more amino acids of the polypeptide are unrecognizable. FIG. 12C shows an example method for determining chemical characteristics of a polypeptide. FIG. 12D shows an example method for identifying a protein from which a polypeptide originated based on a pulse pattern including at least three recognition segments. FIG. 12E shows an example method of characterizing an amino acid based on a pulse pattern emitted by one or more recognizers bound to a first amino acid. FIG. 12F shows an example method for determining at least one chemical characteristic of an amino acid of a polypeptide. FIG. 12G shows an example method for identifying a disease or disorder in a subject based on at least one chemical characteristic of a polypeptide.

FIG. 13 shows an example schematic of a pixel of an integrated device.

FIGS. 14A-14C show example results showing identification of a threonine PTM. FIGS. 14A-14B show results from sequencing reactions using the recognizers PS691, PS610, and PS961 for the peptides: RLTFIAYPDDD (SEQ ID NO: 821) (FIG. 14A); and RLpTFIAYPDDD (SEQ ID NO: 822), where pT is phosphothreonine (FIG. 14B). FIG. 14C shows recognition segment (RS) durations for leucine recognition in the sequencing reactions of FIGS. 14A (left panel) and 14B (right panel).

FIGS. 15A-15B show example results showing identification of a tyrosine PTM in sequencing reactions using the recognizers PS691, PS610, and PS961 for the peptides: RLYFIAYPDDD (SEQ ID NO: 823) (FIG. 15A); and RLpYFIAYPDDD (SEQ ID NO: 824), where pY is phosphotyrosine (FIG. 15B).

FIGS. 16A-16B show example results showing identification of a lysine PTM in sequencing reactions using the recognizers PS691, PS610, PS961, and PS1165 for the peptides: RLYFKAYPDDD (SEQ ID NO: 825) (FIG. 16A); and RLK{acetyl}FIAYPDDD (SEQ ID NO: 826), where K {acetyl} is an acetylated lysine (FIG. 16B).

FIGS. 17A-17G illustrate aspects of an example application of the technology to identification of β-amyloid variants. FIG. 17A illustrates an example of a β-amyloid variant. FIG. 17B illustrates an example workflow for β-amyloid variant detection. FIGS. 17C-17G illustrate examples of pulse patterns of β-amyloid wild type LVFFAE (SEQ ID NO: 827) versus variants (LVFFAK (SEQ ID NO: 828), LVFFGK (SEQ ID NO: 829), LVFFAG (SEQ ID NO: 830), LVPFAE (SEQ ID NO: 831)).

FIGS. 18A-18B show example results from sequencing reactions using the recognizers PS610, PS1220, and PS1223 for peptide fragments comprising unmodified arginine or citrulline. FIG. 18A shows a plot of bin ratio v. pulse duration for the peptide fragment VRFLEQQNK (SEQ ID NO: 841). FIG. 18B shows a plot of bin ratio v. pulse duration for the peptide fragment VCitFLEQQNK (SEQ ID NO: 842), where Cit is citrulline.

FIGS. 19A-19D show example results from sequencing reactions using the recognizers PS610, PS1220, and PS1223 for the peptide fragment VRFLEQQNK (SEQ ID NO: 841). FIGS. 19A and 19B show example traces, and FIGS. 19C and 19D show example plots of intensity v. bin ratio.

FIGS. 20A-20D show example results from sequencing reactions using the recognizers PS610, PS1220, and PS1223 for the peptide fragment VCitFLEQQNK (SEQ ID NO: 842), where Cit is citrulline. FIGS. 20A and 20B show example traces, and FIGS. 20C and 20D show example plots of intensity v. bin ratio.

FIGS. 21A-21B show example results of mapping kinetic signatures to the human proteome. In FIG. 21A, kinetic signatures from each of 5 clusters of traces from cerebral dopamine neurotrophic factor (CDNF) sequencing were mapped to a database of predicted kinetic signatures for more than 300,000 peptides derived from in silico Lys-C digestion of about 20,000 human proteins, and candidate matching peptides are shown for each cluster. FIG. 21B shows matching peptides for each kinetic signature aligned to the full-length sequence of human CDNF protein.

DETAILED DESCRIPTION

Aspects of the application relate to methods and systems for obtaining information regarding multiple amino acids in a polypeptide based on binding interactions between the polypeptide and one or more amino acid recognizers. For example, kinetic signature information may be obtained from a series of signal pulses indicative of a series of binding events between one or more amino acid recognizers and an amino acid of a polypeptide (e.g., a terminal amino acid, an internal amino acid). The kinetic signature information (e.g., pulse duration, interpulse duration, recognition segment (RS) duration, intersegment duration) may be used to determine one or more chemical characteristics (e.g., identity, modification) of multiple amino acids of the polypeptide.

Protein characterization has a number of important applications, including determination of the presence or absence of a protein (e.g., a disease-relevant protein) in a biological sample, identification of an unknown protein in a biological sample, and identification of a protein responsible for biological activity in an isolated protein fraction. However, conventional methods of characterizing proteins, such as mass spectrometry and affinity-based methods, often face substantial challenges, including the inability to identify unknown proteins and/or differentiate unmodified proteins from proteins with post-translational modifications (PTMs). In contrast, methods and systems described herein may provide accurate characterization of a wide range of proteins. In some aspects, methods and systems described herein use single molecule protein sequencing to identify and/or otherwise characterize proteins based on the kinetic signature of binding between recognizers and polypeptide fragments of the proteins. This approach provides the resolution needed to differentiate between polypeptides with similar sequences or physicochemical properties.

Kinetic signature information can be beneficial for mapping peptides to their proteins of origin at least because the kinetic signature information associated with one amino acid may provide information about the chemical characteristics of multiple amino acids. In some cases, when amino acid recognizers bind to a polypeptide, they contact not just one amino acid, but one or more upstream and/or downstream amino acids. This contact with one or more upstream and/or downstream amino acids can influence kinetic signature information (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration). This sensitivity of kinetic signature information to upstream and/or downstream amino acids can provide a wealth of information on peptide sequence composition and can facilitate mapping peptides to the proteome. In some embodiments, recognizers may bind to a terminal amino acid of a polypeptide and one or more downstream amino acids. In some embodiments, recognizers may bind to an internal amino acid of a polypeptide and one or more upstream and/or downstream amino acids. In this manner, the recognizers may directly or indirectly sense all 20 amino acids found in the human body (i.e., the building blocks of the human proteome), and this information can be encoded in the average pulse duration, interpulse duration, recognition segment (RS) duration, and/or intersegment duration. Additionally, adjacent visible residues in a polypeptide can be represented on average by immediately adjacent RSs (i.e., a consensus gap between two RSs may only occur if there is at least one invisible amino acid between them).

As described herein, signal pulses from a dye-labeled first type of amino acid recognizer that binds to an amino acid, such as the terminal amino acid or an internal amino acid of a polypeptide, may be used to determine one or more chemical characteristics of multiple amino acids of the polypeptide. The inventors have recognized that such techniques are advantageous. For example, such techniques may allow for determining chemical characteristics of amino acids which are unrecognized. Such amino acids may be unrecognizable by any amino acid recognizers present in a reaction chamber, in some instances. Such techniques may also save time, require fewer amino acid recognizers, and/or require less signal collection. Accordingly, obtaining information regarding multiple amino acids based on fewer series of signal pulses and/or using fewer recognizers is advantageous.

In some embodiments, kinetic signature information obtained from a first series of binding events between one or more amino acid recognizers and a first amino acid of a polypeptide (e.g., a terminal amino acid, an internal amino acid) may be used to determine one or more chemical characteristics of at least a second amino acid and a third amino acid of the polypeptide. In certain embodiments, the first amino acid is a terminal amino acid and the second and third amino acids are downstream of the first amino acid. In certain embodiments, the first amino acid is an internal amino acid and the second and third amino acids are independently upstream or downstream of the first amino acid. In some instances, the second amino acid and/or third amino acid are proximate to the first amino acid. In some cases, for example, the second amino acid and/or third amino acid are separated from the first amino acid by 10 amino acids or fewer, 5 amino acids or fewer, 4 amino acids or fewer, 3 amino acids or fewer, 2 amino acids or fewer, 1 amino acid or fewer, or 0 amino acids (i.e., the first amino acid is immediately adjacent to the second amino acid and/or the third amino acid). In some cases, the second amino acid and/or the third amino acid are separated from the first amino acid by at least 1 amino acid, at least 2 amino acids, at least 3 amino acids, at least 4 amino acids, at least 5 amino acids, or at least 10 amino acids. In some cases, the second amino acid and/or the third amino acid are separated from the first amino acid by 1-2 amino acids, 1-3 amino acids, 1-4 amino acids, 1-5 amino acids 1-10 amino acids, 2-3 amino acids, 2-4 amino acids, 2-5 amino acids, 2-10 amino acids, 3-5 amino acids, 3-10 amino acids, or 5-10 amino acids. In certain cases, the second amino acid is proximate to the third amino acid. The second amino acid may be adjacent or non-adjacent to the third amino acid. In some embodiments, the second amino acid is separated from the third amino acid by 10 amino acids or fewer, 5 amino acids or fewer, 4 amino acids or fewer, 3 amino acids or fewer, 2 amino acids or fewer, 1 amino acid or fewer, or 0 amino acids (i.e., the second amino acid is immediately adjacent to the third amino acid). In some cases, the second amino acid is separated from the third amino acid by at least 1 amino acid, at least 2 amino acids, at least 3 amino acids, at least 4 amino acids, at least 5 amino acids, or at least 10 amino acids. In some cases, the second amino acid is separated from the third amino acid by 1-2 amino acids, 1-3 amino acids, 1-4 amino acids, 1-5 amino acids 1-10 amino acids, 2-3 amino acids, 2-4 amino acids, 2-5 amino acids, 2-10 amino acids, 3-5 amino acids, 3-10 amino acids, or 5-10 amino acids.

In some embodiments, the determined one or more chemical characteristics comprise an identity of a first amino acid, a second amino acid, and/or a third amino acid of a polypeptide. In some embodiments, the determined one or more chemical characteristics comprise a modification (e.g., a post-translational modification, a mutation, a bond to a binding component) of a first amino acid, a second amino acid, and/or a third amino acid of a polypeptide. In certain embodiments, the determined one or more chemical characteristics may be used to identify the first amino acid, the second amino acid, and/or the third amino acid. In certain embodiments, the identified amino acids may be used to identify a protein from which the polypeptide originated.

In some aspects, compositions, methods, and systems of the disclosure may be utilized in a dynamic peptide sequencing reaction. In this technique, structural information for polypeptides can be determined by evaluating single-molecule binding interactions between amino acid recognizers and a polypeptide while amino acids are progressively cleaved from a terminal end of the polypeptide. FIG. 1 shows an example of a dynamic peptide sequencing reaction in which individual on-off binding events give rise to signal pulses of a signal output. As shown at left, a protein sample may be fragmented into polypeptides, which are immobilized in reaction chambers of an array, where the immobilized polypeptides are exposed to one or more amino acid recognizers and one or more cleaving agents (e.g., aminopeptidases). As shown at right, an amino acid recognizer reversibly binds a terminal end of the polypeptide, and a detectable signal is produced while the recognizer is bound to the polypeptide. As the on-off binding of recognizers generally occurs at a faster rate than amino acid cleavage, the binding events preceding amino acid cleavage give rise to a series of pulses in a signal output which can be used to determine structural information about amino acids of the polypeptide.

Compositions, systems, and methods for performing dynamic polypeptide sequencing and analyzing data obtained therefrom are described more fully in PCT International Publication No. WO2020102741A1, filed Nov. 15, 2019, and PCT International Publication No. WO2021236983A2, filed May 20, 2021, each of which is incorporated by reference in its entirety.

As used herein, in some embodiments, the term “bond” or “bonds” refers to any non-covalent interaction (e.g., a hydrogen bond, a van der Waals interaction, an aromatic interaction, an electrostatic interaction) or covalent interaction between specified binding components or any plurality thereof, and the terms “bind,” “binding,” “bound,” and like terms refer to the formation and/or existence of any such bonds. As an illustrative example, a binding event between an amino acid recognizer and an amino acid may comprise the formation of one or more non-covalent or covalent interactions between the amino acid recognizer and the amino acid.

In some embodiments, the terminology includes identifying one or more amino acids of a polypeptide. As used herein, in some embodiments, “identifying,” “determining the identity,” and like terms, in reference to an amino acid, include determination of an express identity of an amino acid as well as determination of a probability of an express identity of an amino acid. For example, in some embodiments, an amino acid is identified by determining a probability (e.g., from 0% to 100%) that the amino acid is of a specific type, or by determining a probability for each of a plurality of specific types. Accordingly, in some embodiments, the terms “amino acid sequence,” “polypeptide sequence,” and “protein sequence” as used herein may refer to the polypeptide or protein material itself and is not restricted to the specific sequence information (e.g., the succession of letters representing the order of amino acids from one terminus to another terminus) that biochemically characterizes a specific polypeptide or protein.

Exemplary Techniques for Obtaining Information Regarding Amino Acids

As described herein, the inventors have developed techniques for obtaining information regarding multiple amino acids in a polypeptide based on a series of signal pulses indicative of a series of binding events between one or more amino acid recognizers and an amino acid of the polypeptide. FIGS. 12A-12G show example methods for determining and using kinetic signature information to characterize polypeptides.

The methods described herein may be implemented by a system. For example, in some embodiments, the system comprises at least one non-transitory computer-readable medium having instructions encoded thereon that, when executed, cause a processor to perform one or more of the methods described herein. In some embodiments, the system further comprises the processor. The system may comprise any of the components of the integrated device described herein.

The methods may facilitate obtaining information regarding multiple amino acids. For example, a polypeptide comprising a chain of amino acids may be used with the techniques described herein. The chain of amino acids may comprise at least one amino acid to which a dye-labeled recognizer binds. In some embodiments, the chain of amino acids comprises a terminal amino acid and one or more downstream amino acids (e.g., amino acids at position 1, 2, 3, 4, and/or 5 relative to the polypeptide terminus). In some embodiments, one or more amino acid recognizers may bind to the terminal amino acid. In some embodiments, the one or more amino acid recognizers may bind to one or more amino acids downstream of the terminal amino acid in addition to the terminal amino acid of the peptide. In some embodiments, the one or more amino acid recognizers may bind to an internal amino acid and one or more amino acids upstream or downstream of the internal amino acid.

The polypeptide may comprise any number of amino acids. In some embodiments, the polypeptide comprises at least 5 amino acids, at least 10 amino acids, at least 15 amino acids, at least 20 amino acids, at least 50 amino acids, or at least 100 amino acids. In some embodiments, the polypeptide comprises 5-10, 5-15, 5-20, 5-50, 5-100, 10-15, 10-20, 10-50, 10-100, 15-20, 15-50, 15-100, 20-50, 20-100, or 50-100 amino acids.

In some embodiments, to obtain information regarding the chain of amino acids, a sample comprising at least a portion (e.g., all or a fragment thereof) of the polypeptide may be loaded onto an integrated device, such as the integrated device described herein. In particular, the polypeptide may be loaded into a reaction chamber of the integrated device. In some cases, the polypeptide may be bound to the surface of the chamber via a covalent or non-covalent bond (e.g., a streptavidin-biotin bond, a click chemistry bond) which immobilizes the polypeptide in the chamber.

In some embodiments, multiple polypeptides may be loaded onto the integrated device and multiple chambers of the integrated device may receive one or more of the polypeptides. The techniques described herein for obtaining information regarding polypeptides may be performed in a parallel manner (e.g., concurrently, simultaneously).

FIG. 12A shows an example method 1200 for determining chemical characteristics of a polypeptide. In some embodiments, method 1200 may begin at act 1202. In some embodiments, one or more additional or alternative acts may be performed prior to act 1202, such as any of the loading steps described herein.

At act 1202, a polypeptide may be contacted with one or more amino acid recognizers. As described herein, the polypeptide may comprise a plurality of amino acids. In some embodiments, the polypeptide comprises a first amino acid (e.g., a terminal amino acid, an internal amino acid) to which the one or more amino acid recognizers may bind, and at least one other (e.g., upstream, downstream) amino acid (e.g., a second amino acid).

The one or more amino acid recognizers may comprise a first set of one or more amino acid recognizers that bind to the polypeptide. In some embodiments, the first set of one or more amino acid recognizers may bind to an amino acid of the polypeptide and, in some embodiments, to one or more additional amino acids. In certain embodiments, the first set of one or more amino acid recognizers may bind to a terminal amino acid of the polypeptide and, in some embodiments, to one or more downstream amino acids. In certain embodiments, the first set of one or more amino acid recognizers may bind to an internal amino acid of the polypeptide and, in some embodiments, to one or more upstream and/or downstream amino acids. At least one (and, in some embodiments, each) of the one or more amino acid recognizers may be labeled with a fluorescent dye that emits emission light when excited with excitation light, as described herein. In some cases, the one or more amino acid recognizers comprise a plurality of types of amino acid recognizers. In certain cases, each type of amino acid recognizer may only bind to certain amino acids. As an illustrative example, a first type of amino acid recognizer may preferentially bind to leucine, isoleucine, and valine. As another illustrative example, a second type of amino acid recognizer may preferentially bind to phenylalanine, tyrosine, and tryptophan. As another illustrative example, a third type of amino acid recognizer may preferentially bind to arginine. In some embodiments, the first set of one or more amino acid recognizers comprises one type of amino acid recognizer. In some embodiments, the first set of one or more amino acid recognizers comprises two or more types of amino acid recognizers. In some embodiments, each type of recognizer is labeled with a unique dye and/or a unique number of dyes. Accordingly, the emission light from the dye-labeled amino acid recognizers may be used to obtain information about (e.g., identify) the amino acid to which the dye-labeled amino acid recognizer is bound, and in some embodiments, about one or more additional amino acids.

In some embodiments, contacting the polypeptide with the one or more amino acid recognizers comprises introducing the one or more amino acid recognizers onto the device (e.g., by loading a solution comprising the one or more amino acid recognizers onto the integrated device comprising the polypeptide). The one or more amino acid recognizers may periodically bind to the polypeptide (e.g., to at least one amino acid of the polypeptide). The rate at which the one or more amino acid recognizers bind to the polypeptide is referred to herein as the binding rate. In some embodiments, the one or more amino acid recognizers may be labeled with (e.g., conjugated to) fluorescent dyes that may become excited when the one or more recognizers are bound to or in the vicinity of an amino acid of the polypeptide. Therefore, periodic signals emitted by the fluorescent dyes may be characteristic of the binding rate of the amino acid recognizers.

At act 1204, a first series of signal pulses may be detected. For example, the integrated device may comprise one or more photodetection regions which detect light emitted by the reaction chambers, and more specifically, by the excited fluorescent dyes therein. As described herein, the fluorescent dyes which label the one or more amino acid recognizers may become excited with excitation light (e.g., from at least one light source such as a pulsed laser). When excited, electrons of the fluorescent dyes absorb energy from excitation light and move to a higher energy level. After a period of time, the electrons return to the ground state. When returning to the ground state, the electrons emit energy in the form of photons. The emitted photons (also referred to herein as emission light or signals) may be detected by the integrated device described herein. The signal pulses detected by the integrated device include information characteristic of the sample that the fluorescent dye is bound to (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, whether an amino acid is recognized). In particular, the signal pulses include information characteristic of a fluorescent dye. Each type of amino acid recognizer may be conjugated to a unique combination of one or more fluorescent dyes. Accordingly, the signal pulses may correlate to one or more amino acids and may be used to obtain information regarding the sample.

The first series of signal pulses detected at act 1204 may be indicative of a first series of binding events between a first set of one or more dye-labeled amino acid recognizers and at least one amino acid of the polypeptide. As described herein, the one or more dye-labeled amino acid recognizers may periodically bind to an amino acid (e.g., the terminal amino acid, an internal amino acid) and may emit signals when bound to the amino acid. Accordingly, the first series of signal pulses may be indicative of a series of binding events between the one or more dye-labeled amino acid recognizers and the amino acid, and in some embodiments, one or more upstream and/or downstream amino acids.

At act 1206, at least one chemical characteristic of the polypeptide may be determined based on at least one characteristic of the first series of signal pulses detected at act 1204. In some embodiments, determining at least one chemical characteristic of the polypeptide comprises determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide. In some embodiments, the at least two amino acids include the amino acid to which the one or more amino acid recognizers is bound and one or more other amino acids (e.g., one or more upstream and/or downstream amino acids). In some embodiments, the at least two amino acids include the terminal amino acid and one or more downstream amino acids.

As described herein, at least one characteristic of the series of signal pulses may be determined. Examples of the at least one characteristic include, but are not limited to, intensity, fluorescence lifetime, wavelength, pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, absence of signal pulses, and whether an amino acid is recognized. In some embodiments, the at least one characteristic of the series of signal pulses comprises an average characteristic of the series of signal pulses.

In some embodiments, the at least one characteristic of the series of signal pulses comprises intensity (e.g., average intensity of the series of signal pulses). Intensity may be determined based on an amount of charge carriers detected in the photodetection region which receives the emission light from the fluorescent labels. In some embodiments, emission light from a particular fluorescent label may have a characteristic intensity such that analyzing intensity information of emission light may facilitate identification of one or more chemical characteristics of the polypeptide.

In some embodiments, the at least one characteristic of the series of signal pulses comprises wavelength (e.g., average wavelength of the series of signal pulses). Wavelength of the emission light may be determined in any suitable manner, for example by using one or more optical filters and/or photodetection regions disposed at different depths. In some embodiments, emission light from a particular fluorescent label may have a characteristic wavelength such that analyzing wavelength information of emission light may facilitate identification of one or more chemical characteristics of the polypeptide.

In some embodiments, the at least one characteristic of the series of signal pulses comprises fluorescence lifetime (e.g., average fluorescence lifetime of the series of signal pulses). In some embodiments, fluorescent labels, when excited by incident excitation light, fluoresce with a characteristic lifetime (e.g., a characteristic emission decay time period), such that analyzing the lifetime information of emission light may facilitate identification of one or more chemical characteristics of the polypeptide. Fluorescence lifetime, also referred to herein as simply “lifetime”, is a measure of the time which a fluorescent dye spends in the excited state before returning to a ground state and emitting a photon. In some embodiments, fluorescence lifetime information and/or other timing characteristics described herein may be obtained through techniques for time binning charge carriers generated by photons incident on a photodetection region (e.g., a photodiode).

In some embodiments, the at least one characteristic of the series of signal pulses comprises pulse duration (e.g., average pulse duration), also referred to herein as pulse width. Pulse duration refers to the interval of time measured across a pulse. In some embodiments, pulse width is measured at the full width half maximum of a pulse. As described herein, dye-labeled amino acid recognizers periodically bind and unbind to the polypeptide (e.g., to an amino acid of the polypeptide). When bound, the dye-labeled amino acid recognizers may become excited and emit emission light. The average duration of respective signal pulses emitted by the dye-labeled amino acid recognizers comprise the pulse duration of the fluorescent label. In certain embodiments, for example, at least one characteristic of a first series of signal pulses comprises a first pulse duration, and the first pulse duration comprises an average duration of respective pulses of the first series of signal pulses.

In some embodiments, the at least one characteristic of the series of signal pulses comprises interpulse duration (e.g., average interpulse duration). Interpulse duration, also referred to herein as interpulse width, refers to the interval of time between adjacent pulses. As described herein, dye-labeled amino acid recognizers periodically bind and unbind to the polypeptide (e.g., to an amino acid of the polypeptide). When bound, the dye-labeled amino acid recognizers may become excited and emit emission light. The average durations between signal pulses emitted by the fluorescent label comprise the interpulse duration of the fluorescent label. In certain embodiments, for example, at least one characteristic of a first series of signal pulses comprises a first interpulse duration, and the first interpulse duration comprises an average duration between respective pulses of the first series of signal pulses.

In some embodiments, the at least one characteristic of the series of signal pulses comprises recognition segment (RS) duration. A recognition segment generally refers to a series of signal pulses indicative of a series of binding events between a type of amino acid recognizer (e.g., one or more molecules of the type of amino acid recognizer) and one or more amino acids of a polypeptide. In some cases, for example, a first recognition segment comprises a first series of signal pulses indicative of a series of binding events between a first set of one or more amino acid recognizers and a first amino acid of a polypeptide (and, in some cases, one or more additional amino acids). In some cases, a second recognition segment comprises a second series of signal pulses indicative of a series of binding events between a second set of one or more amino acid recognizers and a second amino acid of the polypeptide (and, in some cases, one or more additional amino acids). A recognition segment duration generally refers to a length of time during which a series of signal pulses is received (i.e., a duration of the recognition segment). In some cases, for example, the first recognition segment may have a first recognition segment duration comprising a length of time during which the first series of signal pulses is received. In some cases, the second recognition segment may have a second recognition segment duration comprising a length of time during which the second series of signal pulses is received.

In some embodiments, the at least one characteristic of the series of signal pulses comprises an intersegment duration. Intersegment duration generally refers to a duration of time between two recognition segments. In certain embodiments, for example, a first intersegment duration comprises a length of time between a first recognition segment and a second recognition segment. The first and second recognition segments may have different characteristics, as described herein, which may allow the recognition segments to be distinguished from each other.

In some embodiments, the at least one characteristic of the series of signal pulses comprises a cleavage rate (e.g., an average cleavage rate) and/or a cleavage time. In some embodiments, for example, a terminal amino acid of the polypeptide disposed in the reaction chamber is cleaved from the polypeptide. In certain embodiments, cleaving the terminal amino acid is performed by exposing the polypeptide to a cleaving agent (e.g., one or more aminopeptidases). In some embodiments, the cleaving agent may be included in the same solution as the amino acid recognizers. Cleavage of an amino acid (e.g., a terminal amino acid) from the polypeptide may be referred to as a cleavage event. A cleavage rate may refer to a number of cleavage events per unit time. A cleavage time may refer to a length of time between cleavage events. In some embodiments, cleavage events may be determined by observing a change from a recognition segment to another recognition segment (e.g., based on different characteristics of the recognition segments), a change from a recognition segment to a non-recognition segment (i.e., a segment during which signal pulses are not received), and/or a change from a non-recognition segment to a recognition segment.

In some embodiments, the at least one characteristic comprises an absence of signal pulses at one or more reference time points. As an illustrative example, a polypeptide may have an expected sequence comprising a first amino acid to which a first amino acid recognizer preferentially binds. In certain embodiments, the expected series of binding events between the first amino acid and the first amino acid recognizer may not occur, and there may be an absence of signal pulses at one or more reference time points. In some cases, the absence of signal pulses may indicate the presence of a modification (e.g., a post-translational modification of the first amino acid, a mutation relative to a wild type protein, a bond to a binding component).

One or more of the characteristics of the series of signal pulses may be used to determine at least one chemical characteristic of a first set of at least two amino acids of the polypeptide. In some embodiments, the first set of at least two amino acids includes the terminal amino acid and at least one downstream amino acid of the polypeptide. In some embodiments, the first set of at least two amino acids includes an internal amino acid and at least one upstream and/or downstream amino acid of the polypeptide. In some embodiments, the at least two amino acids of the polypeptide comprise the amino acid to which the dye-labeled recognizers bind and at least one other amino acid (e.g., one or more upstream and/or downstream amino acids). In some embodiments, the first set of at least two amino acids does not consist of a terminal amino acid and a penultimate amino acid of the polypeptide (i.e., a terminal amino acid and an immediately adjacent amino acid). In some embodiments, the at least two amino acids comprise at least three amino acids, at least four amino acids, at least five amino acids, at least ten amino acids, at least fifteen amino acids, at least twenty amino acids, at least fifty amino acids, or at least one hundred amino acids. In some embodiments, the at least two amino acids comprise two amino acids, three amino acids, four amino acids, five amino acids, ten amino acids, fifteen amino acids, twenty amino acids, fifty amino acids, one hundred amino acids, etc. In some embodiments, the at least two amino acids comprise 2-3 amino acids, 2-4 amino acids, 2-5 amino acids, 2-10 amino acids, 2-15 amino acids, 2-20 amino acids, 2-50 amino acids, 2-100 amino acids, 3-5 amino acids, 3-10 amino acids, 3-15 amino acids, 3-20 amino acids, 3-50 amino acids, 3-100 amino acids, 5-10 amino acids, 5-15 amino acids, 5-20 amino acids, 5-50 amino acids, 5-100 amino acids, 10-15 amino acids, 10-20 amino acids, 10-50 amino acids, 10-100 amino acids, 20-50 amino acids, 20-100 amino acids, or 50-100 amino acids.

In some embodiments, the at least one chemical characteristic comprises an identity of an amino acid (e.g., an identity of one or more of the first set of at least two amino acids). In some embodiments, the at least one chemical characteristic may be used to determine an identity of one or more of the first set of at least two amino acids.

In some embodiments, the at least one chemical characteristic comprises a structural characteristic of an amino acid, including a structural characteristic of one or more of the first set of at least two amino acids (e.g., whether the amino acid comprises a modification, what type of modification the amino acid comprises). In some embodiments, the modification comprises a post-translational modification, an unnatural modification, an oxidative modification, a crosslinking modification, and/or a chemical modification. In some embodiments, the modification comprises one or more mutations relative to a wild type protein. In some embodiments, the modification comprises one or more insertions relative to a wild type protein. In some embodiments, the modification comprises one or more deletions relative to a wild type protein. In some embodiments, the modification comprises a covalent or non-covalent bond to a binding component (e.g., a nucleic acid, a linker, an antibody). In some embodiments, the modification affects the at least one characteristic of the first series of signal pulses (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, absence of signal pulses, whether an amino acid is recognized). The impact of the modification on the at least one characteristic of the first series of signal pulses allows the modification to be identified based on the first series of signal pulses.

Accordingly, in some embodiments, determining at least one chemical characteristic of a polypeptide comprises identifying one or more amino acids of a polypeptide. In some embodiments, identifying an amino acid comprises determining which of the naturally-occurring 20 amino acids is present. In some embodiments, the identity of an amino acid is selected from the group consisting of alanine, arginine, asparagine, aspartic acid, cysteine, glutamine, glutamic acid, glycine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine, and valine. In some embodiments, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises identifying at least one (and, in some embodiments, each) amino acid of the first set of at least two amino acids.

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining a subset of potential amino acids that can be present in the polypeptide. In some embodiments, this can be accomplished by determining that an amino acid is not one or more specific amino acids (and therefore could be any of the other amino acids). In some embodiments, this can be accomplished by determining which of a specified subset of amino acids (e.g., based on size, charge, hydrophobicity, post-translational modification, binding properties) could be in the polypeptide (e.g., using a recognizer that binds to a specified subset of two or more amino acids). In some embodiments, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises determining that at least one (and, in some embodiments, each) amino acid of the first set of at least two amino acids is not one or more specific amino acids.

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that an amino acid of the polypeptide comprises a post-translational modification. The post-translational modification may affect the series of signals emitted by a dye-labeled amino acid recognizer bound to the polypeptide (e.g., to a terminal amino acid and/or an internal amino acid). In some embodiments, the series of signals emitted by the dye-labeled amino acid recognizer may be impacted by the post-translational modification even if the post-translational modification is to an amino acid which does not bind to the dye-labeled amino acid recognizer. In some embodiments, a post-translational modification of an amino acid to which a dye-labeled recognizer binds and/or a post-translational modification of one or more upstream or downstream amino acids may cause at least one characteristic of a series of signal pulses (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, absence of signal pulses) to change (e.g., increase, decrease) relative to an unmodified amino acid. Non-limiting examples of post-translational modifications include acetylation (e.g., acetylated lysine), ADP-ribosylation, caspase cleavage, citrullination, formylation, N-linked glycosylation (e.g., glycosylated asparagine), 0-linked glycosylation (e.g., glycosylated serine, glycosylated threonine), hydroxylation, methylation (e.g., methylated lysine, methylated arginine), myristoylation (e.g., myristoylated glycine), neddylation, nitration (e.g., nitrated tyrosine), chlorination (e.g., chlorinated tyrosine), oxidation/reduction (e.g., oxidized cysteine, oxidized methionine), carbonylation (e.g., carbonylated lysine, carbonylated proline, carbonylated arginine, carbonylated threonine), palmitoylation (e.g., palmitoylated cysteine), phosphorylation, prenylation (e.g., prenylated cysteine), S-nitrosylation (e.g., S-nitrosylated cysteine, S-nitrosylated methionine), sulfation (e.g., sulfated tyrosine), glycation (e.g., glycated lysine), sumoylation (e.g., sumoylated lysine), and ubiquitination (e.g., ubiquitinated lysine).

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that an arginine residue of the polypeptide comprises a post-translational modification. For example, as described herein, amino acid recognizers of the disclosure are capable of distinguishing between different arginine modifications, including symmetric dimethylarginine (SDMA), asymmetric dimethylarginine (ADMA), and citrulline (also referred to as citrullinated arginine). In some embodiments, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises determining that at least one amino acid of the first set of at least two amino acids is a post-translationally modified arginine (e.g., SDMA, ADMA, citrulline).

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that an amino acid of the polypeptide comprises a phosphorylated side chain. For example, in some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that the polypeptide comprises a phosphorylated threonine (e.g., phospho-threonine). In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that the polypeptide comprises a phosphorylated tyrosine (e.g., phospho-tyrosine). In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that the polypeptide comprises a phosphorylated serine (e.g., phospho-serine). In some embodiments, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises determining that at least one (and, in some embodiments, each) amino acid of the first set of at least two amino acids comprises a phosphorylated side chain. In certain embodiments, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises determining that at least one (and, in some embodiments, each) amino acid of the first set of at least two amino acids is a phosphorylated threonine, a phosphorylated tyrosine, and/or a phosphorylated serine.

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that the polypeptide comprises a chemically modified variant of an amino acid, an unnatural amino acid, and/or a proteinogenic amino acid (e.g., selenocysteine, pyrrolysine). Examples of unnatural amino acids include, without limitation, 2-naphthyl-alanine, statine, homoalanine, a-amino acid, β2-amino acid, β3-amino acid, γ-amino acid, 3-pyridyl-alanine, 4-fluorophenyl-alanine, cyclohexyl-alanine, N-alkyl amino acid, peptoid amino acid, homo-cysteine, penicillamine, 3-nitro-tyrosine, homo-phenyl-alanine, t-leucine, hydroxy-proline, 3-Abz, 5-F-tryptophan, and azabicyclo-[2.2.1]heptane. In certain embodiments, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises determining that at least one (and, in some embodiments, each) amino acid of the first set of at least two amino acids is a chemically modified variant of an amino acid, an unnatural amino acid, and/or a proteinogenic amino acid.

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that an amino acid of the polypeptide comprises an oxidative modification. For example, as described herein, amino acid recognizers of the disclosure are capable of distinguishing between oxidized methionine and its unmodified variant. In some embodiments, the oxidative modification comprises an oxidatively-damaged side chain of an amino acid. In some embodiments, the oxidatively-damaged side chain comprises a cysteine-derived product (e.g., disulfide, sulfinic acid, sulfonic acid, sulfenic acid, S-nitrosocysteine), a tyrosine-derived product (e.g., di-tyrosine, 3,4-dihydroxyphenylalanine, 3-chlorotyrosine, 3-nitrotyrosine), a histidine-derived product (e.g., 2-oxohistidine, 4-hydroxy-2-oxohistidine, di-histidine, asparagine, aspartic acid, urea), a methionine-derived product (e.g., sulfoxide, sulfone), a tryptophan-derived product (e.g., di-tryptophan, N-formylkynurenine, kynurenine, 2-oxo-tryptophan oxindolylalanine, 6-nitrotryptophan, hydroxytryptophan), a phenylalanine-derived product (e.g., meta-tyrosine, ortho-tyrosine), or a generic side-chain product (e.g., alcohol, hydroperoxide, aldehyde/ketone carbonyl). Examples of oxidatively damaged amino acids are known in the art, see, e.g., Hawkins, C. L., Davies, M. J. Detection, identification, and quantification of oxidative protein modifications. J Biol Chem. 2019 Dec. 20; 294(51):19683-19708. In certain embodiments, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises determining that at least one (and, in some embodiments, each) amino acid of the first set of at least two amino acids comprises an oxidative modification.

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that an amino acid of the polypeptide comprises a side chain characterized by one or more biochemical properties. For example, an amino acid may comprise a nonpolar aliphatic side chain, a positively charged side chain, a negatively charged side chain, a nonpolar aromatic side chain, or a polar uncharged side chain at physiological pH. Non-limiting examples of an amino acid comprising a nonpolar aliphatic side chain include alanine, glycine, valine, leucine, methionine, and isoleucine. Non-limiting examples of an amino acid comprising a positively charged side chain includes lysine, arginine, and histidine. Non-limiting examples of an amino acid comprising a negatively charged side chain include aspartate and glutamate. Non-limiting examples of an amino acid comprising a nonpolar, aromatic side chain include phenylalanine, tyrosine, and tryptophan. Non-limiting examples of an amino acid comprising a polar uncharged side chain include serine, threonine, cysteine, proline, asparagine, and glutamine.

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises identifying one or more mutations relative to a wild type protein. Non-limiting examples of mutations include substitutions, insertions, and deletions. In certain embodiments, the one or more mutations comprise two or more, three or more, four or more, five or more, ten or more, fifteen or more, or twenty or more mutations. In certain embodiments, the one or more mutations comprise 2-3, 2-4, 2-5, 2-10, 2-15, 2-20, 3-4, 3-5, 3-10, 3-15, 3-20, 5-10, 5-15, 5-20, 10-15, 10-20, or 15-20 mutations. In some cases, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises determining that at least one (and, in some embodiments, each) amino acid of the first set of at least two amino acids has been mutated relative to a wild type protein.

In some embodiments, determining at least one chemical characteristic of a polypeptide comprises determining that at least one amino acid is bound (e.g., via a covalent or non-covalent interaction) to a binding component. Non-limiting examples of suitable binding components include a nucleic acid (e.g., DNA, RNA), a linker, and an antibody. In some instances, one or more amino acids of a polypeptide may be bound to a nucleic acid via one or more non-covalent interactions. In some instances, one or more amino acids of a polypeptide may be bound to a linker via one or more covalent interactions. In certain embodiments, determining at least one chemical characteristic of a first set of at least two amino acids of the polypeptide comprises determining that at least one (and, in some embodiments, each) amino acid of the first set of at least two amino acids is covalently or non-covalently bound to a binding component.

In some embodiments, one or more characteristics of a first series of signal pulses indicative of a first series of binding events between a first set of one or more amino acid recognizers and a first amino acid of a polypeptide (e.g., a terminal amino acid, an internal amino acid) may be impacted by one or more chemical characteristics of the polypeptide. In certain instances, one or more modifications of one or more amino acids (e.g., post-translational modifications, mutations, bonds to binding components) may promote a covalent or non-covalent interaction between one or more amino acid recognizers and the first amino acid (e.g., through electrostatic attraction, pi stacking, hydrogen bond formation, etc.), thereby increasing pulse duration. In certain instances, one or more modifications of one or more amino acids (e.g., post-translational modifications, mutations, presence of binding components) may discourage a covalent or non-covalent interaction between one or more amino acid recognizers and the first amino acid (e.g., through electrostatic repulsion, steric hindrance, etc.), thereby decreasing pulse duration.

In some embodiments, determining at least one chemical characteristic of the polypeptide may comprise comparing at least one characteristic of the series of signal pulses with known characteristics of known amino acid segments. For example, FIGS. 10A-10G illustrate known pulse durations for various amino acid segments. In illustrated embodiments, known pulse durations are shown for various tripeptide segments. Using a table such as those shown in FIGS. 10A-10G and determined characteristic(s) (e.g., pulse duration) from a series of signal pulses may allow for identification of an amino acid segment (e.g., a tripeptide segment, a tetrapeptide segment). A table of known characteristics of amino acid segments may be constructed by theoretical means, by simulation, empirically, or any combination thereof. The amino acid segments may have any length. In some embodiments, a table comprises known characteristics of amino acid segments having three amino acids, four amino acids, five amino acids, ten amino acids, fifteen amino acids, or twenty amino acids. In some embodiments, a table comprises known characteristics of amino acid segments having 3-4, 3-5, 3-10, 3-15, 3-20, 4-5, 4-10, 4-15, 4-20, 5-10, 5-15, 5-20, 10-15, 10-20, or 15-20 amino acids.

In some embodiments, a protein from which the polypeptide originated may be identified. For example, as described herein, the techniques may include identifying one of more of the amino acids of an amino acid segment (e.g., a tripeptide segment, a tetrapeptide segment). Based on the identified amino acids, a protein from which the polypeptide originated may be identified. For example, identifying the protein from which the polypeptide originated may comprise comparing the identified amino acids of the amino acid segment to known information. In some embodiments, identifying a protein from which the polypeptide originated may comprise identifying a pattern in the amino acid segment(s) also present in a candidate matching protein. The pattern may be unique to the candidate matching protein relative to other candidate matching proteins. Accordingly, the techniques described herein may allow for identifying a protein from which a polypeptide originated based on identifying only a portion of the amino acids of the polypeptide. In some embodiments, identifying a polypeptide comprises identifying a protein from which a polypeptide originated. In some embodiments, identifying a polypeptide comprises identifying a pattern of amino acids present in the polypeptide and identifying a candidate matching polypeptide comprising the pattern of amino acids.

The polypeptides described herein may be of any type. In some embodiments, the polypeptide comprises a fragment of a protein. In some embodiments, the polypeptide is derived from a biological source. In certain embodiments, the polypeptide is derived from digestion of one or more proteins present in a biological sample (e.g., a human sample, a non-human animal sample, a plant sample). In some embodiments, the polypeptide is a recombinant polypeptide. In some embodiments, the polypeptide is a synthetic polypeptide.

In some embodiments, a protein is present in a biological sample (e.g., blood, plasma, tissue, saliva, urine, or other biological source). In certain cases, the biological sample is obtained from a human subject or a non-human animal subject. In certain cases, the biological sample is obtained from a plant, fungus, virus, or bacterium. The protein may be a wild type or mutant protein. In some embodiments, the protein is a recombinant protein. In some embodiments, the protein is a synthetic protein.

In some embodiments, a protein is digested (e.g., by an enzymatic or chemical reagent) to produce a plurality of polypeptides. Non-limiting examples of suitable reagents for enzymatic and/or chemical digestion include Lys-C, Arg-C, Asp-N, Lys-N, trypsin, chemotrypsin, BNPS-Skatole, CNBr, caspase, formic acid, glutamyl endopeptidase, hydroxylamine, iodosobenzoic acid, neutrophil elastase, pepsin, proline-endopeptidase, proteinase K, staphylococcal peptidase I, thermolysin, and thrombin.

In some embodiments, a solution comprising a mixture of polypeptides may be introduced onto the integrated device. In some embodiments, a reaction chamber may receive at least one polypeptide. In some embodiments, a reaction chamber may receive at least two polypeptides (which may be different polypeptides). In some embodiments, a first polypeptide and a second polypeptide are disposed in different reaction chambers. Respective series of signals from each of the polypeptides may be obtained and used to obtain the at least one chemical characteristic of the amino acids described herein.

It should be appreciated that determining the at least one chemical characteristic of the first set of at least two amino acids may be based on multiple series of signal pulses, in some embodiments. For example, one or more amino acids of the at least two amino acids may be identified and/or otherwise characterized, as described herein, based on a first series of signal pulses (e.g., a series of signal pulses indicative of a series of binding events between one or more amino acid recognizers and a first amino acid) and at least one additional series of signal pulses (e.g., a series of signal pulses indicative of a series of binding events between one or more amino acid recognizers and a second amino acid). In some embodiments, the first series of signal pulses may be obtained when the one or more amino acids are in a first position in the chain of amino acids of the polypeptide (e.g., a position other than the terminal position) and the second series of signal pulses may be obtained when the one or more amino acids are in a second position in the chain of amino acids of the polypeptide (e.g., in the terminal position) different than the first position. In some embodiments, one or more additional series of signal pulses may be used to identify and/or otherwise characterize the at least two amino acids. Such techniques for multi-sampling the same amino acid(s) may ensure greater accuracy in identifying and/or otherwise characterizing the at least two amino acids.

In some embodiments, a method for determining chemical characteristics of a polypeptide (e.g., method 1200) further comprises detecting a second series of signal pulses indicative of a second series of binding events between a second set of one or more amino acid recognizers and the polypeptide. In some embodiments, the method further comprises determining at least one chemical characteristic of a second set of at least two amino acids of the polypeptide based on at least one characteristic of the second series of signal pulses. In certain embodiments, the method further comprises identifying the polypeptide based on the at least one chemical characteristic of the second set of at least two amino acids of the polypeptide. In certain embodiments, the method further comprises identifying the polypeptide based on at least one chemical characteristic of the first set of at least two amino acids and at least one chemical characteristic of the second set of at least two amino acids.

In certain embodiments, the second set of at least two amino acids of the polypeptide comprises at least one amino acid of the first set of at least two amino acids. As an illustrative example, a first set of at least two amino acids may comprise a first amino acid (e.g., a terminal amino acid), a second amino acid, and a third amino acid, and a second set of at least two amino acids may comprise the second amino acid, the third amino acid, and a fourth amino acid.

The at least one characteristic of the second series of signal pulses may comprise any characteristic described herein (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, whether an amino acid is recognized). In some embodiments, the at least one characteristic of the second series of signal pulses comprises a second recognition segment duration (e.g., a length of time during which the second series of signal pulses is received).

In some embodiments, the at least one characteristic of the second series of signal pulses is based in part on at least one characteristic of the first series of signal pulses. In certain embodiments, the at least one characteristic of the second series of signal pulses comprises a first intersegment duration. In some cases, the first intersegment duration comprises a length of time between a first recognition segment during which the first series of signal pulses is received and a second recognition segment during which the second series of signal pulses is received. In certain embodiments, the at least one characteristic of the second series of signal pulses comprises an average of the first recognition segment duration and the second recognition segment duration. In certain embodiments, the at least one characteristic of the second series of signal pulses comprises an average of the first intersegment duration and a second intersegment duration. In some instances, the second intersegment duration comprises a length of time between the second recognition segment and a third recognition segment during which a third series of signal pulses indicative of a third series of binding events between a third set of one or more amino acid recognizers and the polypeptide is received.

The at least one chemical characteristic of the second set of at least two amino acids may comprise any chemical characteristic described herein. In certain embodiments, determining the at least one chemical characteristic of the second set of at least two amino acids comprises identifying at least one (and, in some cases, each) amino acid of the second set of at least two amino acids. In certain embodiments, determining the at least one chemical characteristic of the second set of at least two amino acids comprises identifying a modification of at least one (and, in some cases, each) amino acid of the second set of at least two amino acids. In some instances, the modification comprises a post-translational modification, an unnatural modification, an oxidative modification, a crosslinking modification, and/or a chemical modification. In some instances, the modification comprises one or more mutations relative to a wild type protein. In some instances, the modification comprises a covalent or non-covalent bond between the at least one amino acid and a binding component (e.g., a nucleic acid, a linker, an antibody).

As described herein, the inventors have recognized characteristics of signal pulses are impacted by not only the amino acid to which a dye-labeled amino acid recognizer is bound, but also by one or more upstream and/or downstream amino acids, which may or may not be bound to the dye-labeled amino acid recognizer. Accordingly, in some embodiments, signals from one or more series of signal pulses may be used to determine chemical characteristics regarding a number of amino acids greater than the number of series of signal pulses used. In some embodiments, at least one of the amino acids may be unrecognized (e.g., unrecognizable) by any amino acid recognizers present in a reaction chamber, meaning no signal pulses which would otherwise result from a dye-labeled amino acid recognizer bound to the amino acid are obtained. Although at least one of the amino acids is unrecognized, information regarding the amino acid may still be obtained from other series of signal pulses.

FIG. 12B shows an example method 1210 for determining chemical characteristics of a polypeptide where one or more amino acids of the polypeptide are unrecognizable. Method 1210 may begin at act 1212 wherein data is obtained during a degradation process of a polypeptide. In some embodiments, the data may comprise at least one series of signal pulses indicative of a series of binding events between the polypeptide and one or more amino acid recognizers. In some embodiments, the series of binding events may be between the one or more amino acid recognizers and at least one amino acid of the polypeptide (e.g., a terminal amino acid exposed at a terminus of the polypeptide, an internal amino acid). The data may be obtained according to any of the techniques described herein.

At act 1214, the obtained data may be analyzed to determine portions of the data. Each of the determined portions of the data may comprise a recognition segment, as described herein. For example, each of the determined portions of the data may correspond to an amino acid of the polypeptide during the degradation process (e.g., an amino acid exposed at a terminus of the polypeptide during the degradation process). The data may comprise at least one recognition segment and at least one non-recognition segment (e.g., a period of time where a series of pulse segments is expected to be received but is not, due to, for example, an amino acid at the terminus of the polypeptide being unrecognized). In some embodiments, the data may comprise a first portion corresponding to a first amino acid of the polypeptide. In certain embodiments, the first portion of the data may comprise a first plurality of signal pulses indicative of a series of binding events between a first type of amino acid recognizer and the first amino acid. In some embodiments, the data may comprise a second portion corresponding to a second amino acid of the polypeptide. In certain embodiments, the second portion of the data may not comprise signal pulses indicative of binding events between any type of amino acid recognizer and the second amino acid (e.g., due to the second amino acid being unrecognizable by the one or more amino acid recognizers).

At act 1216, at least one chemical characteristic of the first amino acid and/or the second amino acid may be determined based on at least one characteristic of the first portion of the data and at least one characteristic of the second portion of the data. The at least one characteristic of the respective portions of the data may comprise any of the characteristics described herein (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, absence of signal pulses, whether an amino acid is recognized). In some embodiments, the at least one characteristic of the second portion of the data comprises a duration of the second portion of data (e.g., a duration in which there is a lack of signal pulses). The at least one chemical characteristic of the respective amino acids may comprise any of the chemical characteristics described herein (e.g., identity, structural modification, presence of a binding component). In certain embodiments, the at least one chemical characteristic of the first amino acid and/or the second amino acid comprises an identity of the first amino acid and/or the second amino acid. In certain embodiments, the at least one chemical characteristic comprises a modification (e.g., a post-translational modification, a mutation, a bond to a binding component) of the first amino acid and/or the second amino acid. In some embodiments, act 1216 comprises determining at least one chemical characteristic of each of the first amino acid and the second amino acid.

As described herein, the techniques described herein may be used for identifying characteristics of amino acids based on known information. FIG. 12C shows an example method 1220 for determining chemical characteristics of a polypeptide. Method 1220 may begin at act 1222 where a first series of signal pulses is detected. The first series of signal pulses may be indicative of a first series of binding events between a first set of one or more amino acid recognizers and the polypeptide. In some embodiments, the first series of signal pulses are indicative of a first series of binding events between the first set of one or more amino acid recognizers and an amino acid of the polypeptide (e.g., a terminal amino acid, an internal amino acid).

At act 1224, at least one characteristic of the first series of signal pulses may be determined. For example, any of the characteristics of signal pulses described herein (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, absence of signal pulses, whether an amino acid is recognized) may be determined at act 1224.

At act 1226, the at least one characteristic of the first series of signal pulses may be compared with known characteristics of a plurality of amino acid segments that comprise at least two amino acids. For example, the “heat maps” shown in FIGS. 10A-10G illustrate known pulse durations for different known tripeptide segments. Act 1226 may be performed using a table such as those shown in FIGS. 10A-10G to compare at least one characteristic of the first series of signal pulses with known characteristics of a plurality of amino acid segments (e.g., tripeptide segments, tetrapeptide segments). The table of known characteristics of a plurality of amino acid segments may be constructed by theoretical means, by simulation, empirically, or any combination thereof. The amino acid segments of the plurality of amino acid segments may have any suitable length. In some embodiments, one or more (and, in some cases, all) of the amino acid segments of the plurality of amino acid segments have a length of at least three amino acids, at least four amino acids, at least five amino acids, at least ten amino acids, at least fifteen amino acids, or at least twenty amino acids. In some embodiments, one or more (and, in some cases, all) of the amino acid segments of the plurality of amino acid segments have a length of three amino acids, four amino acids, five amino acids, ten amino acids, fifteen amino acids, or twenty amino acids. In some embodiments, one or more of the at least two amino acids of the amino acid segments are contiguous. In some embodiments, one or more of the at least two amino acids of the amino acid segments are non-contiguous (e.g., separated by one or more amino acids).

At act 1228, at least one chemical characteristic of at least two amino acids of the polypeptide may be determined based on the comparing. For example, any of the chemical characteristics described herein may be determined (e.g., identities of the amino acids, identities or presence of modifications). In some embodiments, determining at least one chemical characteristic of the at least two amino acids comprises identifying at least one (and, in some cases, both) of the at least two amino acids. In some embodiments, determining at least one chemical characteristic of the at least two amino acids comprises identifying a modification (e.g., a post-translational modification, a mutation, a bond to a binding component) of at least one (and, in some cases, both) of the at least two amino acids. The comparing may be performed according to any of the techniques described herein. For example, the comparing may be performed using an algorithm or by manual comparison. In some embodiments, the method may further comprise identifying a protein from which the polypeptide originated based on the determined chemical characteristics.

In some embodiments, additional series of signal pulses may be obtained. For example, the method may further comprise detecting a second series of signal pulses indicative of a second series of binding events between a second set of one or more amino acid recognizers and the polypeptide. In certain embodiments, the second series of signal pulses may be indicative of a second series of binding events between the second set of one or more amino acid recognizers and a subsequent amino acid of the polypeptide (e.g., a second amino acid which becomes the terminal amino acid after cleaving the initial terminal amino acid). In some embodiments, at least one characteristic of the second series of signal pulses may be determined and compared to known characteristics of the plurality of amino acid segments. The at least one chemical characteristic of the amino acids may be determined based on the respective one or more characteristics of the first series of signal pulses and the second series of signal pulses.

FIG. 12D shows an example method 1230 for identifying a protein from which a polypeptide originated based on a pulse pattern including at least three recognition segments. Method 1230 may begin at 1232 where data is obtained during a degradation process of the polypeptide. The data may comprise series of signal pulses indicative of respective binding events with at least three amino acids (e.g., at least three recognition segments).

At act 1234, the data may be analyzed to determine at least three portions of the data. In some embodiments, each portion corresponds to an amino acid of the polypeptide and comprises a plurality of signal pulses indicative of a series of binding events between one or more amino acid recognizers and the amino acid. For example, in certain embodiments, a first portion of the data comprises a first recognition segment and corresponds to a first amino acid. In some embodiments, the first portion of the data comprises a plurality of signal pulses indicative of a series of binding events between one or more amino acid recognizers and the first amino acid. In certain embodiments, a second portion of the data comprises a second recognition segment and corresponds to a second amino acid. In some embodiments, the second portion of the data comprises a plurality of signal pulses indicative of a series of binding events between one or more amino acid recognizers and the second amino acid. In certain embodiments, a third portion of the data comprises a third recognition segment and corresponds to a third amino acid. In some embodiments, the third portion of the data comprises a plurality of signal pulses indicative of a series of binding events between one or more amino acid recognizers and the third amino acid. In some cases, the first amino acid is an amino acid exposed at the terminal of the polypeptide during the degradation process. In some cases, the first amino acid is an internal amino acid.

At act 1236, one or more characteristics of each of the at least three portions of the data may be determined. The one or more characteristics may comprise any of the characteristics described herein (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, absence of signal pulses, whether an amino acid is recognized, etc.).

At act 1238, a protein from which the polypeptide originated may be identified based on the order of the at least three portions of the data and the one or more characteristics of each of the at least three portions of the data. For example, the one or more characteristics of the at least three portions of the data may be used to identify at least three amino acids of the polypeptide. The identities of the at least three amino acids may be used, according to the techniques described herein, for example, to identify a protein from which the polypeptide originated. In some embodiments, the at least three portions of the data comprise at least four portions, at least five portions, at least six portions, at least seven portions, at least eight portions, at least nine portions, at least ten portions, at least fifteen portions, at least twenty portions, or at least fifty portions of the data. In certain embodiments, the at least three portions of the data comprise 3-4 portions, 3-5 portions, 3-10 portions, 3-15 portions, 3-20 portions, 3-50 portions, 5-10 portions, 5-15 portions, 5-20 portions, 5-50 portions, 10-15 portions, 10-20 portions, 10-50 portions, or 20-50 portions of the data.

FIG. 12E shows an example method 1240 of characterizing a second amino acid based on a pulse pattern emitted by one or more amino acid recognizers bound to a first amino acid. The method 1240 may begin at act 1242 where a series of signal pulses indicative of a series of binding events between one or more amino acid recognizers and a first amino acid of a polypeptide is detected. Detecting the series of signal pulses may be performed in accordance with any of the techniques described herein.

At act 1244, at least one characteristic of the series of signal pulses may be used to determine at least one chemical characteristic of a second amino acid of the polypeptide. The at least one characteristic of the series of signal pulses may be any characteristic described herein (e.g., pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, absence of signal pulses, whether an amino acid is recognized). The at least one chemical characteristic of the second amino acid may be any chemical characteristic described herein. Accordingly, signals obtained based on binding of one or more amino acid recognizers to a first amino acid of a polypeptide may be used to identify (or otherwise characterize) a second amino acid of the polypeptide. The inventors have recognized that such a technique is especially beneficial in instances where the second amino acid is unrecognizable (e.g., by the one or more amino acid recognizers).

In some embodiments, determining the at least one chemical characteristic of the second amino acid comprises identifying the second amino acid. In some embodiments, determining the at least one chemical characteristic of the second amino acid comprises identifying a modification of the second amino acid (e.g., a post-translational modification, a mutation, a bond to a binding component).

The polypeptide may comprise a chain of amino acids including the first and second amino acids. In some embodiments, the second amino acid is downstream of the first amino acid. In some embodiments, the second amino acid is upstream of the first amino acid. In some embodiments, the second amino acid is contiguous (e.g., adjacent) to the first amino acid. In some embodiments, the second amino acid is separated from the first amino acid in the chain of amino acids by at least one amino acid (e.g., a third amino acid). In some embodiments, the second amino acid is separated from the first amino acid by at least five amino acids, at least ten amino acids, at least fifteen amino acids, or at least 20 amino acids. In some embodiments, the second amino acid is separated from the first amino acid by five amino acids or fewer.

FIG. 12F shows an example method 1250 for determining at least one chemical characteristic of an amino acid of a polypeptide. Method 1250 may begin at act 1252 where a first series of signal pulses indicative of a first series of binding events between a first set of one or more amino acid recognizers and a first amino acid of a polypeptide are detected. Detecting the first series of signal pulses may be performed in accordance with any of the techniques described herein.

At act 1254, a second series of signal pulses indicative of a second series of binding events between a second set of amino acid recognizers and a second amino acid of the polypeptide may be detected. Detecting the second series of signal pulses may be performed in accordance with any of the techniques described herein.

At act 1256, at least chemical characteristic of the second amino acid may be determined based on at least one characteristic of the first series of signal pulses and at least one characteristic of the second series of signal pulses. As described herein, the inventors have recognized that multi-sampling of signal pulses for an amino acid may be advantageous. For example, multi-sampling may advantageously enhance accuracy of identification and/or other characterization of an amino acid. At act 1256, at least one chemical characteristic of the second amino acid may be determined based on at least one characteristic from each of two signal pulses. The at least one characteristic of the respective series of signal pulses may be the same, in some embodiments, or different, in other embodiments. The characteristic of the series of signal pulses may be any of the characteristics described herein, including but not limited to pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, absence of signal pulses, whether an amino acid is recognized, or any other characteristic.

In some embodiments, additional series of signal pulses may be used. For example, in some embodiments, a third series of signal pulses indicative of a series of binding events between a third set of one or more amino acid recognizers and a third amino acid of the polypeptide may be detected. Determining the at least one chemical characteristic of the second amino acid may be based on at least one characteristic of each of the first, second, and third series of signal pulses.

FIG. 12G shows an example method 1260 of identifying a disease or disorder in a subject. In some embodiments, the subject is a human subject. In some embodiments, the subject is a non-human animal subject.

The method 1260 may begin at act 1262 where a protein in a sample from a subject may be digested to produce a plurality of polypeptides. The protein may be any protein. Examples of a protein of interest include, but are not limited to, vimentin and a β-amyloid protein. Digesting the protein may be performed in accordance with any of the enzymatic and/or chemical techniques described herein.

At act 1264, a polypeptide of the plurality of polypeptides may be contacted with one or more amino acid recognizers and a cleaving agent. The amino acid recognizers may be any amino acid recognizers described herein. The cleaving agent may be any cleaving agent described herein.

At act 1266, one or more series of signal pulses indicative of binding events between one or more amino acid recognizers and the polypeptide are detected as amino acids are progressively cleaved from a terminus of the polypeptide by the cleaving agent. Detecting the series of signal pulses may be performed in accordance with any of the techniques described herein.

At act 1268, at least one characteristic of the one or more series of signal pulses may be used to determine at least one chemical characteristic of the polypeptide. The at least one characteristic of the one or more series of signal pulses may comprise any characteristic described herein. In some embodiments, the at least one characteristic comprises pulse duration, interpulse duration, recognition segment duration, intersegment duration, cleavage rate, cleavage time, intensity, wavelength, fluorescence lifetime, whether an amino acid is recognized). In some embodiments, the at least one characteristic comprises an absence of signal pulses at one or more reference time points.

The at least one chemical characteristic may comprise any chemical characteristic described herein. In certain embodiments, the at least one chemical characteristic is indicative of a modification of the protein. In some embodiments, the modification is a post-translational modification. The post-translational modification may be any post-translational modification described herein. In certain embodiments, the post-translational modification comprises citrullination of at least one amino acid. In some instances, the at least one amino acid comprises arginine. In certain embodiments, the post-translational modification comprises methylation (e.g., demethylation) of at least one amino acid. In some instances, the at least one amino acid comprises arginine and/or lysine. In certain embodiments, the post-translational modification comprises phosphorylation of at least one amino acid. In some instances, the at least one amino acid comprises threonine, tyrosine, and/or serine. In certain embodiments, the post-translational modification comprises acetylation of at least one amino acid. In some instances, the at least one amino acid comprises lysine. In certain embodiments, the post-translational modification comprises oxidation of at least one amino acid. In some instances, the at least one amino acid comprises methionine and/or cysteine. In some embodiments, the modification comprises one or more mutations relative to a wild type protein.

In some embodiments, the modification of the protein is indicative of a disease or disorder in the subject. Non-limiting examples of diseases or disorders include a cardiovascular disease, an autoimmune disease, a cancer, and/or a neurodegenerative disease. In certain embodiments, the disease or disorder comprises an autoimmune disease. Non-limiting examples of autoimmune diseases include rheumatoid arthritis, Crohn's disease, lupus, and multiple sclerosis. In certain embodiments, the disease or disorder comprises a cancer. Non-limiting examples of cancers include lung cancer, breast cancer, prostate cancer, skin cancer, brain cancer, oral cancer, gastrointestinal cancer, and colorectal cancer. In certain embodiments, the disease or disorder comprises a neurodegenerative disease. A non-limiting example of a neurodegenerative disease is Alzheimer's disease.

Amino Acid Recognizers

In some aspects, the techniques described herein can be performed using any amino acid recognizer known in the art. See, for example, PCT International Publication No. WO2020102741A1, filed Nov. 15, 2019, and PCT International Publication No. WO2021236983A2, filed May 20, 2021, which describe amino acid recognizers (e.g., recognition molecules) in detail, the relevant contents of which are incorporated by reference in their entirety.

In some embodiments, an amino acid recognizer of the disclosure comprises an amino acid binding protein having an amino acid sequence selected from Table 1. Table 1 herein provides a list of example sequences of amino acid binding proteins. It should be appreciated that these sequences and other examples described herein are meant to be non-limiting, and amino acid recognizers in accordance with the disclosure can include any homologs, variants, or fragments thereof minimally containing domains or subdomains responsible for amino acid recognition.

In some embodiments, the amino acid binding protein has an amino acid sequence that is at least 80% identical to an amino acid sequence selected from Table 1. In some embodiments, an amino acid binding protein has at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 85%, at least 90%, at least 95%, at least 98%, or higher, amino acid sequence identity to an amino acid sequence selected from Table 1. In some embodiments, an amino acid binding protein has 25-50%, 50-60%, 60-70%, 70-80%, 80-90%, 90-95%, 95-99%, 40-100%, 50-100%, 60-100%, 70-100%, 80-100%, 90-100%, or 95-100% amino acid sequence identity to an amino acid sequence selected from Table 1.

For the purposes of comparing two or more amino acid sequences, the percentage of “sequence identity” between a first amino acid sequence and a second amino acid sequence (also referred to herein as “amino acid identity”) may be calculated by: dividing [the number of amino acid residues in the first amino acid sequence that are identical to the amino acid residues at the corresponding positions in the second amino acid sequence] by [the total number of amino acid residues in the first amino acid sequence] and multiplying by [100], in which each deletion, insertion, substitution or addition of an amino acid residue in the second amino acid sequence compared to the first amino acid sequence is considered as a difference at a single amino acid residue (position). Alternatively, the degree of sequence identity between two amino acid sequences may be calculated using a known computer algorithm (e.g., by the local homology algorithm of Smith and Waterman (1970) Adv. Appl. Math. 2:482c, by the homology alignment algorithm of Needleman and Wunsch, J. Mol. Biol. (1970) 48:443, by the search for similarity method of Pearson and Lipman. Proc. Natl. Acad. Sci. USA (1998) 85:2444, or by computerized implementations of algorithms available as Blast, Clustal Omega, or other sequence alignment algorithms) and, for example, using standard settings. Usually, for the purpose of determining the percentage of “sequence identity” between two amino acid sequences in accordance with the calculation method outlined hereinabove, the amino acid sequence with the greatest number of amino acid residues will be taken as the “first” amino acid sequence, and the other amino acid sequence will be taken as the “second” amino acid sequence.

Additionally, or alternatively, two or more sequences may be assessed for the identity between the sequences. The terms “identical” or percent “identity” in the context of two or more amino acid sequences refer to two or more sequences or subsequences that are the same. Two sequences are “substantially identical” if two sequences have a specified percentage of amino acid residues that are the same (e.g., at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, 99.5%, 99.6%, 99.7%, 99.8%, or 99.9% identical) over a specified region or over the entire sequence, when compared and aligned for maximum correspondence over a comparison window, or designated region as measured using one of the above sequence comparison algorithms or by manual alignment and visual inspection. Optionally, the identity exists over a region that is at least about 25, 50, 75, or 100 amino acids in length, or over a region that is 100 to 150, 150 to 200, 100 to 200, or 200 or more, amino acids in length.

Additionally, or alternatively, two or more sequences may be assessed for the alignment between the sequences. The terms “alignment” or percent “alignment” in the context of two or more amino acid sequences refer to two or more sequences or subsequences that are the same. Two sequences are “substantially aligned” if two sequences have a specified percentage of amino acid residues that are the same (e.g., at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, 99.5%, 99.6%, 99.7%, 99.8% or 99.9% identical) over a specified region or over the entire sequence, when compared and aligned for maximum correspondence over a comparison window, or designated region as measured using one of the above sequence comparison algorithms or by manual alignment and visual inspection. Optionally, the alignment exists over a region that is at least about 25, 50, 75, or 100 amino acids in length, or over a region that is 100 to 150, 150 to 200, 100 to 200, or 200 or more amino acids in length.

In some embodiments, the amino acid binding protein comprises a modified amino acid binding protein and includes one or more amino acid deletions, additions, or mutations relative to a sequence set forth in Table 1. In some embodiments, a modified amino acid binding protein includes a deletion, addition, or mutation of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, or more amino acids (which may or may not be consecutive amino acids) relative to a sequence set forth in Table 1.

Devices and Systems

Methods in accordance with the disclosure, in some aspects, may be performed using a system that permits single-molecule analysis. The system may include an integrated device and an instrument configured to interface with the integrated device. The integrated device may include an array of pixels, where individual pixels include a reaction chamber and at least one photodetector. The reaction chambers of the integrated device may be formed on or through a surface of the integrated device and be configured to receive a sample placed on the surface of the integrated device. Collectively, the reaction chambers may be considered as an array of reaction chambers. The plurality of reaction chambers may have a suitable size and shape such that at least a portion of the reaction chambers receive a single sample (e.g., a single molecule, such as a polypeptide). In some embodiments, the number of samples within a reaction chamber may be distributed among the reaction chambers of the integrated device such that some reaction chambers contain one sample while others contain zero, two or more samples.

Excitation light is provided to the integrated device from one or more light sources external to the integrated device. Optical components of the integrated device may receive the excitation light from the light source and direct the light towards the array of reaction chambers of the integrated device and illuminate an illumination region within the reaction chamber. In some embodiments, a reaction chamber may have a configuration that allows for the sample to be retained in proximity to a surface of the reaction chamber, which may ease delivery of excitation light to the sample and detection of emission light from the sample. A sample positioned within the illumination region may emit emission light in response to being illuminated by the excitation light. For example, the sample may be labeled with a fluorescent label, which emits light in response to achieving an excited state through the illumination of excitation light. Emission light emitted by a sample may then be detected by one or more photodetectors within a pixel corresponding to the reaction chamber with the sample being analyzed. When performed across the array of reaction chambers, which may range in number between approximately 10,000 pixels to 1,000,000 pixels according to some embodiments, multiple samples can be analyzed in parallel.

The integrated device may include an optical system for receiving excitation light and directing the excitation light among the reaction chamber array. The optical system may include one or more grating couplers configured to couple excitation light to other optical components of the integrated device and direct the excitation light to the other optical components. For example, the optical system may include optical components that direct the excitation light from the grating coupler(s) towards the reaction chamber array. Such optical components may include optical splitters, optical combiners, and waveguides. In some embodiments, one or more optical splitters may couple excitation light from a grating coupler and deliver excitation light to at least one of the waveguides. According to some embodiments, the optical splitter may have a configuration that allows for delivery of excitation light to be substantially uniform across all the waveguides such that each of the waveguides receives a substantially similar amount of excitation light. Such embodiments may improve performance of the integrated device by improving the uniformity of excitation light received by reaction chambers of the integrated device. Examples of suitable components, e.g., for coupling excitation light to a reaction chamber and/or directing emission light to a photodetector, to include in an integrated device are described in U.S. patent application Ser. No. 14/821,688, filed Aug. 7, 2015, titled “INTEGRATED DEVICE FOR PROBING, DETECTING AND ANALYZING MOLECULES,” and U.S. patent application Ser. No. 14/543,865, filed Nov. 17, 2014, titled “INTEGRATED DEVICE WITH EXTERNAL LIGHT SOURCE FOR PROBING, DETECTING, AND ANALYZING MOLECULES,” both of which are incorporated by reference in their entirety. Examples of suitable grating couplers and waveguides that may be implemented in the integrated device are described in U.S. patent application Ser. No. 15/844,403, filed Dec. 15, 2017, titled “OPTICAL COUPLER AND WAVEGUIDE SYSTEM,” which is incorporated by reference in its entirety.

Additional photonic structures may be positioned between the reaction chambers and the photodetectors and configured to reduce or prevent excitation light from reaching the photodetectors, which may otherwise contribute to signal noise in detecting emission light. In some embodiments, metal layers which may act as a circuitry for the integrated device, may also act as a spatial filter. Examples of suitable photonic structures may include spectral filters, a polarization filters, and spatial filters and are described in U.S. patent application Ser. No. 16/042,968, filed Jul. 23, 2018, titled “OPTICAL REJECTION PHOTONIC STRUCTURES,” and U.S. Provisional Patent Application No. 63/124,655, filed Dec. 11, 2020, titled “INTEGRATED CIRCUIT WITH IMPROVED CHARGE TRANSFER EFFICIENCY AND ASSOCIATED TECHNIQUES,” both of which are incorporated by reference in their entirety.

Components located off of the integrated device may be used to position and align an excitation source to the integrated device. Such components may include optical components including lenses, mirrors, prisms, windows, apertures, attenuators, and/or optical fibers. Additional mechanical components may be included in the instrument to allow for control of one or more alignment components. Such mechanical components may include actuators, stepper motors, and/or knobs. Examples of suitable excitation sources and alignment mechanisms are described in U.S. patent application Ser. No. 15/161,088, filed May 20, 2016, titled “PULSED LASER AND SYSTEM,” which is incorporated by reference in its entirety. Another example of a beam-steering module is described in U.S. patent application Ser. No. 15/842,720, filed Dec. 14, 2017, titled “COMPACT BEAM SHAPING AND STEERING ASSEMBLY,” which is incorporated herein by reference. Additional examples of suitable excitation sources are described in U.S. patent application Ser. No. 14/821,688, filed Aug. 7, 2015, titled “INTEGRATED DEVICE FOR PROBING, DETECTING AND ANALYZING MOLECULES,” which is incorporated by reference in its entirety.

The photodetector(s) positioned with individual pixels of the integrated device may be configured and positioned to detect emission light from the pixel's corresponding reaction chamber. Examples of suitable photodetectors are described in U.S. patent application Ser. No. 14/821,656, filed Aug. 7, 2015, titled “INTEGRATED DEVICE FOR TEMPORAL BINNING OF RECEIVED PHOTONS,” which is incorporated by reference in its entirety. In some embodiments, a reaction chamber and its respective photodetector(s) may be aligned along a common axis. In this manner, the photodetector(s) may overlap with the reaction chamber within the pixel.

Characteristics of the detected emission light may provide an indication for identifying the label associated with the emission light. Such characteristics may include any suitable type of characteristic, including an arrival time of photons detected by a photodetector, an amount of photons accumulated over time by a photodetector, and/or a distribution of photons across two or more photodetectors. In some embodiments, such characteristics can be any one or a combination of two or more of luminescence lifetime, luminescence intensity, brightness, absorption spectra, emission spectra, luminescence quantum yield, wavelength (e.g., peak wavelength), and signal characteristics (e.g., pulse duration, interpulse durations, change in signal magnitude).

In some embodiments, a photodetector may have a configuration that allows for the detection of one or more timing characteristics associated with a sample's emission light (e.g., luminescence lifetime). The photodetector may detect a distribution of photon arrival times after a pulse of excitation light propagates through the integrated device, and the distribution of arrival times may provide an indication of a timing characteristic of the sample's emission light (e.g., a proxy for luminescence lifetime). In some embodiments, the one or more photodetectors provide an indication of the probability of emission light emitted by the label (e.g., luminescence intensity). In some embodiments, a plurality of photodetectors may be sized and arranged to capture a spatial distribution of the emission light. Output signals from the one or more photodetectors may then be used to distinguish a label from among a plurality of labels, where the plurality of labels may be used to identify a sample within the sample. In some embodiments, a sample may be excited by multiple excitation energies, and emission light and/or timing characteristics of the emission light emitted by the sample in response to the multiple excitation energies may distinguish a label from a plurality of labels.

In operation, parallel analyses of samples within the reaction chambers are carried out by exciting some or all of the samples within the chambers using excitation light and detecting signals from sample emission with the photodetectors. Emission light from a sample may be detected by a corresponding photodetector and converted to at least one electrical signal. The electrical signals may be transmitted along conducting lines in the circuitry of the integrated device, which may be connected to an instrument interfaced with the integrated device. The electrical signals may be subsequently processed and/or analyzed. Processing or analyzing of electrical signals may occur on a suitable computing device either located on or off the instrument.

The instrument may include a user interface for controlling operation of the instrument and/or the integrated device. The user interface may be configured to allow a user to input information into the instrument, such as commands and/or settings used to control the functioning of the instrument. In some embodiments, the user interface may include buttons, switches, dials, and a microphone for voice commands. The user interface may allow a user to receive feedback on the performance of the instrument and/or integrated device, such as proper alignment and/or information obtained by readout signals from the photodetectors on the integrated device. In some embodiments, the user interface may provide feedback using a speaker to provide audible feedback. In some embodiments, the user interface may include indicator lights and/or a display screen for providing visual feedback to a user.

In some embodiments, the instrument may include a computer interface configured to connect with a computing device. The computer interface may be a USB interface, a FireWire interface, or any other suitable computer interface. A computing device may be any general purpose computer, such as a laptop or desktop computer. In some embodiments, a computing device may be a server (e.g., cloud-based server) accessible over a wireless network via a suitable computer interface. The computer interface may facilitate communication of information between the instrument and the computing device. Input information for controlling and/or configuring the instrument may be provided to the computing device and transmitted to the instrument via the computer interface. Output information generated by the instrument may be received by the computing device via the computer interface. Output information may include feedback about performance of the instrument, performance of the integrated device, and/or data generated from the readout signals of the photodetector.

In some embodiments, the instrument may include a processing device configured to analyze data received from one or more photodetectors of the integrated device and/or transmit control signals to the excitation source(s). In some embodiments, the processing device may comprise a general purpose processor, a specially-adapted processor (e.g., a central processing unit (CPU) such as one or more microprocessor or microcontroller cores, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a custom integrated circuit, a digital signal processor (DSP), or a combination thereof). In some embodiments, the processing of data from one or more photodetectors may be performed by both a processing device of the instrument and an external computing device. In other embodiments, an external computing device may be omitted and processing of data from one or more photodetectors may be performed solely by a processing device of the integrated device.

According to some embodiments, the instrument that is configured to analyze samples based on luminescence emission characteristics may detect differences in luminescence lifetimes and/or intensities between different luminescent molecules (e.g., fluorescent molecules), and/or differences between lifetimes and/or intensities of the same luminescent molecules in different environments. The inventors have recognized and appreciated that differences in luminescence emission lifetimes can be used to discern between the presence or absence of different luminescent molecules and/or to discern between different environments or conditions to which a luminescent molecule is subjected. In some cases, discerning luminescent molecules based on lifetime (rather than emission wavelength, for example) can simplify aspects of the system. As an example, wavelength-discriminating optics (such as wavelength filters, dedicated detectors for each wavelength, dedicated pulsed optical sources at different wavelengths, and/or diffractive optics) may be reduced in number or eliminated when discerning luminescent molecules based on lifetime. In some cases, a single pulsed optical source operating at a single characteristic wavelength may be used to excite different luminescent molecules that emit within a same wavelength region of the optical spectrum but have measurably different lifetimes. An analytic system that uses a single pulsed optical source, rather than multiple sources operating at different wavelengths, to excite and discern different luminescent molecules emitting in a same wavelength region can be less complex to operate and maintain, more compact, and may be manufactured at lower cost.

Although analytic systems based on luminescence lifetime analysis may have certain benefits, the amount of information obtained by an analytic system and/or detection accuracy may be increased by allowing for additional detection techniques. For example, some embodiments of the systems may additionally be configured to discern one or more properties of a sample based on luminescence wavelength and/or luminescence intensity. In some implementations, luminescence intensity may be used additionally or alternatively to distinguish between different luminescent labels. For example, some luminescent labels may emit at significantly different intensities or have a significant difference in their probabilities of excitation (e.g., at least a difference of about 35%) even though their decay rates may be similar. By referencing binned signals to measured excitation light, it may be possible to distinguish different luminescent labels based on intensity levels.

According to some embodiments, different luminescence lifetimes may be distinguished with a photodetector that is configured to time-bin luminescence emission events following excitation of a luminescent label. The time binning may occur during a single charge-accumulation cycle for the photodetector. A charge-accumulation cycle is an interval between read-out events during which photo-generated carriers are accumulated in bins of the time-binning photodetector. Examples of a time-binning photodetector are described in U.S. patent application Ser. No. 14/821,656, filed Aug. 7, 2015, titled “INTEGRATED DEVICE FOR TEMPORAL BINNING OF RECEIVED PHOTONS,” which is incorporated herein by reference. In some embodiments, a time-binning photodetector may generate charge carriers in a photon absorption/carrier generation region and directly transfer charge carriers to a charge carrier storage bin in a charge carrier storage region. In such embodiments, the time-binning photodetector may not include a carrier travel/capture region. Such a time-binning photodetector may be referred to as a “direct binning pixel.” Examples of time-binning photodetectors, including direct binning pixels, are described in U.S. patent application Ser. No. 15/852,571, filed Dec. 22, 2017, titled “INTEGRATED PHOTODETECTOR WITH DIRECT BINNING PIXEL,” which is incorporated herein by reference.

In some embodiments, different numbers of fluorophores of the same type may be linked to different reagents in a sample, so that each reagent may be identified based on luminescence intensity. For example, two fluorophores may be linked to a first labeled recognition molecule and four or more fluorophores may be linked to a second labeled recognition molecule. Because of the different numbers of fluorophores, there may be different excitation and fluorophore emission probabilities associated with the different recognition molecules. For example, there may be more emission events for the second labeled recognition molecule during a signal accumulation interval, so that the apparent intensity of the bins is significantly higher than for the first labeled recognition molecule.

The inventors have recognized and appreciated that distinguishing biological or chemical samples based on fluorophore decay rates and/or fluorophore intensities may enable a simplification of the optical excitation and detection systems. For example, optical excitation may be performed with a single-wavelength source (e.g., a source producing one characteristic wavelength rather than multiple sources or a source operating at multiple different characteristic wavelengths). Additionally, wavelength discriminating optics and filters may not be needed in the detection system. Also, a single photodetector may be used for each reaction chamber to detect emission from different fluorophores. The phrase “characteristic wavelength” or “wavelength” is used to refer to a central or predominant wavelength within a limited bandwidth of radiation (e.g., a central or peak wavelength within a 20 nm bandwidth output by a pulsed optical source). In some cases, “characteristic wavelength” or “wavelength” may be used to refer to a peak wavelength within a total bandwidth of radiation output by a source.

According to an aspect of the present disclosure, an exemplary integrated device may be configured to perform single-molecule analysis in combination with an instrument as described above. It should be appreciated that the exemplary integrated device described herein is intended to be illustrative and that other integrated device configurations may be configured to perform any or all techniques described herein.

FIG. 13 illustrates a cross-sectional view of a pixel 1-112 of an integrated device 1-102. Pixel 1-112 includes a photodetection region, which may be a pinned photodiode (PPD), and a charge storage region, which may be a storage diode (SD0). In some embodiments, a photodetection region and charge storage regions may be formed in semiconductor material of a pixel by doping regions of the semiconductor material. For example, the photodetection region and charge storage regions can be formed using a same conductivity type (e.g., n-type doping or p-type doping).

During operation of pixel 1-112, excitation light may illuminate reaction chamber 1-108 causing incident photons, including fluorescence emissions from a sample, to flow along the optical axis to photodetection region PPD. As shown in FIG. 13, pixel 1-112 may include a waveguide 1-220 configured to optically (e.g., evanescently) couple excitation light from a grating coupler of the integrated device (not shown) to the reaction chamber 1-108. In response, a sample in the reaction chamber 1-108 may emit fluorescent light toward photodetection region PPD. In some embodiments, pixel 1-112 may also include one or more photonic structures 1-230, which may include one or more optical rejection structures such as a spectral filter, a polarization filter, and/or a spatial filter. For example, the photonic structures 1-230 may be configured to reduce the amount of excitation light that reaches the photodetection region PPD and/or increase the amount of fluorescent emissions that reach the photodetection region PPD. Also shown in pixel 1-112, pixel 1-112 may include one or more metal layers 1-240, which may be configured as a filter and/or may carry control signals from a control circuit configured to control transfer gates, as described further herein.

In some embodiments, pixel 1-112 may include one or more transfer gates configured to control operation of pixel 1-112 by applying an electrical bias to one or more semiconductor regions of pixel 1-112 in response to one or more control signals. For example, when transfer gate ST0 induces a first electrical bias at the semiconductor region between photodetection region PPD and storage region SD0, a transfer path (e.g., charge transfer channel) may be formed in the semiconductor region. Charge carriers (e.g., photo-electrons) generated in photodetection region PPD by the incident photons may flow along the transfer path to storage region SD0. In some embodiments, the first electrical bias may be applied during a collection period during which charge carriers from the sample are selectively directed to storage region SD0. Alternatively, when transfer gate ST0 provides a second electrical bias at the semiconductor region between photodetection region PPD and storage region SD0, charge carriers from photodetection region PPD may be blocked from reaching storage region SD0 along the transfer path. In some embodiments, drain gate REJ may provide a channel to drain D to draw noise charge carriers generated in photodetection region PPD by the excitation light away from photodetection region PPD and storage region SD0, such as during a rejection period before fluorescent emission photons from the sample reach photodetection region PPD. In some embodiments, during a readout period, transfer gate ST0 may provide the second electrical bias and transfer gate TX0 may provide an electrical bias to cause charge carriers stored in storage region SD0 to flow to the readout region, which may be a floating diffusion (FD) region, for processing.

It should be appreciated that, in accordance with various embodiments, transfer gates described herein may include semiconductor material(s) and/or metal, and may include a gate of a field effect transistor (FET), a base of a bipolar junction transistor (BJT), and/or the like.

In some embodiments, operation of pixel 1-112 may include one or more collection sequences, each collection sequence including one or more rejection (e.g., drain) periods and one or more collection periods. In one example, a collection sequence performed in accordance with one or more pulses of an excitation light source may begin with a rejection period, such as to discard charge carriers generated in pixel 1-112 (e.g., in photodetection region PD) responsive to excitation photons from the light source. For instance, the excitation photons may arrive at pixel 1-112 prior to the arrival of fluorescence emission photons from the reaction chamber. Transfer gates for the charge storage regions may be biased to have low conductivity in the charge transfer channels coupling the charge storage regions to the photodetection region, blocking transfer and accumulation of charge carriers in the charge storage regions. A drain gate for the drain region may be biased to have high conductivity in a drain channel between the photodetection region and the drain region, facilitating draining of charge carriers from the photodetection region to the drain region. Transfer gates for any charge storage regions coupled to the photodetection region may be biased to have low conductivity between the photodetection region and the charge storage regions, such that charge carriers are not transferred to or accumulated in the charge storage regions during the rejection period.

Following the rejection period, a collection period may occur in which charge carriers generated responsive to the incident photons are transferred to one or more charge storage regions. During the collection period, the incident photons may include fluorescent emission photons, resulting in accumulation of fluorescent emission charge carriers in the charge storage region(s). For instance, a transfer gate for one of the charge storage regions may be biased to have high conductivity between the photodetection region and the charge storage region, facilitating accumulation of charge carriers in the charge storage region. Any drain gates coupled to the photodetection region may be biased to have low conductivity between the photodetection region and the drain region such that charge carriers are not discarded during the collection period.

Some embodiments may include multiple rejection and/or collection periods in a collection sequence, such as a second rejection period and second collection period following a first rejection period and a collection period, where each pair of rejection and collection periods is conducted in response to a pulse of excitation light. In one example, charge carriers generated in the photodetection region during each collection period of a collection sequence (e.g., in response to a plurality of pulses of excitation light) may be aggregated in a single charge storage region. In some embodiments, charge carriers aggregated in the charge storage region may be read out for processing prior to the next collection sequence. Alternatively or additionally, in some embodiments, charge carriers aggregated in a first charge storage region during a first collection sequence may be transferred to a second charge storage region sequentially coupled to the first charge storage region and read out simultaneously with the next collection sequence. In some embodiments, a processing circuit configured to read out charge carriers from one or more pixels may be configured to determine one or more of luminescence intensity information, luminescence lifetime information, luminescence spectral information, and/or any other mode of luminescence information associated with performing techniques described herein.

In some embodiments, a first collection sequence may include transferring, to a charge storage region at a first time following each excitation pulse, charge carriers generated in the photodetection response in response to the excitation pulse, and a second collection sequence may include transferring, to the charge storage region at a second time following each excitation pulse, charge carriers generated in the photodetection response in response to the excitation pulse. For example, the number of charge carriers aggregated after the first and second times may indicate luminance lifetime information of the received light.

As described further herein, pixels of an integrated device may be controlled to perform one or more collection sequences using one or more control signals from a control circuit of the integrated circuit, such as by providing the control signal(s) to drain and/or transfer gates of the pixel(s) of the integrated circuit. In some embodiments, charge carriers may be read out from the FD region of each pixel during a readout pixel associated with each pixel and/or a row or column of pixels for processing. In some embodiments, FD regions of the pixels may be read out using correlated double sampling (CDS) techniques.

Sequence Information

TABLE 1

Non-limiting example sequences of amino acid binding proteins.

SEQ ID

Name
NO.
Sequence

PS557
1
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS621
2
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

Ntaq1sf
3
MNGLSAQHERIAPARHECVYTSCYCEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVP

IWKQKSGRGEEPVIWDYHVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYIN

PAFWRKLRVVPADVFLQNFASDRSHMKDASGGWRMPPPPYPCIETAESRMNLDDFISMNP

SVGWGHVYTLEEFVQHFGKT

PS579
4
MSDSPVDLKPKPKVKPKLERPKLYKVMLLNDDYTTAFFVTKVLKAVFRMSEDTGRRVMMT

AHRFGSAVVVVCERDIAETKAKEATDLGKEAGFPLMFTTEPEE

PS580
5
MSDSPVDLKPKPKVKPKLERPKLYKVMLLNDDYTTMRFVTLVLKAVFRMSEDTGRRVMMT

AHRFGSAVVVVCERDIAETKAKEATDLGKEAGFPLMFTTEPEE

PS581
6
MLSATRRALQLFHSLFPIPRMGDSAAKIVSPQEALPGRKEPLVVAAKHHVNGNRTVEPFP

EGTQMAVFGMGCFWGAERKFWTLKGVYSTQVGFAGGYTPNPTYKEVCSGKTGHAEVVRVV

FQPEHISFEELLKVFWENHDPTQGMRQGNDHGSQYRSAIYPTSAEHVGAALKSKEDYQKV

LSEHGFGLITTDIREGQTFYYAEDYHQQYLSKDPDGYCGLGGTGVSCPLGIKK

PS582
7
MLSATRRALQLFHSLFPIPRMGDSAAKIVSPQEALPGRKEPLVVAAKHHVNGNRTVEPFP

EGTQMAVFGMGSFWGAERKFWTLKGVYSTQVGFAGGYTPNPTYKEVCSGKTGHAEVVRVV

FQPEHISFEELLKVFWENHDPTQGMRQGNDHGSQYRSAIYPTSAEHVGAALKSKEDYQKV

LSEHGFGLITTDIREGQTFYYAEDYHQQYLSKDPDGYCGLGGTGVSCPLGIKK

PS585
8
MAFPARGKTAPKNEVRRQPPYNVILLNDDDTTYRYVIEMLQKIFGFPPEKGFQIAEEVDR

TGRVILLTTSKEHAELKQDQVHSYGPDPYLGRPCSGSMTCVIEPAV

PS586
9
MAFPARGKTAPKNEVRRQPPYNVILLDDDDHTYRYVIEMLQKIFGFPPEKGFQIAEEVDR

TGRVILLTTSKEHAELKQDQVHSYGPDPYLGRPCSGSMTCVIEPAV

PS587
10
MAFPARGKTAPKNEVRRQPPYNVILLKDDDHTYRYVIEMLQKIFGFPPEKGFQIAEEVDR

TGRVILLTTSKEHAELKQDQVHSYGPDPYLGRPCSGSMTCVIEPAV

PS588
11
MAFPARGKTAPKNEVRRQPPYNVILLNKDDHTYRYVIEMLQKIFGFPPEKGFQIAEEVDR

TGRVILLTTSKEHAELKQDQVHSYGPDPYLGRPCSGSMTCVIEPAV

PS589
12
MAFPARGKTAPKNEVRRQPPYNVILLNDDDHTYRYVIEMLQKIFGFPPEKGFQIAEEVHR

TGRVILLTTSKEHAELKQDQVHSYGPDPYLGRPCSGSMTCVIEPAV

PS590
13
MAFPARGKTAPKNEVRRQPPYNVILLNDDNHTYRYVIEMLQKIFGFPPEKGFQIAEEVDR

TGRVILLTTSKEHAELKQDQVHSYGPDPYLGRPCSGSMTCVIEPAV

PS591
14
MGSVHKHTGRNCGRKFKIGEPLYRCHECGCDDTCVLCIHCFNPKDHVKHHVCTDICTEFT

SGICDCGDEEAWNSPLHCKAEEQ

PS594
15
MTSLNIMGRKFILERAKRNDNIEEIYTSAYVSLPSSTDTRLPHFKAKEEDCDVYEEGTNL

VGKNAKYTYRSLGRHLDFLRPGLRFGGSQSSKYTYYTVEVKIDTVNLPLYKDSRSLDPHV

TGTFTIKNLTPVLDKVVTLFEGYVINYNQFPLCSLHWPAEETLDPYMAQRESDCSHWKRF

GHFGSDNWSLTERNFGQYNHESAEFMNQRYIYLKWKERFLLDDEEQENQMLDDNHHLEGA

SFEGFYYVCLDQLTGSVEGYYYHPACELFQKLELVPTNCDALNTYSSGFEIA

PS595
16
MGSSHHHHHHHHHHSSGLVPRGSHMQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGI

PPDQQRLIFAGKQLEDGRTLSDYNIQKESTLHLVLRLRGGMASVVEYKGLKAGYYCGYCE

SREGKTSCGMWAHSMTVQDYQDLIDRGWRRSGKYVYKPVMDQTCCPQYTIRCHPLQFQPS

KSHKKVLKKMLKFLAKGEISKGNCEDEPMDSTVEDAVDGDFALINKLDIKCDLKTLSDLK

GSIESEEKEKEKSIKKEGSKEFIHPQSIEEKLGSGEPSHPIKVHIGPKPGKGADLSKPPC

RKAREMRKERQRLKRMQQASAAASEAQGQPVCLLPKAKSNQPKSLEDLIFQSLPENASHK

LEVRLVPASFEDPEFNSSFNQSFSLYTKYQVAIHQEAPEICEKSEFTRFLCSSPLEAEHP

ADGPECGYGSFHQQYWLDGKIIAVGVLDILPYCVSSVYLYYDPDYSFLSLGVYSALREIA

FTRQLHEKTSQLSYYYMGFYIHSCPKMRYKGQYRPSDLLCPETYVWVPIEQCLPSLDNSK

YCRFNQDPEAEDEGRSKELDRLRVFHRRSAMPYGVYKNHQEDPSEEAGVLEYANLVGQKC

SERMLLFRH

PS630
17
MSEPMTLPAIPQPRLKERTQRQPPYNVILLNDDDKSYEYVAAMLQVLFGYPPEKGYQMAK

EVDSTGRVILLTTTREHAELKQEQIHAFGPDPNQARNSGSMKAVIEPAV

PS631
18
MSEPMTLPAIPQPRLKERTQRQPPYNVILLNDDDKSYEYVIAMLQVLFGYPPEKGYQMAK

EVDSTGRVILLTTTREHAELKQEQIHAFGPDPNQARNSGSMKAVIEPAV

PS632
19
MSEPMTLPAIPQPRLKERTQRQPPYNVIILNDDDKSFEYVAAMLQVLFGYPPEKGYQMAK

EIDSTGRVIMLTTTREHAELKQEQIHAFGPDPNQARNSGSMKAVIEPAV

PS633
20
MSEPMTLPAIPQPRLKERTQRQPPYNVIILNDDDKSFEYVAALLQVLFGYPPEKGYQMAK

EIDSTGRVIMLTTTREHAELKQEQIHAFGPDPNQARNSGSMKAVIEPAV

PS634
21
MSEPMTLPAIPQPRLKERTQRQPPYNVIVLNDDDKSFEYVAAMLQVLFGYPPEKGYQVAK

EIDSTGRVITLTTTREHAELKQEQIHAFGPDPNQARNSGSMKAVIEPAV

PS635
22
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVQWNDDRHTYQYTVVMFQSLFGH

PPERGYRLAKESDTQGRIIVLTTTREHAELKRDQIHAFGYDRLLARDKGSYKASIEAEE

PS636
23
HHHHHHHHHHDYDIPTTENLYFQGMPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYH

VLWNDDDHTYQYVVVMLQSLFGHPPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIH

AFGYDRLLARSKGSMKASIEAEE

PS642
24
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVQWNDDRHTYQYTVVMFQSLFGH

PPERGYRLAKESDTQGRIIVLTTTREHAELKRDQIHAFGYDPLQSGDKGSYKASIEAEE

PS643
25
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVAWNDDRHTYQYTVVMFQSLFGH

PPERGYRLAKEQDTQGRIIVLTTTREHAELKRDQIHAFGYDPLQSGDKGSYKASIEAEE

PS644
26
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVAWNDDRHTYQYTVVMFQSLFGH

PPERGYRLAKEQDTQGRIIVLTTTREHAELKRDQIHAFGYDPLQSGDKGSYKASIEAEE

PS645
27
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVSWNDDKHTYQWTVVMFQSLFGH

PPERGYRLAKERDTQGRIIVLTTTREHAELKRDQIHAFGYDPLQSGDKGSMKASIEAEE

PS646
28
MKMYNIPTPTMAQVIMVDDPITTTEFVISALRDFFDKSLEEAKALTSSIHRDGEGVCGVY

PYDIARHRAAWVRDKAKALEFPLKLLVEEIK

PS647
29
MKMYNIPTPTMAQVIMVDDPINTYEFTISALRDFFDKSLEEAKALASSIDRDGEGVCGVY

PYDIARHRAAWVRDKAKALEFPEKLLVEEIK

PS648
30
MKMYNIPTPTMAQVIMVDDPINTKEFTISALRDFFDKSLEEAKALASSIDRDGEGVCGVY

PYDIARHRAAWVRDKAKALEFPEKLLVEEIK

PS649
31
MKMYNIPTPTMAQVIRVDDPSMTNEFGISALRDFFDKSLEEAKALASSIDRDGEGVCGVY

PYDIARHRAAWVRDKAKALEFPSKLLVEEIK

PS650
32
MKMYNIPTPTMAQVIRVDDPSMTYEFGISALRDFFDKSLEEAKALASSIDRDGEGVCGVY

PYDIARHRAAWVRDKAKALEFPSKLLVEEIK

PS657
33
MPQERQQVTRKHYPNYKVIFLNSDFYTFQHLVALMMKYIPNMTSDRAWEISNQIHYEGQA

IVWVGPQEQAELYHEQFLRAGLTMAPLEPE

PS658
34
MTSTLRARPARDTDLQHRPYPHYRIITLDDDVMTFQHMANSYVTFLPGMTRDQMWAMSQQ

DDGEGSMVVWTGPQEQAELYHVQLGNHGQTNIPLEPV

PS659
35
MTSTLRARPARDTDLQHRPYPHYRIIVLDDDVMTFQHMANSFVTFLPGMTRDQMWAMSQQ

DEGEGSMVVWTGPQEQAELYHVQLGNHGQTNIPLEPV

PS660
36
MTSTLRARPARDTDLQHRPYPHYRIIVLDDDVMTFQHLANSFVTFLPGMTRDQMWAMSQQ

DDGEGSMVVWTGPQEQAELYHVQLGNHGQTNIPLEPV

PS661
37
MTSTLRARPARDTDLQHRPYPHYRIIVLDDDVMTFQHMANSFVTFLPGMTRDQMWAMSQQ

DDGEGSMVVWTGPQEQAELYHVQLGNHGQTNIPLEPV

PS662
38
MTSTLRARPARDTDLQHRPYPHYRIILLDSDVITFQLTANAFVTFLPGMTRDQMWAKIQQ

SDGEGSCWWTGPQEQAELYHVQLGNQGLTEIPLEPV

PS663
39
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLHKVIEVNQDYIP

WEFWVTFFKGEFHMSEDQAQRKMIAGDRRGVYVVAVFTRDVAETKATRFSDHGRAKGYPT

QMTTEPEE

PS664
40
MGQTVEKPRVEGPGTGLGGSWRVITRNNDHYTRDHWARTIARFIPGVSLERAHEWSKVIH

TTGRKWYTGHKEAAEHYWQQFKGSGLESMPLEQG

PS665
41
MTLSVALGPDTQESTQTGTAVSTDTLTAPDIPWNLVDWNDPVNLMSYISYVFQSYFGYSE

TKANKLMMEQDKKGRSIVAHGSKEQVEQHAVALHGYGNWATVEKATGGNSGGGKSGGPGK

GKGKRG

PS666
42
MSGTVVESKPRNSTQLAPRWKVIYHDNPVTTFDFTTGMFRRVFAKPPGEARRMTREAHDT

GSVLVDVLALEQAEFRRDQMHSLARAEGFPQTLTLEPAD

PS667
43
MSGTVVESKPRNSTQLAPRWKVIYHDQPVTTFDFTTGLFRRVFAKPPGEARRMTREAHDT

GSVLVDVLALEQAEFRRDQMHSLARAEGFPQTLTLEPAD

PS668
44
MSDSPVDLKPKPKVKPKLERPSMYKVITVNDDYTPMEFTIDHLQKFFSYDVERATQLMLA

SDYQGKAICGVFTAEVAETKVAMMNKSARENEHPELCTLEKAE

PS669
45
MSDSPVDLKPKPKVKPKLERPSMYKVITVNDDYTPMEFTIDHLQKFFSYDVERATQLMLA

SEYQGKAICGVFTAEVAETKVAMMNKSARENEHPELCTLEKAE

PS670
46
MHSKFNHAGRICGAKHRVGEPMYRCKECSFDDTCTLCVNCFNPKDHVGHHVYTSICTEFK

NGICDCGDKEAWNHELNCKGAED

PS671
47
MHSKFNHAGRICGAKFRVGEPLYRCKECSFDDTCVLCVNCFNPKDHVGHHVYTSICTEFL

NGICDCGDKEAWNHELNCKGAED

PS672
48
MHSKFNHAGRICGAKFRVGEPLYKCKECSFDDTCVLCVNCFNPKDHVGHHVYTMICTEFL

NGICDCGDKEAWNHELNCKGAED

PS673
49
MAFPARGKTAPKNEVRRQPPYNVIMLNDDDHTWRYAMELFQKIFGFPPEKGFQIVEEMDR

TGRVILLTTSKEHAELKQDQMHSYGPDPYLGRPCSGSMTCVIEPAV

PS674
50
MAFPARGKTAPKNEVRRQPPYNVIILNDDDHTWRYLMEMFQKIFGFPPEKGFQIIEEIDR

TGRAILLTTSKEHAELKQDQLHSYGPDPYLGRPCSGSMTVVIEPAV

PS675
51
MAFPARGKTAPKNEVRRQPPYNVILLNDDDHTWRYIMEMFQKIFGFPPEKGFQITEEIDR

TGRAILLTTSKEHAELKQDQTHSYGPDPYLGRPCSGSMTMVIEPAV

PS676
52
MAFPARGKTAPKNEVRRQPPYNVIILNDDDMTWRYLMEAFQKIFGFPPEKGFQIIEEIDR

TGRAILLTTSKEHAELKQDQMHSYGPDPYLGRPCSGSMTMVIEPAV

PS677
53
MSGTVVESKPRNSTQLAPRWKVIMHDQPVITFDFTLGMFRRVFAKPPGEARRITREAHDT

GSVLVDVLALEQAEFRRDQMHSLARAEGFPLTMTLEPAD

PS678
54
MAFPARGKTAPKNEVRRQPPYNVIILNDDDHTYRYFIEMFQKIFGFPPEKGFQYTEEMDR

TGRLILLTTSKEHAELKQDQLHSYGPDPYLGRPCSGSVTWIEPAV

PS679
55
MAFPARGKTAPKNEVRRQPPYNVIILNDDDHTYRYFLEMFQKIFGFPPEKGFQYAEEIDR

TGRLILLTTSKEHAELKQDQMHSYGPDPYLGRPCSGSITCVIEPAV

PS680
56
MAFPARGKTAPKNEVRRQPPYNVIILNDDDHTYRYFIEMFQKIFGFPPEKGFQIVEEIDR

TGRYILLTTSKEHAELKQDQLHSYGPDPYLGRPCSGSITCVIEPAV

PS681
57
MAFPARGKTAPKNEVRRQPPYNVIMLNDDDHTYRYFIELFQKIFGFPPEKGFQIIEEIDR

TGRAILLTTSKEHAELKQDQIHSYGPDPYLGRPCSGSITCVIEPAV

PS682
58
MAFPARGKTAPKNEVRRQPPYNVIILNDDDHTYRYFLEMFQKIFGFPPEKGFQYVEEIDR

TGRIILLTTSKEHAELKQDQMHSYGPDPYLGRPCSGSITCVIEPAV

PS683
59
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVIWNDDDHTYQYFVVMFQSLFGH

PPERGYRIVKEIDTQGRYIVLTTTREHAELKRDQLHAFGYDRLLARSKGSIKASIEAEE

PS684
60
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVYWNDDDHTYQYFVVLFQSLFGH

PPERGYRIVKEIDTQGRYIVLTTTREHAELKRDQTHAFGYDRLLARSKGSIKISIEAEE

PS685
61
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVMWNDDDHTYQYFVVLLQSLFGH

PPERGYRIVKEIDTQGRYIVLTTTREHAELKRDQIHAFGYDRLLARSKGSIKVSIEAEE

PS686
62
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVFWNDDDHTYQYFVVLFQSLFGH

PPERGYRIAKEIDTQGRYIVLTTTREHAELKRDQVHAFGYDRLLARSKGSIKISIEAEE

PS687
63
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVIWNDDDHTYQYFVVTFQSLFGH

PPERGYRIAKEIDTQGRYIVLTTTREHAELKRDQWHAFGYDRLLARSKGSIKCSIEAEE

PS688
64
MHSKFSHAGRICGAKFKVGEPAYRCKECSFDDTCILCVNCFNPKDHTGHHVYTMICTEFL

NGICDCGDKEAWNHTLFCKAEEG

PS689
65
MHSKFSHAGRICGAKFKVGEPAYLCKECSFDDTCILCVNCFNPKDHTGHHVYTMICTEFL

NGICDCGDKEAWNHTLFCKAEEG

PS710
66
MSDSPVDLKPKPKVKPKLERPKLYKVMFLNDDYTPMSYIIVFFKAVFRMSEDTGRRKMMT

AHRFGSMVVVVCERDIAETKAKEFTDHGKEAGFPIMMTTEPEE

PS711
67
MSDSPVDLKPKPKVKPKLERPKLYKVMFLDDDYTPMSYIIVFFKAVFRMSEDTGRRKMMT

AHRFGSMVVVVCERDIAETKAKEFTDHGKEAGFPIQMTTEPEE

PS712
68
MIAEPICMQGEGDGEDGGTNRGTSVITRVKPKTKRPNLYRVLTLDDDYTPMEFMIHMFER

FFQKDREAATRLMLLVHQHGVAECGVFTYEVAETKVSQMMDWARQHQHPFQMVMEKK

PS713
69
MPQERQQVTRKHYPNYKVILLDMDFMTFAFMSAVLMKYIPNMTSDRSTELIRQAHYEGQT

IVWVGPQEQAELYHEQFLRSGLQNMPLEPE

PS714
70
MASAPSTTLDKSTQVVKKTYPNYKVIFLDSDLLTMDFLANVMIKYIPDMTTDRAWEKAYQ

MHYQGQFIVWTGPQEQAELYHQQFRREGLENIPLEAA

PS715
71
MTSTLRARPARDTDLQHRPYPHYRIITLDNDVNTFQKIANVHVTFLPGMTRDQMWAKMQQ

VDGEGSVVVWTGPQEQAELYHVQFGNQGLKNIPLEPV

PS716
72
MATETIERPRTRDPGSGLGGHWLVIMLDNDHMTFDLISKVLARVIPGVTVDDAYRFTYQM

HQRGQVIIWRGPKEPAEHYWEQLQDVGLDNAPLERH

PS717
73
MAFPARGKTAPKNEVRRQPPYNVIILNSDDHTYRYFMEMFQKIFGFPPEKGFQYMEEIDR

TGRIILLTTSKEHAELKQDQSHSYGPDPYLGRPCSGSITMVIEPAV

PS718
74
MGQTVEKPRVEGPGTGLGGSWRVISRDNDHYTFDEWVRIIARFIPGVSLERAHEWMKVLH

TTGRMVVYTGHKEAAEHYWQQLKGAGFQSVPLEQG

PS719
75
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLYKVIFVDDDFVP

FEF11RMFKAEFRMSEDQAAEKMMRAHQRGVQWAVFTRDVAETKATRFTDWGRAKGYPL

IMTTEPEE

PS720
76
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLHKVIFVDQDYIP

FEFIITMFKGEFHMSEDQAQRKLITAHRRGVYVVAVFTRDVAETKATRFSDAGRAKGYPL

QVTTEPEE

PS721
77
MTLSVALGPDTQESTQTGTAVSTDTLTAPDIPWNLVFWDDPVTLMSRIIYFFQSYFGYSE

TKAYKIVMEAHKKGRSIVAHGSKEQVEQHAVAFHGLGLWTTVEKATGGNSGGGKSGGPGK

GKGKRG

PS722
78
MSDTITLPGRPEVERDERTRRQPPYNVITHDKDDITFAYFIVMYNQLFGYPPEKGYEKLK

EIHLNGRAIVLTTSKEHAELKRDQMHAWGPDPFSSKDCKGSISASIEPAY

PS723
79
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVIWNDDDWTYQYYVVMFQSLFGH

PPERGYRLMKELDTQGRFIVLTTTREHAELKRDQIHAFGYDRLLARSKGSIKASIEAEE

PS724
80
MSSPSSLDDVQVSTSRAKPANETRTRKQPPYAVIFEDQDHVTHLWFYEMFMKVCGHAPEK

GFVKSQQIHTQGKVMVWSGTLELAELKRDQFRGFGPDNYAPAPVTFPPGMTIEPLP

PS725
81
MSGTVVESKPRNSTQLAPRWKVIFHDNPVTTFAFIIGMFRRVFAKPPGEAREMLRRAHDT

GSVLVDVLALEQAEFRRDQFHSEARAEGFPSTMTLEPAD

PS726
82
MHHHHHHHHHHDYDIPTTENLYFQGMHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCV

LCVNCFNPKDHTGHHVYTTICTEFNNGICDCGDKEAWNHTLFCKAEE

PS727
83
MSDSPVDLKPKPKVKPKLERPKLYKVMFLNQDYVPMSFIVVMFKAVFRMSEDTGRKKMMH

AHRFGSVVVVVCERDIAETKAKEFTDYGKEAGFPVMMTTEPEE

PS728
84
MTLSVALGPDTQESTQTGTAVSTDTLTAPDIPWNLVMWNQPVLLWSYMVYLFQSYFGYSE

TKTNKMVMEAHKKGRSIVAHGSKEQVEQHAVAMHGRGLWATVEKATGGNSGGGKSGGPGK

GKGKRG

PS729
85
MSDTITLPGRPEVERDERTRRQPPYNVITHNQDDITWEYFRVMYNQLFGYPPEKGYEKLK

EIHLNGRIIVLTTSKEHAELKRDQMHAWGPDPFSSKDCKGSVSNSIEPAY

PS730
86
MSDTITLPGRPEVERDERTRRQPPYNVIIHNTDDLTWEYFKVMFNQLFGYPPEKGYEKLK

EIHLNGRAIVLTTSKEHAELKRDQMHAWGPDPFSSKDCKGSVSASIEPAY

PS731
87
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVTWNTDDWTHQYYVVMYQSLFGH

PPERGYRLTKEMDTQGRCIVLTTTREHAELKRDQMHAFGYDRLLARSKGSTKVSIEAEE

PS732
88
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVMWNTDDWTYQYIIVMMQSLFGH

PPERGYRMVKEMDTQGRTIVLTTTREHAELKRDQMHAFGYDRLLARSKGSIKNSIEAEE

PS733
89
MSSPSSLDDVQVSTSRAKPANETRTRKQPPYAVIFENQDHVTILWFWEMFMKVCGHAPEK

GFVKSQQIHTQGKVMVWSGTLELAELKRDQFRGFGPDNYAPRPVTFPPGMTIEPLP

PS734
90
MSSPSSLDDVQVSTSRAKPANETRTRKQPPYAVIMENLDHITLLWMWEMFMKVCGHAPEK

GFVKSQQNHTQGKVMVWSGTLELAELKRDQMRGWGPDNYAPRPVTFPPGFTIEPLP

PS735
91
MSGTVVESKPRNSTQLAPRWKVIYHDQPVTTFDFIIGMFRRVFAKPPGEAREMTRRAHDT

GSVLVDVLALEQAEFRRDQFHSEARAEGFPSTMTLEPAD

PS736
92
MSGTVVESKPRNSTQLAPRWKVIYHDQPVMTFDFIIGLFRRVFAKPPGEARTITRIAHDT

GSVLVDVLALEQAEFRRDQFHSEARAEGFPATMTLEPAD

PS737
93
MSDSPVDLKPKPKVKPKLERPKLYKVMFLNQDYTPMSFIVVMFKAVFRMSEDTGRKKMMH

AHRFGSVVVVVCERDIAETKAKEFTDYGKEAGFPSMMTTEPEE

PS738
94
MIAEPICMQGEGDGEDGGTNRGTSVITRVKPKTKRPNLYRVLWLNHDYIPMEFMVHMFER

FFQKDREAATRYMLLVHQHGVAECGVFTYEVAETKVSQLMDWARQHQHPFQVVMEKK

PS739
95
MIAEPICMQGEGDGEDGGTNRGTSVITRVKPKTKRPNLYRVLWLNHDYIPMEFMVHMFER

FFQKDREAATRIMLEVHQHGVSECGVFTYEVAETKVSQLMDFARQHQHPFQVVMEKK

PS740
96
MPQERQQVTRKHYPNYKVIMLNNDFHTFQFMSAVMMKYIPNMTSDRSWEKVNQVHYEGQT

IVWVGPQEQAELYHEQFLRSGLTNMPLEPE

PS741
97
MPQERQQVTRKHYPNYKVIMLNDDFWTFQFLAAVIMKYIPNMTSDRVWEITNQVHYEGQS

IVWVGPQEQAELYHEQFLREGFLHVPLEPE

PS742
98
MASAPSTTLDKSTQVVKKTYPNYKVILLNNDLITRDKLANVLIKYIPDMTTDRAWERINQ

MHYQGQFIVWTGPQEQAELYHQQFRREGMQNIPLEAA

PS743
99
MASAPSTTLDKSTQVVKKTYPNYKVIMLNNDLLTRDEIANVFIKYIPDMTTDRMWEMTNQ

MHYQGQLIVWTGPQEQAELYHQQFRREGLLNVPLEAA

PS744
100
MTSTLRARPARDTDLQHRPYPHYRIITLDNDVITFQELVNYYVTFLPGMTRDQIWAKMQQ

VDGEGSAVVWTGPQEQAELYHVQLGNQGLFNCPLEPV

PS745
101
MTSTLRARPARDTDLQHRPYPHYRIITLDMDVNTFQEIANYYVTFLPGMTRDQMWAWMQQ

VDGEGSVVVWTGPQEQAELYHVQLGNQGLYNIPLEPV

PS746
102
MATETIERPRTRDPGSGLGGHWLVIHLNSDHFTFDEHAKWLARVIPGVTVDDAYRFTDQM

HQRGQMIVWRGPKEPAEHYWEQLQDVGLSQSPLERH

PS747
103
MATETIERPRTRDPGSGLGGHWLVIMLNSDHFTFDEFSKWLARVIPGVTVDDAYRFTDQM

HQRGQVIVWRGPKEPAEHYWEQFQDIGLSQVPLERH

PS748
104
MAFPARGKTAPKNEVRRQPPYNVIILNSDDHTYRYYMEMFQKIFGFPPEKGFQYMEEIDR

TGRIILLTTSKEHAELKQDQLHSYGPDPYLGRPCSGSITCVIEPAV

PS749
105
MAFPARGKTAPKNEVRRQPPYNVIILNSDDHTYRYFMEMFQKIFGFPPEKGFQYMEEIDR

TGRIILLTTSKEHAELKQDQLHSYGPDPYLGRPCSGSITCVIEPAV

PS750
106
MGQTVEKPRVEGPGTGLGGSWRVIMRNTDHITKDEFARSIARFIPGVSLERAHEKIKVMH

TTGRFVVYTGHKEAAEHYWQQFKGSGVQVMPLEQG

PS751
107
MGQTVEKPRVEGPGTGLGGSWRVIMRNDDHHTKDKFARMIARFIPGVSLERAHEKIKVLH

TTGRMVVYTGHKEAAEHYWQQMKGAGVQNVPLEQG

PS752
108
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLYKVIFVNRDFIP

MEFIIRMFKAEFRMSEDQAARKMMYAHQRGVYWAVFTRDVAETKATRFTDWGRAKGYPL

LMTTEPEE

PS753
109
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLYKVIFVNRDFIP

MEFIIRMFKAEFRMSEDQAATKMMLAHQRGVQVVAVFTRDVAETKATRFTDWGRAKGYPL

LMTTEPEE

PS754
110
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLHKVIFVNQDYIP

WEFIVTLFKGEFHMSEDQAQRKMIIAHRRGVYVVAVFTRDVAETKATRTSDWGRAKGYPL

QFTTEPEE

PS755
111
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLHKVIFVNKDYIP

WEFIVTMFKGEFHMSEDQAQRKMIIAHRRGVYVVAVFTRDVAETKATRFSDWGRAKGYPL

QMTTEPEE

PS756
112
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPPLHKVILVNRDFIP

MEFIIRMLKAEFRTTGDEAQRKMIYAHMKGSYVVAVFTREIAESKATRFTEWARAEGFPM

LMTTEPEE

PS757
113
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPPLHKVILVNQDFIP

WEFMIRFLKAEFRTTGDEAQKKMISAHMKGSHVVAVFTREIAESKATRMTEWARAEGFPL

LFTTEPEE

PS758
114
MTLSVALGPDTQESTQTGTAVSTDTLTAPDIPWNLVIWNLPVLLWSFIVYLFQSYFGYSE

TKANKIVMEMHKKGRSIVAHGSKEQVEQHAVAFHGRGLWTTVEKATGGNSGGGKSGGPGK

GKGKRG

PS759
115
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTHQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS760
116
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVMMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS761
117
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTHQYVVMMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS762
118
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS763
119
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDYDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS764
120
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDYDDHTYQYVVVMLQSLFGH

PPERGYRLAKELDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS765
121
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDEDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS766
122
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNYDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS767
123
MTLSVALGPDTQESTQTGTAVSTDTLTAPDIPWNLVIWDDPVNLMSYVSYVFQSYFGYSE

TKANKLMMEVHKKGRSIVAHGSKEQVEQHAVAMHGYGLWATVEKATGGNSGGGKSGGPGK

GKGKRG

PS768
124
MSDTITLPGRPEVERDERTRRQPPYNVILHDDDDHTFEYVIVMLNQLFGYPPEKGYEMAK

EVHLNGRVIVLTTSKEHAELKRDQIHAFGPDPFSSKDCKGSMSASIEPAY

PS769
125
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS770
126
MSSPSSLDDVQVSTSRAKPANETRTRKQPPYAVIVEDDDHHTFLYVIEALMKVCGHAPEK

GFVLAQQIHTQGKAMVWSGTLELAELKRDQLRGFGPDNYAPRPVTFPLGVTIEPLP

PS771
127
MSGTVVESKPRNSTQLAPRWKVIVHDDPVTTFDFVLGVLRRVFAKPPGEARRITREAHDT

GSALVDVLALEQAEFRRDQAHSLARAEGFPLTLTLEPAD

PS772
128
MSDSPVDLKPKPKVKPKLERPKLYKVMLLDDDYTPMSFVTVVLKAVFRMSEDTGRRVMMT

AHRFGSAVVVVCERDIAETKAKEATDLGKEAGFPLMFTTEPEE

PS773
129
MIAEPICMQGEGDGEDGGTNRGTSVITRVKPKTKRPNLYRVLLLDDDYTPMEFVIHILER

FFQKDREAATRIMLHVHQHGVGECGVFTYEVAETKVSQVMDFARQHQHPLQCVMEKK

PS774
130
MPQERQQVTRKHYPNYKVIVLDDDFNTFQHVAACLMKYIPNMTSDRAWELTNQVHYEGQA

IVWVGPQEQAELYHEQLLRAGLTMAPLEPE

PS775
131
MASAPSTTLDKSTQVVKKTYPNYKVIVLDDDLNTFDHVANCLIKYIPDMTTDRAWELTNQ

VHYQGQAIVWTGPQEQAELYHQQLRREGLTMAPLEAA

PS776
132
MATETIERPRTRDPGSGLGGHWLVIVLDDDHNTFDHVAKTLARVIPGVTVDDGYRFADQI

HQRGQAIVWRGPKEPAEHYWEQLQDAGLSMAPLERH

PS777
133
MAFPARGKTAPKNEVRRQPPYNVILLDDDDHTYRYVIEMLQKIFGFPPEKGFQIAEEVDR

TGRVILLTTSKEHAELKQDQVHSYGPDPYLGRPCSGSMTCVIEPAV

PS778
134
MGQTVEKPRVEGPGTGLGGSWRVIVRDDDHNTFDHVARTLARFIPGVSLERGHEIAKVIH

TTGRAVVYTGHKEAAEHYWQQLKGAGLTMAPLEQG

PS779
135
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLYKVILVDDDFTP

REFWRVLKAEFRMSEDQAAKVMMTAHQRGVCWAVFTRDVAETKATRATDAGRAKGYPL

LFTTEPEE

PS780
136
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLHKVILVDDDYTP

REFWTVLKGEFHMSEDQAQRVMITAHRRGVCWAVFTRDVAETKATRASDAGRAKGYPL

QFTTEPEE

PS781
137
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPPLHKVILVDDDFTP

REFWRLLKAEFRTTGDEAQRIMITAHMKGSCWAVFTREIAESKATRATETARAEGFPL

LFTTEPEE

PS782
138
MTLSVALGPDTQESTQTGTAVSTDTLTAPDIPWNLVIWDDPVNLMSYVSYVFQSYFGYSE

TKANKLMMEVDKKGRSIVAHGSKEQVEQHAVAMHGYGLWATVEKATGGNSGGGKSGGPGK

GKGKRG

PS783
139
MSDTITLPGRPEVERDERTRRQPPYNVILHDDDDHTFEYVIVMLNQLFGYPPEKGYEMAK

EVDLNGRVIVLTTSKEHAELKRDQIHAFGPDPFSSKDCKGSMSASIEPAY

PS784
140
MSSPSSLDDVQVSTSRAKPANETRTRKQPPYAVIVEDDDHHTFLYVIEALMKVCGHAPEK

GFVLAQQIDTQGKAMVWSGTLELAELKRDQLRGFGPDNYAPRPVTFPLGVTIEPLP

PS785
141
MSGTVVESKPRNSTQLAPRWKVIVHDDPVTTFDFVLGVLRRVFAKPPGEARRITREADDT

GSALVDVLALEQAEFRRDQAHSLARAEGFPLTLTLEPAD

PS786
142
MSDSPVDLKPKPKVKPKLERPKLYKVMLLDDDYTPMSFVTVVLKAVFRMSEDTGRRVMMT

ADRFGSAVVVVCERDIAETKAKEATDLGKEAGFPLMFTTEPEE

PS787
143
MIAEPICMQGEGDGEDGGTNRGTSVITRVKPKTKRPNLYRVLLLDDDYTPMEFVIHILER

FFQKDREAATRIMLHVDQHGVGECGVFTYEVAETKVSQVMDFARQHQHPLQCVMEKK

PS788
144
MPQERQQVTRKHYPNYKVIVLDDDFNTFQHVAACLMKYIPNMTSDRAWELTNQVDYEGQA

IVWVGPQEQAELYHEQLLRAGLTMAPLEPE

PS789
145
MASAPSTTLDKSTQVVKKTYPNYKVIVLDDDLNTFDHVANCLIKYIPDMTTDRAWELTNQ

VDYQGQAIVWTGPQEQAELYHQQLRREGLTMAPLEAA

PS790
146
MATETIERPRTRDPGSGLGGHWLVIVLDDDHNTFDHVAKTLARVIPGVTVDDGYRFADQI

DQRGQAIVWRGPKEPAEHYWEQLQDAGLSMAPLERH

PS791
147
MGQTVEKPRVEGPGTGLGGSWRVIVRDDDHNTFDHVARTLARFIPGVSLERGHEIAKVID

TTGRAVVYTGHKEAAEHYWQQLKGAGLTMAPLEQG

PS792
148
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLYKVILVDDDFTP

REFWRVLKAEFRMSEDQAAKVMMTADQRGVCWAVFTRDVAETKATRATDAGRAKGYPL

LFTTEPEE

PS793
149
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPKLHKVILVDDDYTP

REFWTVLKGEFHMSEDQAQRVMITADRRGVCWAVFTRDVAETKATRASDAGRAKGYPL

QFTTEPEE

PS794
150
MVSIGAATVACAEGRPIFSGYFDWLAAMPETVTVPRTRLRPKTERPPLHKVILVDDDFTP

REFWRLLKAEFRTTGDEAQRIMITADMKGSCWAVFTREIAESKATRATETARAEGFPL

LFTTEPEE

PS795
151
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS796
152
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS797
153
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS798
154
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS799
155
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDYHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS800
156
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDNYHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS801
157
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS802
158
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

SPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS803
159
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PRERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS804
160
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDADHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS805
161
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGFRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS806
162
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS807
163
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAGSKGSMKASIEAEE

PS808
164
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS809
165
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS810
166
MPTAASATESAIEDTPAPARPEVDSRTKPKRQPRYHVVNWNDDDLTCQYLVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSIKASIEAEE

PS811
167
MPTAASATESAIEDTPAPARPEVDSRTKPKRQPRYHVVNWNDDDLTCQYMVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSTKASIEAEE

PS812
168
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVNWNDDDPTRQYMVVMLQSLFGH

PPERGYRLAKETDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSTKASIEAEE

PS813
169
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVNWNDDDPTRQYLVVMLQSLFGH

PPERGYRLAKETDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSTKASIEAEE

PS814
170
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS815
171
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS816
172
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS817
173
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS818
174
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS819
175
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS820
176
MPTAASGTESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS821
177
MPTAASGTESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS822
178
MPTAASGTESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS823
179
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS824
180
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS825
181
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS826
182
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS827
183
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PRERGYRLAKEVDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS828
184
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRERGYRLAKEVDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS829
185
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS830
186
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRKRGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS831
187
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PRKRGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS832
188
MPTAASATESAIEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS833
189
MPTAASATESAIEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS834
190
MPTAASATESAIEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS835
191
MPTAASATESAIEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS836
192
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PRERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS837
193
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS838
194
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS839
195
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS840
196
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PRKRGYRLAKEVMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS841
197
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

SPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS842
198
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

SPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS843
199
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

SPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS844
200
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

SPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS845
201
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS846
202
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS847
203
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS848
204
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS849
205
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS850
206
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS851
207
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS852
208
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS853
209
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS854
210
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS855
211
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS856
212
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS857
213
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS858
214
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPKRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS859
215
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPKRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS860
216
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLLGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS861
217
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLLGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS862
218
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLLGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS863
219
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLLGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS864
220
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPGRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS865
221
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPGRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS866
222
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPGRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS867
223
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPGRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS868
224
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPGRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS869
225
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPGRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS870
226
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPGRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS871
227
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPPEKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS872
228
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPEKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS873
229
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPPEKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS874
230
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPREKGFELATEV

DKLGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS875
231
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPREKGFELATEM

DKLGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS876
232
MPSAAPAKPVTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPEKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS877
233
MPSAAPAKPVTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPPEKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS878
234
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPREKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS879
235
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPREKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS880
236
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPREKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS881
237
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHSPEKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS882
238
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHSPEKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS883
239
MPSAAPAKPKTKRQSRTQHMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPPEKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS884
240
MPSAAPAKPKTKRQSRTQHMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPPEKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS885
241
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPEKGFEMATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS886
242
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPPEKGFEMATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS887
243
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVLGHPPEKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS888
244
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVLGHPPEKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS889
245
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPGKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS890
246
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPPGKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS891
247
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPGKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPHSKGSMSAVVERAG

PS892
248
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLRKVFGHPPGKGFELATEM

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPHSKGSMSAVVERAG

PS896
249
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS897
250
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVNWNDDDPTRQYTVVMLQSLFGH

PPERGYRLAKETRTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSTKASIEAEE

PS898
251
MPTAASATESAIEDTPAPARPEVDSRTKPKRQPRYHVVNWNDDDLTCQYTVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSHKASIEAEE

PS899
252
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVSWNDDDHTSQYTVVMLQSLFGH

PPERGYRLAKELHTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSPKASIEAEE

PS900
253
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPKRGYRMAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS901
254
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PRKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS902
255
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPGRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS903
256
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS904
257
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPRRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS905
258
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPDRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS906
259
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS907
260
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPKRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS908
261
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS909
262
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDNYHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS910
263
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDNDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS911
264
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDNYHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS912
265
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS913
266
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPKKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS914
267
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPEKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPHSKGSMSAVVERAG

PS915
268
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPKKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPHSKGSMSAVVERAG

PS916
269
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDDDHTYGYVIEMLNKVFGHPPEKGFELATEM

DKLGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS917
270
MPSAAPAKPKTKRQSRTQGMPPYNVVLLDDNYHTYGYVIEMLNKVFGHPPEKGFELATEV

DKNGRVIVMTTNLEVAELKRDEVHAFGPDPLMPRSKGSMSAVVERAG

PS918
271
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDPLMPRSKGSMSAVVEAEE

PS919
272
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDPLMPRSKGSMSASIEAEE

PS920
273
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGPDPLMPRSKGSMSAVVERAG

PS921
274
MPTAASATESAFEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS922
275
MPTAASATESAFEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS923
276
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS924
277
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS925
278
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS926
279
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS927
280
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS928
281
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS929
282
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS930
283
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS931
284
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS932
285
MPTAASATESAIEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS933
286
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS934
287
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS935
288
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS936
289
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS937
290
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS938
291
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS939
292
MPTAASATESAFEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS940
293
MPTAASATESAFEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS941
294
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS942
295
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS943
296
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS944
297
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PRERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS945
298
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS946
299
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS947
300
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS948
301
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS949
302
MPTAASATESAFEDTPAPARPVVDGRTKPKHQPRYHVVLWDDNYHTYQYVVVMLRSLFGH

PRERGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS950
303
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDNYHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS951
304
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDYHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS952
305
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS953
306
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDYHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS954
307
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDNDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS955
308
MPTAASATESAFEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS956
309
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTLGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS957
310
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS958
311
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS959
312
MHHHHHHHHHHDYDIPTTENLYFQGMPTAASATESAIEDTPAPARPEVDGRTKPKHQPRY

HVVLWDDDDHTYQYVVVMLRSLFGHPPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQI

HAFGYDRLLARSKGSMKASIEAEE

PS960
313
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGI

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS961
314
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS962
315
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PYARGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS963
316
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPARGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS964
317
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPWRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS965
318
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS966
319
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPARGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS967
320
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPARGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS968
321
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS969
322
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLAHSKGSMKASIEAEE

PS970
323
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPSRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS971
324
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS972
325
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLHSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLAHSKGSMKASIEAEE

PS973
326
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYLVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS974
327
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYIVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS975
328
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEFDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS976
329
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDNYHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS978
330
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLHSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS979
331
MPTAASGTESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVEMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS980
332
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PTERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS981
333
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPDRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS982
334
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLLGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS983
335
MPTAASATESAIEDTPAPARPEMDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRGQIHAFGYDRLLARSKGSMKASIEAEE

PS984
336
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYYVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS985
337
MPTAASATESAIEDTPAPARPEVDGRTKPKRQTRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS986
338
MPTAASATESAIEDTPAPARPEVDGRTVPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYHLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS987
339
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVVVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS988
340
MPTAASATESAIEDTPAPARPEVDGRTVPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS989
341
MPTAASATESAIEDTPAPARPEVDGRTKPRRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS990
342
MPTAASATESAIEDTPAPARPEVDGRTVPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS991
343
MPTAASATESAFEDTPAPARPEVDGRTKPIRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS992
344
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRCHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS993
345
MPTAASATESAIEDTPAPARSEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS994
346
MPTAASATESAIEDTPAPARPEVDGRTKPERQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS995
347
MPTAASATESAIEDTPAPARPEVDGCTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS996
348
MPTAASATESAIEDTPAPARPEVDGSTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS997
349
MPTAASATESAIEDTPAPARPEMDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAVGYDRLLARSKGSMKASIEAEE

PS998
350
MPTAASATESAIEDTPAPARPEVDGRTKPKRHPRYHVVLWDDDDHTYQYVVVMLQSLFGH

SPKRGYCLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS999
351
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGY

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1000
352
MPTAASATESAIEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1001
353
MPTAASATESAFEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRTLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1002
354
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRDLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1003
355
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PKQRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1004
356
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PQRRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1005
357
MPTAASATESAIEDTPAPARPVVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLLSLFGH

PSERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1006
358
MPTAASATESAFEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1007
359
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRYLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1008
360
MPTAASATESAIEDTPALARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLLSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1009
361
MPTAASATESAIEDTPAPARPVVDGRTKPKRQPRYHVVLWDDHDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1010
362
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRKAKELDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1011
363
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKELVTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1012
364
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRTLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1013
365
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRDLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1014
366
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRYLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1015
367
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PKQRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1016
368
MPTAASATESAFEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1017
369
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PQRRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1018
370
MPTAASATESAIEDTPAPARPVVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PQRRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1019
371
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1020
372
MPTAASATESAFEDIPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1021
373
MPTATSATESAIEDTPAPARPEVDGRTKPKRQPHYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1022
374
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1023
375
MPTAASATESAFEDIPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1024
376
MPTATSATESAIEDTPAPARPEVDGRTKPKRQPHYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1025
377
MPTAASATESAIEDTPAPARPEVDGRTKPKKQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1026
378
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGF

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1027
379
MPTAASATESAIEDIPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1028
380
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMFRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1029
381
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHALGRDRLLARSKGSMKASIEAEE

PS1030
382
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTNEHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1031
383
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMFRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHALGRDRLLARSKGSMKASIEAEE

PS1032
384
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGVVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1033
385
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMRTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1034
386
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIPLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1035
387
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVNWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1036
388
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTTEHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1038
389
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEEG

SAGSAAGSGEFMPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQY

VVVMLRSLFGHPPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKG

SMKASIEAEE

PS1043
390
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PKQRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEEG

SAGSAAGSGEFMPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQY

VVVMLRSLFGHPKQRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKG

SMKASIEAEE

PS1044
391
MSPILGYWKIKGLVQPTRLLLEYLEEKYEEHLYERDEGDKWRNKKFELGLEFPNLPYYID

PS1045
392
MSPILGYWKIKGLVQPTRLLLEYLEEKYEEHLYERDEGDKWRNKKFELGLEFPNLPYYID

PS1046
393
MGGLFFNALKNCKENFTVLQTIRQQQSTLNGSWVALLQTRNTLNRAGIRYMMDQNNIGSG

STVAELMESASISLKQAEKNWADYEALPRDPRQSTAAAAEIKRNYDIYHNALAELIQLLG

AGKINEFFDQPTQGYQDGFEKQYVAYMEQNDRLHDIAVSDNNASYS

PS1047
394
MGGLFFNALKNDKENFTVLQTIRQQQSTLNGSWVALLQTRNTLNRAGIRYMMDQNNIGSG

STVAELMESASISLKQAEKNWADYEALPRDPRQSTAAAAEIKRNYDIYHNALAELIQLLG

AGKINEFFDQPTQGYQDGFEKQYVAYMEQNDRLHDIAVSDNNASYS

PS1048
395
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYYVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1049
396
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYYVVMLRSLFGH

PPSRGYRMAKEIDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1050
397
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWEDDDETYQYIVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLKASIEAEE

PS1051
398
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDLTYQYLVVMLRSLFGH

PPSRGYRMIKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSPKASIEAEE

PS1052
399
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWEDDDETYQYLVVMLRSLFGH

PPSRGYRMAKEIDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1053
400
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDDTYQYLVVMLRSLFGH

PPSRGYRMMKEIDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLKASIEAEE

PS1054
401
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDETYQYLVVMLRSLFGH

PPSRGYRMVKEADTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1055
402
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWTDDDQTYQYMVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSPKASIEAEE

PS1056
403
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWSDDDETYQYIVVMLRSLFGH

PPSRGYRMIKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSVKASIEAEE

PS1057
404
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDDTYQYLVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1058
405
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMVKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSVKASIEAEE

PS1059
406
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWEDDDETYQYLVVMLRSLFGH

PPSRGYRMVKEIDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSWKASIEAEE

PS1060
407
MHHHHHHHHHHDYDIPTTENLYFQGMPTAASATESAIEDTPAPARPEVDGRTKPKRQPRY

HVVLWDDDDHTYQYVVVMLRSLFGHPPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQI

HAFGRDRLLARSKGSMKASIEAEE

PS1061
408
MPTAASATESAIEDTPAPARPEVDGRTEPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1062
409
MPTAASATESAIEDTPAPARSEVDGRTKPERQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1063
410
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHSYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1064
411
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHIYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1065
412
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLVGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1066
413
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

SPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1067
414
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1068
415
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMVTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1069
416
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTLGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1070
417
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRHAKTMDTQGRVIVLTTTREHAELKRDQIHALGRDRLLARSKGSMKASIEAEE

PS1071
418
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDRHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1072
419
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTDQYVVVMLRSLFGH

PPSRGYRMALEAHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1073
420
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLEDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEYDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1074
421
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYIVVMLRSLFGH

PPSRGYRMARIMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1075
422
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PRQRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1076
423
MAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGHPPSRGYRMA

KEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1077
424
MPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGHPPSRGYRMAKEMDTQGRVI

VLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1078
425
MPRYHVVLWDDDDHTYQYVVVMLRSLFGHPPSRGYRMAKEMDTQGRVIVLTTTREHAELK

RDQIHAFGRDRLLARSKGSMKASIEAEE

PS1079
426
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDPLIDRCKGSMSASIEAEE

PS1080
427
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDPLIDRCKGSMSASIEAEE

PS1082
428
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYIVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1083
429
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYTVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1084
430
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYLVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1085
431
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWEDDDHTYQYLVVMLRSLFGH

PPSRGYRMAKEYDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSNKASIEAEE

PS1086
432
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PTERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1087
433
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PTERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1088
434
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPWRGYRLAREMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1089
435
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPWRGYRLAREMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1090
436
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLEASIEAEE

PS1091
437
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLEASIEAEE

PS1092
438
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHASGRDRLLARSKGSYKASIEAEE

PS1093
439
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHASGRDRLLAHSKGSKKASIEAEE

PS1094
440
MPTAASATESAIEDTPAPARPEVDGCTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPERGYRLAKEMDTQGCVIVLTTTREHAELKRDQIYAFGYDRLLARSKGSMKASIEAEE

PS1095
441
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVEMLRTLFGH

PPERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKACIEAEE

PS1096
442
MPTAASATESAIEDTPAPARPEVDGRAKPKRQPRYHVVLWNDDDHTYQYVVVVLQSLFSH

PRERGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1097
443
MPTAASATESAIGDTPAPARPKMDGRTKPKRQPRYHVVLWNDDDHTYQYAVVMLQSLFGH

PPERGYRQAKEVDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

PS1098
444
MPTAASATESAIGDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRDLFGH

PPERGYHMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1099
445
MGSSHHHHHHSSGENLYFQGHMPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVL

WDDDDHTYQYVVVMLRSLFGHPPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFG

RDRLLARSKGSMKASIEAEE

PS1100
446
MGSSHHHHHHSSGENLYFQGHMQPRYHVVLWDDDDHTYQYVVVMLRSLFGHPPSRGYRMA

KEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1101
447
MHSKFSHAGRICGAKFKVREPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1102
448
MHSKFSHAGRICGAKFKVGEPIYRCKECQFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1103
449
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDYTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1104
450
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHRGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1105
451
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTRHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1106
452
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYVTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1107
453
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICREFN

NGICDCGDKEAWNHTLFCKAEEG

PS1108
454
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTERN

NGICDCGDKEAWNHTLFCKAEEG

PS1109
455
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

KGICDCGDKEAWNHTLFCKAEEG

PS1110
456
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGECDCGDKEAWNHTLFCKAEEG

PS1111
457
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKSAWNHTLFCKAEEG

PS1112
458
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKTAWNHTLFCKAEEG

PS1113
459
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKEAWNKTLFCKAEEG

PS1114
460
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHRGHHVYTTICTERN

NGICDCGDKEAWNHTLFCKAEEG

PS1115
461
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHRGHHVYTTICTERN

NGICDCGDKEAWNHELFCKAEEG

PS1116
462
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTYHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1117
463
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1118
464
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTKFN

NGICDCGDKEAWNHTLFCKAEEG

PS1119
465
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICKEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1120
466
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTKICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1121
467
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHKGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEG

PS1122
468
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1123
469
PLYQVVLLDDDDHTYDYIIEMLQQIFIFTMVEGYRRAEELERKGRSVLIVCELSEAEFAR

DQIPSYGSDWRLPHSQGSMSAVIEPAE

PS1124
470
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDSDHTRQYAVVMLRSLFGH

PPSRGYRMAKEMATQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1125
471
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDRDHTRQYAVVMLRSLFGH

PPSRGYRMAKEIRTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1126
472
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDRDHTSQYIVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1127
473
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDRDHTSQYIIVMLRSLFGH

PPSRGYRMAKELQTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1128
474
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVFWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAHEMCTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1129
475
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFYH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1130
476
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFYH

PPSRGYRMAHEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1131
477
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVQWDDDDHTYQYFVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1132
478
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVQIDDDDHTYQYVVVMLRSLFYH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1133
479
MPTAASATESAIEDTPAPARPEVDGRTVPQRQPRYHVVLWDDDDHTYQYVVGMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1134
480
MPTAASATESAIEDIPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMASEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1135
481
MPTAASATESAIEDTPAPARTEVDGRTVPKRQPRYHVVLWDDDDHTYQYVVEMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1136
482
MPTAASATESAIEDTPAPARPEVDGRTRPKRQPRYHVVLWDDDDHTYQYVVVMLRKLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1137
483
MPTAASATESAIEDTPAPARSEVDGYTVPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIRAFGRDRLLARSKGSMKASIEAEE

PS1138
484
MSGSKFRGHQKSKGNSYDVEVVLQHVDTGNSYLCGYLKIKGLTEEYPTLTVFFEGEIISK

KHPFLTRKWDADEDVDRKHWGKFLAFYQYAKSFNSDDFDYEELKNGDYVFMRWKEQFLVP

DHTIKDISGLSFAGFYYICFQKSAASIEGYYYHRSSEWYQSLNLTHV

PS1139
485
MSGSKFRGHQKSKGNSYDVEVVLQHVDTGNSYLCGYLKIKGLTEEYPTLTVFFEGEIISK

KHPFLTRKWDADEDVDRKHWGKFLAFYQYAKSFNSDDFDYEELKNGDYVFMRWKEQFLVP

DHTIKDISGASFAGFYYICFQKSAASIEGYYYHRSSEWYQSLNLTHV

PS1140
486
MSGSKFRGHQKSKGNSYDVEVVLQHVDTGNSYLCGYLKIKGLTEEYPTLTAFFEGEIISK

KHPFLTRKWDADEDVDRKHWGKFLAFYQYAKSFNSDDFDYEELKNGDYVFMRWKEQFLVP

DHTIKDISGLSFAGFYYICFQKSAASIEGYYYHRSSEWYQSLNLTHV

PS1141
487
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAHEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1142
488
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLISDDDHTYQYTVVMLRSLFGH

PPSRGYRMAHEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1143
489
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVFWDDDDHTYQYTVVMLRSLFYH

PPSRGYRMAHEMCTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1144
490
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVFWDDDDHTYQYTVVMLRSLFYH

PPSRGYRMAHEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1145
491
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRFIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1146
492
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVEWDDDSHTYQYVVVMLRSLFGH

PPSRGYRMDKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSEKASIEAEE

PS1147
493
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDVDHTYQYTVVMLRSLFGY

PPSRGYRMAKEVDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1148
494
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDRTYQYVVVMLRSLFGH

PPSRGYRMDKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1149
495
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDKDHTPQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1150
496
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWPDDDHTYQYVVVMLRSLFGH

PPSRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1151
497
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDCTYQYLVVMLRSLFGH

PPSRGYREAKEMDTQGRRIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1152
498
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMIKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1153
499
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGI

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1154
500
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVEMLRSLFGI

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1155
501
MPTAASATESAIKDTPAPARSEVDGRTKPERQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PTSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1156
502
MPTAASATGSAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRYLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1157
503
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWSDEDNTKQYIVVMLRSLFGH

PPSRGYRMVEELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSIKASIEAEE

PS1158
504
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVVWDDDDNDEDYVVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLKASIEAEE

PS1159
505
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDEDHTYDYIVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSVKASIEAEE

PS1160
506
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTRQYLVVMLRSLFGH

PPSRGYRMTEEADTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1161
507
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVIWDDEDHTHDYWVVMLRSLFGH

PPSRGYRMSEELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1162
508
MGDVQPETCRPSAASGNYFPQYPEYAIETARLRTFEAWPRNLKQKPHQLAEAGFFYTGVG

DRVRCFSCGGGLMDWNDNDEPWEQHARHLSQCRFVKLMKGQLYIDTVAAKPVLAEEKEES

TSIGGD

PS1163
509
MGSDAVSSDRNFPNSTNLPRNPSMADYEARIFTFGTWIYSVNKEQLARAGFYALGEGDKV

KCFHCGGGLTDWKPSEDPWEQHAKWYPGCKYLLEQKGQEYINNIHLTHSLEECLVR

PS1164
510
MGSDAVSSDRNFPNSTNLPRNPSMADYEARIFTFGTWIYSVNKEQLARAGFYALGEGDKV

KCFHCGGGLTDWKPSEDPWEQHARHYPGCKYLLEQKGQEYINNIHLTHSLEECLVR

PS1165
511
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRNDDVKCF

CCDGGLRCWESGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1166
512
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRNDDVKCF

CCDGGLRCWESGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1167
513
MGSMRYTVSNLSMQTHAARFKTFFNWPSSVLVNPEQLASAGFYYVGNSDDVKCFCCDGGL

RCWESGDDPWVQHAKWFPRCEYLIRIKGQEFIRQVQAS

PS1168
514
MGSMRYTVSNLSMQTHAARFKTFFNWPSSVLVNPEQLASAGFYYVGNSDDVKCFCCDGGL

RCWESGDDPWVQHARHFPRCEYLIRIKGQEFIRQVQAS

PS1169
515
MGSHMLETEEEEEEGAGATLSRGPAFPGMGSEELRLASFYDWPLTAEVPPELLAAAGFFH

TGHQDKVRCFFCYGGLQSWKRGDDPWTEHAKWFPSCQFLLRSKGRDFVHSVQETHSQLLG

SWDP

PS1170
516
MGSHMLETEEEEEEGAGATLSRGPAFPGMGSEELRLASFYDWPLTAEVPPELLAAAGFFH

TGHQDKVRCFFCYGGLQSWKRGDDPWTEHARHFPSCQFLLRSKGRDFVHSVQETHSQLLG

SWDP

PS1171
517
MGSHMSTNLPRNPSMTGYEARLITFGTWMYSVNKEQLARAGFYAIGQEDKVQCFHCGGGL

ANWKPKEDPWEQHAKWYPGCKYLLEEKGHEYINNIHLTRSLEGALVQTT

PS1172
518
MGSHMSTNLPRNPSMTGYEARLITFGTWMYSVNKEQLARAGFYAIGQEDKVQCFHCGGGL

ANWKPKEDPWEQHARHYPGCKYLLEEKGHEYINNIHLTRSLEGALVQTT

PS1173
519
MGSHMRYQEEEARLASFRNWPFYVQGISPCVLSEAGFVFTGKQDTVQCFSCGGCLGNWEE

GDDPWKEHAKWFPKCEFLRSKKSSEEITQYIQSYK

PS1174
520
MGSHMRYQEEEARLASFRNWPFYVQGISPCVLSEAGFVFTGKQDTVQCFSCGGCLGNWEE

GDDPWKEHARHFPKCEFLRSKKSSEEITQYIQSYK

PS1175
521
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLKASIEAEE

PS1176
522
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKEATTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSAKASIEAEE

PS1177
523
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDEDHTMQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSAKASIEAEE

PS1178
524
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKEIGTQGRVIVLTTTREHAELKRDQIHAFGHDRLLARSKGSAKASIEAEE

PS1179
525
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGHDRLLARSKGSAKASIEAEE

PS1180
526
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKEIYTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSAKASIEAEE

PS1181
527
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSAKASIEAEE

PS1182
528
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDRDHTYQYIVVMLRSLFGH

PPSRGYRMAKEAYTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLKASIEAEE

PS1183
529
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDRDHTAQYAVVMLRSLFGH

PPSRGYRMAKEIYTQGRVIVLTTTREHAELKRDQIHAFGHDRLLARSKGSAKASIEAEE

PS1184
530
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDNDHTLQYIVVMLRSLFGH

PPSRGYRMAKEVDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1185
531
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1186
532
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDGDHTWQYIVVMLRSLFGH

PPSRGYRMAKELTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1187
533
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDSDHTFQYIVVMLRSLFGH

PPSRGYRMAKELHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1188
534
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDADHTYQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1189
535
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTMQYIVVMLRSLFGH

PPSRGYRMAKEVTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1190
536
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDSDHTIQYIVVMLRSLFGH

PPSRGYRMAKEADTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1191
537
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTWQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1192
538
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1193
539
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDNDHTLQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1194
540
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYIVVMLRSLFGH

PPSRGYRMAKEISTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1195
541
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDGDHTLQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1196
542
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTIQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1197
543
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDEDHTMQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLKASIEAEE

PS1198
544
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEEG

SAGSAAGSGEFMDKDCEMKRTTLDSPLGKLELSGCEQGLHEIKLLGKGTSAADAVEVPAP

AAVLGGPEPLMQATAWLNAYFHQPEAIEEFPVPALHHPVFQQESFTRQVLWKLLKVVKFG

EVISYQQLAALAGNPAATAAVKTALSGNPVPILIPCHRVVSSSGAVGGYEGGLAVKEWLL

AHEGHRLGKPGLG

PS1199
545
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEEG

SAGSAAGSGEFMPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQY

VVVMLRSLFGHPPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKG

SMKASIEAEEGSAGSAAGSGEFMDKDCEMKRTTLDSPLGKLELSGCEQGLHEIKLLGKGT

SAADAVEVPAPAAVLGGPEPLMQATAWLNAYFHQPEAIEEFPVPALHHPVFQQESFTRQV

LWKLLKVVKFGEVISYQQLAALAGNPAATAAVKTALSGNPVPILIPCHRVVSSSGAVGGY

EGGLAVKEWLLAHEGHRLGKPGLG

PS1200
546
MSDSPVDLKPKPKVKPKLERPKLYKVMLLNDDYTPMSFVTVVLKAVFRMSEDTGRRVMMT

AHRFGSAVVVVCERDIAETKAKEATDLGKEAGFPLMFTTEPEEGSAGSAAGSGEFMSDSP

VDLKPKPKVKPKLERPKLYKVMLLNDDYTPMSFVTVVLKAVFRMSEDTGRRVMMTAHRFG

SAVVVVCERDIAETKAKEATDLGKEAGFPLMFTTEPEEGHHHHHHHHHHGGGSGGGSGGG

SGLNDFFEAQKIEWHEGGGSGGGSGGGSGLNDFFEAQKIEWHEGSAGSAAGSGEFMDKDC

EMKRTTLDSPLGKLELSGCEQGLHEIKLLGKGTSAADAVEVPAPAAVLGGPEPLMQATAW

LNAYFHQPEAIEEFPVPALHHPVFQQESFTRQVLWKLLKVVKFGEVISYQQLAALAGNPA

ATAAVKTALSGNPVPILIPCHRVVSSSGAVGGYEGGLAVKEWLLAHEGHRLGKPGLG

PS1201
547
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEGGSAGSAAGSGEFMDKDCEMKRTTLDSPLGKLELSGCE

QGLHEIKLLGKGTSAADAVEVPAPAAVLGGPEPLMQATAWLNAYFHQPEAIEEFPVPALH

HPVFQQESFTRQVLWKLLKVVKFGEVISYQQLAALAGNPAATAAVKTALSGNPVPILIPC

HRVVSSSGAVGGYEGGLAVKEWLLAHEGHRLGKPGLG

PS1202
548
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFN

NGICDCGDKEAWNHTLFCKAEEGGSAGSAAGSGEFMHSKFSHAGRICGAKFKVGEPIYRC

KECSFDDTCVLCVNCFNPKDHTGHHVYTTICTEFNNGICDCGDKEAWNHTLFCKAEEGGS

AGSAAGSGEFMDKDCEMKRTTLDSPLGKLELSGCEQGLHEIKLLGKGTSAADAVEVPAPA

AVLGGPEPLMQATAWLNAYFHQPEAIEEFPVPALHHPVFQQESFTRQVLWKLLKVVKFGE

VISYQQLAALAGNPAATAAVKTALSGNPVPILIPCHRVVSSSGAVGGYEGGLAVKEWLLA

HEGHRLGKPGLG

PS1203
549
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLLDDDDHTSQYVVVMLRSLFGH

PPSRGYRMSKEMDTQGRAIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1204
550
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLLDDPDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1205
551
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVQWDDDDHTYQYVVVMLRSLFYH

PPSRGYRMAHEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1206
552
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKPMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1207
553
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMKTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1208
554
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1209
555
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLQDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1210
556
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDGDHTSQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1211
557
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDTHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1212
558
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDSDHTGQYIVVMLRSLFGH

PPSRGYRMAKEKDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1213
559
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDLDHTYQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1214
560
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDGDHTWQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1215
561
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDGDHTWQYIVVMLRSLFGH

PPSRGYRMAKEAKTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1216
562
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDGDHTVQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1217
563
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDQDHTWQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1218
564
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHRGHHVYTTICTERN

NGICDCGDKEAWNHELFCKAEEGSAGSAAGSGEFMHSKFSHAGRICGAKFKVGEPIYRCK

ECSFDDTCVLCVNCFNPKDHRGHHVYTTICTERNNGICDCGDKEAWNHELFCKAEEG

PS1219
565
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEGGGSGGGSGGGSGMHSKFSHAGRICGAKFKVGEPIYRC

KECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFNNGECDCGDKTAWNHTLFCKAEEG

PS1220
566
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEGSAGSAAGSGEFMHSKFSHAGRICGAKFKVGEPIYRCK

ECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFNNGECDCGDKTAWNHTLFCKAEEG

PS1221
567
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEGSAGSAAGSGEFGSAGSAAGSGEFGSAGSAAGSGEFMH

SKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFNNG

ECDCGDKTAWNHTLFCKAEEG

PS1222
568
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEEG

GGSGGGSGGGSGMPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQ

YVWVMLRSLFGHPPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSK

GSMKASIEAEE

PS1223
569
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEEG

SAGSAAGSGEFGSAGSAAGSGEFGSAGSAAGSGEFMPTAASATESAIEDTPAPARPEVDG

RTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGHPPSRGYRMAKEMDTQGRVIVLTTTR

EHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1224
570
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLHDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1225
571
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGI

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1226
572
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTAQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1227
573
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDNDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1228
574
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1229
575
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTWQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1230
576
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1231
577
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGY

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1232
578
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTLQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1233
579
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTIQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1234
580
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHASGRDRLLARSKGSMKASIEAEE

PS1235
581
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PLSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1236
582
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDQHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1237
583
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRTIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1238
584
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLFDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1239
585
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMTKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1240
586
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGS

PPSRGYRMAKEMDTQGRLIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1241
587
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGV

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1242
588
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGL

PPSRGYRMAHEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1243
589
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDDDHTDQYVVVMLRSLFGH

PPSRGYRLAEEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1244
590
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLLDDDSHTYQYVVVMLRSLFGV

PPSRGYRMAAEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1245
591
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDHDHTYQYVVVMLRSLFGH

PPSRGYRMAKELHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1246
592
MEGNGPAAVHYQPASPPRDACVYSSCYCEENVWKLCEYIKNHDQYPLEECYAVFISNERK

MIPIWKQQARPGDGPVIWDYHVVLLHVSSGGQSFIYDLDTVLPFPCLFDTYVEDAIKSDD

DIHPQFRRKFRVICADSYLKNFASDRSHMKDSSGNWREPPPPYPCIETGDSKMNLNDFIS

MDPKVGWGAVYTLSEFTHRFGSKN

PS1247
593
MEGNGPAAVHYQPASPPRDACVYSSCYSEENVWKLCEYIKNHDQYPLEECYAVFISNERK

MIPIWKQQARPGDGPVIWDYHVVLLHVSSGGQSFIYDLDTVLPFPCLFDTYVEDAIKSDD

DIHPQFRRKFRVICADSYLKNFASDRSHMKDSSGNWREPPPPYPCIETGDSKMNLNDFIS

MDPKVGWGAVYTLSEFTHRFGSKN

PS1248
594
MEGNGPAAVHYQPASPPRDACVYSSCYSEENVWKLCEYIKNHDQYPLEECYAVFISNERK

MIPIWKQQARPGDGPVIWDYQVVLLHVSSGGQSFIYDLDTVLPFPCLFDTYVEDAIKSDD

DIHPQFRRKFRVICADSYLKNFASDRSHMKDSSGNWREPPPPYPCIETGDSKMNLNDFIS

MDPKVGWGAVYTLSEFTHRFGSKN

PS1249
595
MEGNGPAAVHYQPASPPRDACVYSSCYSEENVWKLCEYIKNHDQYPLEECYAVFISNERK

MIPIWKQQARPGDGPVIWDYQVVLLHVSSGGQSFIYDLDTVLPFPCLFDTYVEDAIKSDD

DIHPQFRRKFRVICADSYLKNFASDRSHEKDSSGNWREPPPPYPCIETGDSKMNLNDFIS

MDPKVGWGAVYTLSEFTHRFGSKN

PS1250
596
MGPAATAPQYQPVCPTRDACVYNSCYSEENIWKLCEYIKTHNQYLLEECYAVFISNEKKM

VPIWKQQARPENGPVIWDYHVVLLHVSREGQSFIYDLDTILPFPCPFDIYIEDALKSDDD

IHLQFRRKFRVVRADSYLKHFASDRSHMKDSSGNWREPPPEYPCIETGDSKMNLNDFISM

DPAVGWGAVYTLPEFVHRFSSKTY

PS1251
597
MGPAATAPQYQPVCPTRDACVYNSCYSEENIWKLCEYIKTHNQYLLEECYAVFISNEKKM

VPIWKQQARPENGPVIWDYQVVLLHVSREGQSFIYDLDTILPFPCPFDIYIEDALKSDDD

IHLQFRRKFRVVRADSYLKHFASDRSHMKDSSGNWREPPPEYPCIETGDSKMNLNDFISM

DPAVGWGAVYTLPEFVHRFSSKTY

PS1252
598
MGPAATAPQYQPVCPTRDACVYNSCYSEENIWKLCEYIKTHNQYLLEECYAVFISNEKKM

VPIWKQQARPENGPVIWDYQVVLLHVSREGQSFIYDLDTILPFPCPFDIYIEDALKSDDD

IHLQFRRKFRVVRADSYLKHFASDRSHEKDSSGNWREPPPEYPCIETGDSKMNLNDFISM

DPAVGWGAVYTLPEFVHRFSSKTY

PS1253
599
MVPAAAAARYQPASPPRDACVYNSCYSEENIWKLCEYIKNHDQYPLEECYAVFISNERKM

IPIWKQQARPGDGPVIWYYFFLLVRYHVKSIGFSFTFQAIPLVNTLEDILAQLFKFCIHM

HACVLWKFRVIRADSYLKNFASDRSHMKDSSGNWREPPPSYPCIETGDSKMNLNDFISMD

PEVGWGAVYSLSEFVHRFGSQNY

PS1254
600
MVPAAAAARYQPASPPRDACVYNSCYSEENIWKLCEYIKNHDQYPLEECYAVFISNERKM

IPIWKQQARPGDGPVIWYYFFLLVRYHVKSIGFSFTFQAIPLVNTLEDILAQLFKFCIHM

HACVLWKFRVIRADSYLKNFASDRSHEKDSSGNWREPPPSYPCIETGDSKMNLNDFISMD

PEVGWGAVYSLSEFVHRFGSQNY

PS1255
601
MAAGEPSPFLVRSDCLYTSCYSEENVWKLCEYIRDHRPCLLEQFSAVFISNENKMIPIWK

QKSAKGDGPVIWDYHVILLHESARDGNFVYDLDTILPFPSPCNTYIREALKCDSNIHCDF

RRKLRVVGAHEFLQTFASDRSHMRDSSSNWTKPPPPYPCIQTAESTMNLDDFISMNPEVG

WGTVYSLAAFIERFGDTTL

PS1256
602
MAAGEPSPFLVRSDCLYTSCYSEENVWKLCEYIRDHRPCLLEQFSAVFISNENKMIPIWK

QKSAKGDGPVIWDYQVILLHESARDGNFVYDLDTILPFPSPCNTYIREALKCDSNIHCDF

RRKLRVVGAHEFLQTFASDRSHMRDSSSNWTKPPPPYPCIQTAESTMNLDDFISMNPEVG

WGTVYSLAAFIERFGDTTL

PS1257
603
MAAGEPSPFLVRSDCLYTSCYSEENVWKLCEYIRDHRPCLLEQFSAVFISNENKMIPIWK

QKSAKGDGPVIWDYQVILLHESARDGNFVYDLDTILPFPSPCNTYIREALKCDSNIHCDF

RRKLRVVGAHEFLQTFASDRSHERDSSSNWTKPPPPYPCIQTAESTMNLDDFISMNPEVG

WGTVYSLAAFIERFGDTTL

PS1258
604
MNGLSAQHERIAPARHECVYTSCYSEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVP

IWKQKSGRGEEPVIWDYHVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYIN

PAFWRKLRVVPADVFLQNFASDRSHMKDASGGWRMPPPPYPCIETAESRMNLDDFISMNP

SVGWGHVYTLEEFVQHFGKT

PS1259
605
MNGLSAQHERIAPARHECVYTSCYSEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVP

IWKQKSGRGEEPVIWDYQVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYIN

PAFWRKLRVVPADVFLQNFASDRSHMKDASGGWRMPPPPYPCIETAESRMNLDDFISMNP

SVGWGHVYTLEEFVQHFGKT

PS1260
606
MNGLSAQHERIAPARHECVYTSCYSEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVP

IWKQKSGRGEEPVIWDYQVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYIN

PAFWRKLRVVPADVFLQNFASDRSHEKDASGGWRMPPPPYPCIETAESRMNLDDFISMNP

SVGWGHVYTLEEFVQHFGKT

PS1261
607
MESASSEYKVITPSGNQCVYTSCYSEENVWKLCEYIKNQRHCPLEEVYAVFISNERKKIP

IWKQKSSRGDEPVIWDYHVILLHASKQGPSFIYDLDTILPFPCSLDVYSMEAFQSDKHLK

PAYWRKLRVIPGDTYLKEFASDRSHMKDSDGNWRMPPPAYPCLETPESKMNLDDFICMDP

RVGYGEVYSLSDFVKHFGVK

PS1262
608
MESASSEYKVITPSGNQCVYTSCYSEENVWKLCEYIKNQRHCPLEEVYAVFISNERKKIP

IWKQKSSRGDEPVIWDYQVILLHASKQGPSFIYDLDTILPFPCSLDVYSMEAFQSDKHLK

PAYWRKLRVIPGDTYLKEFASDRSHMKDSDGNWRMPPPAYPCLETPESKMNLDDFICMDP

RVGYGEVYSLSDFVKHFGVK

PS1263
609
MESASSEYKVITPSGNQCVYTSCYSEENVWKLCEYIKNQRHCPLEEVYAVFISNERKKIP

IWKQKSSRGDEPVIWDYQVILLHASKQGPSFIYDLDTILPFPCSLDVYSMEAFQSDKHLK

PAYWRKLRVIPGDTYLKEFASDRSHEKDSDGNWRMPPPAYPCLETPESKMNLDDFICMDP

RVGYGEVYSLSDFVKHFGVK

PS1264
610
MEHVSSKYVNITPSRDECVYTSCYSEENVWKLCEHIKTQTQIHLDEVYAVFISNERKMIP

IWKQKSSRGDEPVVWDYHVVLLHQNQQGQSFIYDQDTVLPFSCPFHVYTTEAFHTDHGLK

PAFWRKLRVIPADTYLKNFASDRSHMKNADGTWRMPPPLYPCIETTDSKMNLDDFISMDS

KVGCGHVYSLSEFVKHFAEK

PS1265
611
MEHVSSKYVNITPSRDECVYTSCYSEENVWKLCEHIKTQTQIHLDEVYAVFISNERKMIP

IWKQKSSRGDEPVVWDYQVVLLHQNQQGQSFIYDQDTVLPFSCPFHVYTTEAFHTDHGLK

PAFWRKLRVIPADTYLKNFASDRSHMKNADGTWRMPPPLYPCIETTDSKMNLDDFISMDS

KVGCGHVYSLSEFVKHFAEK

PS1266
612
MEHVSSKYVNITPSRDECVYTSCYSEENVWKLCEHIKTQTQIHLDEVYAVFISNERKMIP

IWKQKSSRGDEPVVWDYQVVLLHQNQQGQSFIYDQDTVLPFSCPFHVYTTEAFHTDHGLK

PAFWRKLRVIPADTYLKNFASDRSHEKNADGTWRMPPPLYPCIETTDSKMNLDDFISMDS

KVGCGHVYSLSEFVKHFAEK

PS1267
613
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDIVICF

CCDGGLHCWQSGDDPWVEHALFFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1268
614
MHHHHHHHHHHDYDIPTTENLYFQGMHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCV

LCVNCFNPKDHLGHHVYTTICTEFNNGECDCGDKTAWNHTLFCKAEE

PS1270
615
MHHHHHHHHHHDYDIPTTENLYFQGRFSISNLSMQTHAARMRTFMYWPSS

VPVQPEQLASAGFYYVGRNDDVKCFCCDGGLRCWESGDDPWVEHAKWFPR

CEFLIRMKGQEFVDEIQGRY

PS1271
616
MGDVQPETCRPSAASGNYFPQYPEYAIETARLRTFEAWPRNLKQKPHQLAEAGFFYTGVG

DRVRCFSCGGGLMDWNDNDEPWEQHARHLSQCRFVKLMKGQLYIDTVAAKPVLAEEKEES

TSIGGDGSAGSAAGSGEFMGDVQPETCRPSAASGNYFPQYPEYAIETARLRTFEAWPRNL

KQKPHQLAEAGFFYTGVGDRVRCFSCGGGLMDWNDNDEPWEQHARHLSQCRFVKLMKGQL

YIDTVAAKPVLAEEKEESTSIGGD

PS1272
617
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRNDDVKCF

CCDGGLRCWESGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLSGSAGSA

AGSGEFMGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRN

DDVKCFCCDGGLRCWESGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

GGSHHHHHHHHHHGGGSGGGSGGGSGLNDFFEAQKIEWHEGGGSGGGSGGGSGLNDFFEA

QKIEWHE

PS1273
618
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRNDDVKCF

CCDGGLRCWESGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLSGSAGSA

AGSGEFMGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRN

DDVKCFCCDGGLRCWESGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1274
619
MGDVQPETCRPSAASGNYFPQYPEYAIETARLRTFEAWPRNLKQKPHQLAEAGFFYTG

VGDRVRCFSCGGGLMDWNDNDEPWEQHALWLSQCRFVKLMKGQLYIDTVAAKPVL

AEEKEESTSIGGDTGSAGSAAGSGEFMGDVQPETCRPSAASGNYFPQYPEYAIETARLR

TFEAWPRNLKQKPHQLAEAGFFYTGVGDRVRCFSCGGGLMDWNDNDEPWEQHAL

WLSQCRFVKLMKGQLYIDTVAAKPVLAEEKEESTSIGGDTGHHHHHHHHHHGGGSGG

GSGGGSGLNDFFEAQKIEWHEGGGSGGGSGGGSGLNDFFEAQKIEWHE*

PS1275
620
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRNDDVKCF

CCDGGLRCWESGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLSGGGSGG

GSGGGSGMGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGR

NDDVKCFCCDGGLRCWESGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLL

S

PS1276
621
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRNDDVKCF

CCDGGLRCWESGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLSGSAGSA

AGSGEFGSAGSAAGSGEFGSAGSAAGSGEFMGLENSLETLRFSISNLSMQTHAARMRTFM

YWPSSVPVQPEQLASAGFYYVGRNDDVKCFCCDGGLRCWESGDDPWVEHAKWFPRCEFLI

RMKGQEFVDEIQGRYPHLLEQLLS

PS1277
622
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDEDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1278
623
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAREMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1279
624
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1280
625
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDQDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1281
626
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDEHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1282
627
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTMQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1283
628
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTFQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1284
629
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTVQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1285
630
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDDTHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1286
631
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDEDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1287
632
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDDDHTFQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1288
633
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAREMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1289
634
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1290
635
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDEDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1291
636
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDEDHTFQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1292
637
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAREMTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1293
638
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDEDHTYQYVVVMLRSLFGH

PPSRGYRMAREMTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1294
639
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDEDHTFQYVVVMLRSLFGH

PPSRGYRMAKEMTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1295
640
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDEDHTFQYVVVMLRSLFGH

PPSRGYRMAREMTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1296
641
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLYDDEDHTFQYVVVMLRSLFGH

PPSRGYRMAREMTTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1297
642
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWSDEDHTHQYVVVMLRSLFGH

PPSRGYRMAKEIDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1298
643
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVIWEDDDHTYQYWVVMLRSLFGH

PPSRGYRMAKEAHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLKASIEAEE

PS1299
644
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVIWSDDDHTHDYVVVMLRSLFGH

PPSRGYRMTKELHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1300
645
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVMWDDQDNTDQYWVVMLRSLFGH

PPSRGYRMSEELHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSVKASIEAEE

PS1301
646
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVVWDDEDHTHQYWVVMLRSLFGH

PPSRGYRMAKEAHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSLKASIEAEE

PS1302
647
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTSQYVVVMLHSLFGH

PPSRGYRLAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1303
648
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWSDEDHTHQYIVVMLRSLFGH

PPSRGYRMAKEIDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1304
649
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTKQYIVVMLRSLFGH

PPSRGYRMAKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSVKASIEAEE

PS1305
650
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVMWEDEDHTFQYVVVMLRSLFGH

PPSRGYRMVKEMHTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1306
651
MASDTPESLMALCTDFCLRNLDGTLGYLLDKETLRLHPDIFLPSEICDRLVNEYVELVNA

ACNFEPHESFFSLFSDPRSTRLTRIHLREDLVQDQDLEAIRKQDLVELYLTNCEKLSAKS

LQTLRSFSHTLVSLSLFGCTNIFYEEENPGGCEDEYLVNPTCQVLVKDFTFEGFSRLRFL

NLGRMIDWVPVESLLRPLNSLAALDLSGIQTSDAAFLTQWKDSLVSLVLYNMDLSDDHIR

VIVQLHKLRHLDISRDRLSSYYKFKLTREVLSLFVQKLGNLMSLDISGHMILENCSISKM

EEEAGQTSIEPSKSSIIPFRALKRPLQFLGLFENSLCRLTHIPAYKVSGDKNEEQVLNAI

EAYTEHRPEITSRAINLLFDIARIERCNQLLRALKLVITALKCHKYDRNIQVTGSAALFY

LTNSEYRSEQSVKLRRQVIQVVLNGMESYQEVTVQRNCCLTLCNFSIPEELEFQYRRVNE

LLLSILNPTRQDESIQRIAVHLCNALVCQVDNDHKEAVGKMGFVVTMLKLIQKKLLDKTC

DQVMEFSWSALWNITDETPDNCEMFLNFNGMKLFLDCLKEFPEKQELHRNMLGLLGNVAE

VKELRPQLMTSQFISVFSNLLESKADGIEVSYNACGVLSHIMFDGPEAWGVCEPQREEVE

ERMWAAIQSWDINSRRNINYRSFEPILRLLPQGISPVSQHWATWALYNLVSVYPDKYCPL

LIKEGGMPLLRDIIKMATARQETKEMARKVIEHCSNFKEENMDTSR

PS1307
652
MLTNSEYRSEQSVKLRRQVIQVVLNGMESYQEVTVQRNCCLTLCNFSIPEELEFQYRRVN

ELLLSILNPTRQDESIQRIAVHLCNALVCQVDNDHKEAVGKMGFVVTMLKLIQKKLLDKT

CDQVMEFSWSALWNITDETPDNCEMFLNFNGMKLFLDCLKEFPEKQELHRNMLGLLGNVA

EVKELRPQLMTSQFISVFSNLLESKADGIEVSYNACGVLSHIMFDGPEAWGVCEPQREEV

EERMWAAIQSWDINSRRNINYRSFEPILRLLPQGISPVSQHWATWALYNLVSVYPDKYCP

LLIKEGGMPLLRDIIKMATARQETKEMARKVIEHCSNFKEENMDTSR

PS1308
653
MLTNSEYRMEQSIKLRRQVIQVVLNGMESYQEVTVQRNCCLTLCNFSIPEELEFQYRRVN

ELLLSILNQSRQDESIQRIAVHLCNALVCQVDNDHKEAVGKMGFVMTMLKLIQKKLADKT

CDQVMEFSWSALWNITDETPDNCEMFLNYSGMKLFLECLKEFPEKQELHRNMLGLLGNVA

EVRELRPQLMTSQFISVFSNLLESKADGIEVSYNACGVLSHIMFDGPEAWGICEPHREEV

VKRMWAAIQSWDINSRRNINYRSFEPILRLLPQGISPVSQHWATWALYNLVSVYPDKYCP

LLIKEGGIPLLKDMIKMASARQETKEMAWKVIEHCSNFKEENMDTSR

PS1309
654
MTGSAALFYLTNTEYRGEQSVRLRRQVIQVVLNGMEHYQEVTVQRNCCLTLCNFSIPEEL

EFQYRRVNLLLLKILEPLRQDESIQRIAVHLCNALVCQVDNDHKEAVGKMGFVKTMLNLI

QKKLQDRMCDQVMEFSWSALWNITDETPDNCQMFLECNGMNLFLECLKEFPDKQELHRNM

LGLLGNVAEVKALRPQLLTRQFITVFSDLLDSKADGIEVSYNACGVLSHIMFDGPGVWSM

EEPSRTHVMDKMWTAIQSWDVSSRRNINYRSFEPILRLLPQSGAPVSQHWATWALYNLVS

VYPSKYCPLLIKEGGVSLLQAVLELQTSHVETKDMARKVMEQCESFKEDPMDTSR

PS1310
655
MPEDQAGAAMEEASPYSLLDICLNFLTTHLEKFCSARQDGTLCLQEPGVFPQEVADRLLR

TMAFHGLLNDGTVGIFRGNQMRLKRACIRKAKISAVAFRKAFCHHKLVELDATGVNADIT

ITDIISGLGSNKWIQQNLQCLVLNSLTLSLEDPYERCFSRLSGLRALSITNVLFYNEDLA

EVASLPRLESLDISNTSITDITALLACKDRLKSLTMHHLKCLKMTTTQILDVVRELKHLN

HLDISDDKQFTSDIALRLLEQKDILPNLVSLDVSGRKHVTDKAVEAFIQQRPSMQFVGLL

ATDAGYSEFLTGEGHLKVSGEANETQIAEALKRYSERAFFVREALFHLFSLTHVMEKTKP

EILKLVVTGMRNHPMNLPVQLAASACVFNLTKQDLAAGMPVRLLADVTHLLLKAMEHFPN

HQQLQKNCLLSLCSDRILQDVPFNRFEAAKLVMQWLCNHEDQNMQRMAVAIISILAAKLS

TEQTAQLGTELFIVRQLLQIVKQKTNQNSVDTTLKFTLSALWNLTDESPTTCRHFIENQG

LELFMRVLESFPTESSIQQKVLGLLNNIAEVQELHSELMWKDFIDHISSLLHSVEVEVSY

FAAGIIAHLISRGEQAWTLSRSQRNSLLDDLHSAILKWPTPECEMVAYRSFNPFFPLLGC

FTTPGVQLWAVWAMQHVCSKNPSRYCSMLIEEGGLQHLYNIKDHEHTDPHVQQIAVAILD

SLEKHIVRHGRPPPCKKQPQARLN

PS1311
656
MVFNLTKQDLAAGMPVRLLADVTHLLLKAMEHFPNHQQLQKNCLLSLCSDRILQDVPFNR

FEAAKLVMQWLCNHEDQNMQRMAVAIISILAAKLSTEQTAQLGTELFIVRQLLQIVKQKT

NQNSVDTTLKFTLSALWNLTDESPTTCRHFIENQGLELFMRVLESFPTESSIQQKVLGLL

NNIAEVQELHSELMWKDFIDHISSLLHSVEVEVSYFAAGIIAHLISRGEQAWTLSRSQRN

SLLDDLHSAILKWPTPECEMVAYRSFNPFFPLLGCFTTPGVQLWAVWAMQHVCSKNPSRY

CSMLIEEGGLQHLYNIKDHEHTDPHVQQIAVAILDSLEKHIVRHGRPPPCKKQPQARLN

PS1312
657
MPEMLKLVVIGMRNHPTNLPVQLAASACVFNLTKQDLAAGMPVKLLADVTHLLLEAMKHF

PNHQQLQKNCLLSLCSDRILQDVPFNRFDAAKLVMQWLCNHEDQNMQRMAVAIISILAAK

LSTEQTAQLGAELFIVRQLLQIVRQKTSQNMVDTTLKFTLSALWNLTDESPTTCRHFIEN

QGLELFMKVLETFPSESSIQQKVLGLLNNIAEVKELHSELMCKDFIDQISKLLHSVEVEV

SYFAAGIIAHLVSRGEESWTLSSSLRETLLEQLHSAILSWPTPECEMVAYRSFNPFFPLL

ACFRTPGVQLWAVWAMQHVCSKNPVRYCSMLIEEGGLVRLHRIRDHMCADPDVLRITIAI

LDNLDRHLRKHGNPPCPKPPFAK

PS1313
658
MLTHAIEKPRPDILKLVALGMKNHPTTLNVQLAASACVFNLTKQELAFGIPVRLLGNVTQ

QLLEAMKTFPNHQQLQKNCLLSLCSDRILQEVPFNRFEAAKLVMQWLCNHEDQNMQRMAV

AIISILAAKLSTEQTAQLGAELFIVKQLLHIVRQKTCQSTVDATLKFTLSALWNLTDESP

TTCRHFIENQGLELFIKVLESFPSESSIQQKVLGLLNNIAEVSELHGELMVQSFLDHIRT

LLHSPEVEVSYFAAGILAHLTSRGEKVWTLELTLRNTLLQQLHSAILKWPTPECEMVAYR

SFNPFFPLLECFQTPGVQLWAAWAMQHVCSKNAGRYCSMLLEEGGLQHLEAITSHPKTHS

DVRRLTESILDGLQRHRARTGYTAIPKTQAHREKCNP

PS1314
659
MEGNGPAAVHYQPASPPRDACVYSSCYSEENVWKLCEYIKNHDQYPLEECYAVFISNERK

MIPIWKQQARPGDGPVIWDYQVVLLHVSSGGQSFIYDLDTVLPFPCLFDTYVEDAIKSDD

DIHPQFRRKFRVICADSYLKNFASDRSHMKDSSGNWREPPPPYPCIETGDSKMNLNDFIS

MDPKVGWGAVYTLSEFTHRFGSKNGSAGSAAGSGEFMEGNGPAAVHYQPASPPRDACVYS

SCYSEENVWKLCEYIKNHDQYPLEECYAVFISNERKMIPIWKQQARPGDGPVIWDYQVVL

LHVSSGGQSFIYDLDTVLPFPCLFDTYVEDAIKSDDDIHPQFRRKFRVICADSYLKNFAS

DRSHMKDSSGNWREPPPPYPCIETGDSKMNLNDFISMDPKVGWGAVYTLSEFTHRFGSKN

PS1315
660
MNGLSAQHERIAPARHECVYTSCYSEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVP

IWKQKSGRGEEPVIWDYHVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYIN

PAFWRKLRVVPADVFLQNFASDRSHMKDASGGWRMPPPPYPCIETAESRMNLDDFISMNP

SVGWGHVYTLEEFVQHFGKTGSAGSAAGSGEFMNGLSAQHERIAPARHECVYTSCYSEEN

VWKLCEHIKTSKRCPLGDVYAVFISNERKMVPIWKQKSGRGEEPVIWDYHVILLHDCHKE

QTFIYDLDTTLPFPCPFDTYVKEAFKSDNYINPAFWRKLRVVPADVFLQNFASDRSHMKD

ASGGWRMPPPPYPCIETAESRMNLDDFISMNPSVGWGHVYTLEEFVQHFGKT

PS1316
661
MNGLSAQHERIAPARHECVYTSCYSEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVP

IWKQKSGRGEEPVIWDYQVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYIN

PAFWRKLRVVPADVFLQNFASDRSHMKDASGGWRMPPPPYPCIETAESRMNLDDFISMNP

SVGWGHVYTLEEFVQHFGKTGGGSGGGSGGGSGMNGLSAQHERIAPARHECVYTSCYSEE

NVWKLCEHIKTSKRCPLGDVYAVFISNERKMVPIWKQKSGRGEEPVIWDYQVILLHDCHK

EQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYINPAFWRKLRVVPADVFLQNFASDRSHMK

DASGGWRMPPPPYPCIETAESRMNLDDFISMNPSVGWGHVYTLEEFVQHFGKT

PS1317
662
MNGLSAQHERIAPARHECVYTSCYSEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVP

IWKQKSGRGEEPVIWDYQVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYIN

PAFWRKLRVVPADVFLQNFASDRSHMKDASGGWRMPPPPYPCIETAESRMNLDDFISMNP

SVGWGHVYTLEEFVQHFGKTGSAGSAAGSGEFMNGLSAQHERIAPARHECVYTSCYSEEN

VWKLCEHIKTSKRCPLGDVYAVFISNERKMVPIWKQKSGRGEEPVIWDYQVILLHDCHKE

QTFIYDLDTTLPFPCPFDTYVKEAFKSDNYINPAFWRKLRVVPADVFLQNFASDRSHMKD

ASGGWRMPPPPYPCIETAESRMNLDDFISMNPSVGWGHVYTLEEFVQHFGKT

PS1318
663
MNGLSAQHERIAPARHECVYTSCYSEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVP

IWKQKSGRGEEPVIWDYQVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYIN

PAFWRKLRVVPADVFLQNFASDRSHMKDASGGWRMPPPPYPCIETAESRMNLDDFISMNP

SVGWGHVYTLEEFVQHFGKTGSAGSAAGSGEFGSAGSAAGSGEFGSAGSAAGSGEFMNGL

SAQHERIAPARHECVYTSCYSEENVWKLCEHIKTSKRCPLGDVYAVFISNERKMVPIWKQ

KSGRGEEPVIWDYQVILLHDCHKEQTFIYDLDTTLPFPCPFDTYVKEAFKSDNYINPAFW

RKLRVVPADVFLQNFASDRSHMKDASGGWRMPPPPYPCIETAESRMNLDDFISMNPSVGW

GHVYTLEEFVQHFGKT

PS1321
664
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVAMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1322
665
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVMMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1323
666
MPTAASATESAIEDTPAPARTEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1324
667
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVAMLRSLFGI

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1325
668
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVMMLRSLFGI

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1326
669
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVMMLRSLFGY

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1327
670
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAWGRDRLLARSKGSMKASIEAEE

PS1328
671
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PKSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1329
672
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1330
673
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLKSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1331
674
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLASLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1332
675
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLSSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1333
676
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPQRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1334
677
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVHMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1335
678
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSVFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1336
679
MPTAASATESAIEDTPAPARPEVDGKTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1337
680
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAYGRDRLLARSKGSMKASIEAEE

PS1338
681
MPTAASATESAIEDTPAPARSEVDGYTVPKRQQRYHVVLWDDDDHTYQYVVYMLRSVFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1339
682
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVYMLRSVFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1340
683
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTLQYVVVMLRSLFGH

PPSRGYRMAQEMETQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1341
684
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVEMLRHLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1342
685
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVSMLRSVFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIRARGRDPLLARSKGSMKASIEAEE

PS1343
686
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVAMLRSIFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMSASIEAEE

PS1344
687
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKELETQGRLIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1345
688
MPTAASATESAIEDTPAPARPEVDGRTKPKHQPRYHVVLWDDDDHTDQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMSASIEAEE

PS1346
689
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTDQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMSASIEAEE

PS1347
690
MPTAASATESAIEDTPAPARPEVDGYTVPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAYGRDRLLARSKGSMKASIEAEE

PS1348
691
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVTMLRSVFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1349
692
MPTAASATESAIEDTPAPARSEVDGYTVPKRQPRYHVVLWDDDDHTYQYVVIMLRSLFGH

PPSRGYRMAKEMDTQGRVTVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1350
693
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVIMLRSLFGH

PPSRGYRMAKEMDTQGRVTVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1351
694
MHSKFSHAGRICGAKFKVGERIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1352
695
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1353
696
MHSKFSHAGRICGAKFKVGEPIYRCKLCSFDDTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1354
697
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDATCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1355
698
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDCTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1356
699
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDGTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1357
700
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDHTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1358
701
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDKTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1359
702
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDPTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1360
703
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDQTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1361
704
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDRTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1362
705
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDSTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1363
706
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDVTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1364
707
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHIGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1365
708
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTIRTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1366
709
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTCFN

NGECDCGDKTAWNHTLFCKAEEG

PS1367
710
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTDFN

NGECDCGDKTAWNHTLFCKAEEG

PS1368
711
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTIFN

NGECDCGDKTAWNHTLFCKAEEG

PS1369
712
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTNFN

NGECDCGDKTAWNHTLFCKAEEG

PS1370
713
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTQFN

NGECDCGDKTAWNHTLFCKAEEG

PS1371
714
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTSFN

NGECDCGDKTAWNHTLFCKAEEG

PS1372
715
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTWFN

NGECDCGDKTAWNHTLFCKAEEG

PS1373
716
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTICTEKN

NGECDCGDKTAWNHTLFCKAEEG

PS1374
717
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDKTCVLCVNCFNPKDHIGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1375
718
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDVTCVLCVNCFNPKDHLGHHVYTTIRTCKN

NGECDCGDKTAWNHTLFCKAEEG

PS1376
719
MHSKFSHAGRICGAKFKVGERIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTIRTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1377
720
MHSKFSHAGRICGAKFKVGERIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTIRTEKN

NGECDCGDKTAWNHTLFCKAEEG

PS1378
721
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDDTCVLCVNCFNPKDHIGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1379
722
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDVTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1380
723
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDVTCVLCVNCFNPKDHIGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1381
724
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDVTCVLCVNCFNPKDHIGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1382
725
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDRTCVLCVNCFNPKDHIGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1383
726
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDRTCVLCVNCFNPKDHLGHHVYTTICTQKN

NGECDCGDKTAWNHTLFCKAEEG

PS1384
727
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDHTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1385
728
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDHTCVLCVNCFNPKDHIGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1386
729
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDQTCVLCVNCFNPKDHLGHHVYTTICTEKN

NGECDCGDKTAWNHTLFCKAEEG

PS1387
730
MHSKFSHAGRICGAKFKVGEPIYRCRLCSFDVTCVLCVNCFNPKDHLGHHVYTTIRTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1388
731
MHSKFSHAGRICGAKFKVGEPIYRCRLCSFDVTCVLCVNCFNPKDHLGHHVYTTIRTEKN

NGECDCGDKTAWNHTLFCKAEEG

PS1389
732
MHSKFSHAGRICGAKFKVGEPIYRCRLCSFDQTCVLCVNCFNPKDHLGHHVYTTIRTSFN

NGECDCGDKTAWNHTLFCKAEEG

PS1390
733
MHSKFSHAGRICGAKFKVGEPIYRCKLCSFDVTCVLCVNCFNPKDHLGHHVYTTIRTSKN

NGECDCGDKTAWNHTLFCKAEEG

PS1391
734
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDVTCVLCVNCFNPKDHLGHHVYTTIRTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1392
735
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDDTCVLCVNCFNPKDHLGHHVYTTIRTEKN

NGECDCGDKTAWNHTLFCKAEEG

PS1393
736
MHSKFSHAGRICGAKFKVGEPIYRCKLCSFDDTCVLCVNCFNPKDHLGHHVYTTIRTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1394
737
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDQTCVLCVNCFNPKDHLGHHVYTTICTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1395
738
MHSKFSHAGRICGAKFKVGEPIYRCKECSFDVTCVLCVNCFNPKDHLGHHVYTTIRTEKN

NGECDCGDKTAWNHTLFCKAEEG

PS1396
739
MHSKFSHAGRICGAKFKVGEPIYRCRLCSFDDTCVLCVNCFNPKDHLGHHVYTTIRTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1397
740
MHSKFSHAGRICGAKFKVGEPIYRCKLCSFDVTCVLCVNCFNPKDHLGHHVYTTIRTEFN

NGECDCGDKTAWNHTLFCKAEEG

PS1398
741
MHSKFSHAGRICGAKFKVGEPIYRCRECSFDHTCVLCVNCFNPKDHLGHHVYTTIRTDKN

NGECDCGDKTAWNHTLFCKAEEG

PS1399
742
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDDVCCF

CCDGALRCWQSGDDPWVEHALWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1400
743
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRNDIVRCF

CCDGALWCWESGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1401
744
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDEVRCF

CCDGGLHCWQSGDDPWVEHALWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1402
745
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYSGRNDEVRCF

CCDGVLHCWESGDDPWVEHAKHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1403
746
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYSGRNDLVACF

CCDGGLTCWESGDDPWVEHAKHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1404
747
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDIVRCF

CCDGVLGCWESGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1405
748
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDEVRCF

CCDGGLHCWQSGDDPWVEHARWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1406
749
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYVGRNDIVRCF

CCDGALHCWKSGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1407
750
MGLENSLETLRFSISNLSMQTHAARMRTKMYWESSVPVQWEQLASYGFQFVGRNDDVKCQ

CCDGGLRCWESGDDVAVEHSKRFIRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1408
751
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLHCWQSGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1409
752
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDIVKCF

CCDGVLHCWQSGDDPWVEHAKHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1410
753
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDEVRCF

CCDGVLHCWESGDDPWVEHARWFPRCEFLIRMNGQEFVDEIQGRYPHLLEQLLS

PS1411
754
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYSGRNDIVRCF

CCDGDLHCWESGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1412
755
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYAGRNDEVKCF

CCDGGLHCWESGDDPWVEHARHFPRCEFLIRMNGQEFVDEIQGRYPHLLEQLLS

PS1413
756
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDIVKCF

CCDGVLHCWQSGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1414
757
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLHCWQSGDDPWVEHAKHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1415
758
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLHCWQSGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1416
759
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLHCWESGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1417
760
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDIVKCF

CCDGVLHCWQSGDDPWVEHAKWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1418
761
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGALHCWQSGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1419
762
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLHCWQSGDDPWVEHARHFPRCEFLIRMKGQEFVDEVQGRYPHLLEQLLS

PS1420
763
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLHCWQSGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLPS

PS1421
764
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLRCWESGDDPWVEHAKHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1422
765
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLHCWQSGDDPWVEHATWFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1423
766
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYGGRNDLVKCF

CCDGVLHCWQSGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1424
767
MGLENSLETLRFSISNLSMQTHAARMRTFMYWPSSVPVQPEQLASAGFYYLGRNDLVKCF

CCDGVLHCWQGGDDPWVEHARHFPRCEFLIRMKGQEFVDEIQGRYPHLLEQLLS

PS1425
768
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYAYVVVMLVSLFGH

PPSRGYRMAKEMDVQGRVIVLTTTRAHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1426
769
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYAYVVVMLRSLFGH

PPSRGYRMAKEMDVQGRVIVLTTTRAHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1427
770
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVTMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1428
771
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPGRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1429
772
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRIAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1430
773
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEVDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1431
774
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAEFKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1432
775
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQINAFGRDRLLARSKGSMKASIEAEE

PS1433
776
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDSLLARSKGSMKASIEAEE

PS1434
777
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDGLLARSKGSMKASIEAEE

PS1435
778
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMTASIEAEE

PS1436
779
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAWGRDSLLARSKGSMKASIEAEE

PS1437
780
MPTAASATESAIEDTPAPARSEVDGYTVPKRQPRYHVVLWDDDDHTYQYVVGMLRSVFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1438
781
MPTAASATESAIEDTPAPVRPEVDGYTVPKRQPRYHVVLWDDDDHTYQYVVTMLRSLFGH

PPGRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1439
782
MPTAASATESAMEDTPAPARPEVDGRTKPKRQPRYHVVLWNDDDHTYQYVVVMLQSLFGH

PPKRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARCKGSMKASIEAEE

PS1440
783
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLQSLFGH

PPNRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGCDRLLARCKGSMKASIEAEE

PS1441
784
MPTAASATESAIEDPPAPARPEVDGRTKPKRQPRYHVVMWEDDDHTYQYVVVMLRSLFGH

PPNRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGCDRLLARSKGSMKASIEAEE

PS1442
785
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKELDTQGRVIVLTTTREHAELKRDQIRAYGRDGLLARSKGSMKASIEAEE

PS1443
786
MPTAASATESAIEDTPAPARSEVDGRTEPKRQPRYHVVLWDDDDHTYQYVVAMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDSLLARSKGSMKASIEAEE

PS1444
787
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

SASRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1445
788
MPTAASATESAIEDTPAPARSEVDGYTVPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1446
789
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVHMLRSIFGH

PPSRGYRMAKEMDTQGRVIVLTTTREYAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1447
790
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPERGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGRDRLLARSKGSMKASIEAEE

PS1448
791
MPTAASATESAIEDTPAPARPEVDGRTKPKRQPRYHVVLWDDDDHTYQYVVVMLRSLFGH

PPSRGYRMAKEMDTQGRVIVLTTTREHAELKRDQIHAFGYDRLLARSKGSMKASIEAEE

EXAMPLES
Example 1
Real-Time Dynamic Single-Molecule Protein Sequencing on an Integrated Semiconductor Device

In this example, a dynamic sequencing-by-degradation approach in which single surface-immobilized peptide molecules are probed in real time by a mixture of dye-labeled N-terminal amino acid recognizers was demonstrated. By measuring fluorescence intensity, lifetime, and intermolecular kinetics of recognizers on a semiconductor chip, the ability to annotate amino acids and collectively identify the peptide sequence was shown. Leveraging the kinetics of binding allows each recognizer to uniquely identify multiple amino acids. Also described here are the principles and processes to expand the number of recognizable amino acids. Furthermore, it was shown that this method is compatible with both synthetic peptides and natural peptides isolated from recombinant human proteins, and capable of detecting single amino acid changes and post-translational modifications. The results demonstrated a robust core technology that can serve as an accurate, sensitive, and scalable next-generation sequencing platform for proteins.

Measurements of the proteome provide deep and valuable insight into biological processes. However, methods with higher sensitivity are needed to fully understand the complex and dynamic states of the proteome in cells and changes to the proteome that occur in disease states, and to make this information more accessible. The complex nature of the proteome and the chemical properties of proteins present several fundamental challenges to achieving comprehensive sensitivity, throughput, and adoption on par with DNA sequencing technologies. These challenges include the large number of different proteins per cell (>10,000) and yet larger number of proteoforms; the very wide dynamic range of protein abundance in cells and biological fluids and lack of correlation with transcript levels; the costs and high detection limits of current mass spectrometry methods; and the inability to copy or amplify proteins. Methods to directly sequence single protein molecules offer the maximum possible detection sensitivity, with the potential to enable single-cell inputs, digital quantification based on read counts, detection of post-translational modifications (PTMs) and low-abundance or aberrant proteoforms, and cost and throughput levels that favor broad adoption.

Here, a single-molecule protein sequencing approach and integrated system for massively parallel proteomic studies was demonstrated. In this approach, peptides are immobilized in nanoscale reaction chambers on a semiconductor chip and N-terminal amino acids (NAAs) with dye-labeled NAA recognizers are detected in real time. Aminopeptidases sequentially remove individual NAAs to expose subsequent amino acids for recognition, eliminating the need for complex chemistry and fluidics (FIG. 1). A benchtop device with a 532 nm pulsed laser source for fluorescence excitation and electronics for signal processing was built (FIG. 6A). The semiconductor chip uses intensity and fluorescence lifetime, rather than emission wavelength, for discrimination of dye labels. The recognizers detect one or more types of NAAs and provide information for peptide identification based on the temporal order of NAA recognition and the kinetics of on-off binding.

CMOS fabrication technology was used to build a custom time-domain-sensitive semiconductor chip with nanosecond precision, containing fully-integrated components for single-molecule detection, including photosensors, optical waveguide circuitry, and reaction chambers for biomolecule immobilization (FIG. 1). Observation volumes less than 5 attoliters were achieved through evanescent illumination at reaction chamber bottoms from the nearby waveguide, enabling sensitive single-molecule detection in the context of high freely-diffusing dye concentrations (>1 μM).

The semiconductor chip uses a filterless system that excludes excitation light on the basis of photon arrival time, achieving greater than 10,000-fold attenuation of incident excitation light. Elimination of the need for an integrated optical filter layer increases the efficiency of fluorescence collection and enables scalable manufacturing of the chip. To enable discrimination of fluorescent dye labels attached to NAA recognizers by fluorescence lifetime and intensity, the chip rapidly alternates between early and late signal collection windows associated with each laser pulse, thereby collecting different portions of the exponential fluorescence lifetime decay curve. The relative signal in these collection windows (termed “bin ratio”) provides a reliable indication of fluorescence lifetime (FIGS. 6B-6F, and Materials and Methods).

In order for NAA binding proteins to function as recognizers in this approach, the average lifetime of the bound recognizer-peptide complex should be long enough (typically >120 ms) to generate detectable single-molecule binding events. Proteins from the N-end rule adapter family ClpS that natively bind to N-terminal phenylalanine, tyrosine, and tryptophan were evaluated. Using PS610, a recognizer derived from ClpS2 from A. tumefaciens, it was established that this recognizer binds detectably to immobilized peptides with these NAAs. Importantly, it was also determined that the kinetics of binding differ for each NAA. To demonstrate these properties, immobilized peptides containing the initial N-terminal sequences FAA, YAA, or WAA were incubated on separate chips with PS610 and data collected for 10 hours (Methods). NAA recognition was observed by PS610, characterized by continuous on-off binding during the incubation period, with distinct pulse duration (PD) for each peptide (FIG. 2A). Median PDs were 2.51, 0.73, and 0.31 s for FAA, YAA, and WAA, respectively. These values reflect differences in binding affinity driven by different dissociation rates for each type of protein-NAA interaction (FIGS. 7A-7B).

To expand the set of recognizable NAAs, N-end rule pathway proteins were investigated as a source of additional recognizers. In a comprehensive screen of diverse ClpS family proteins, a group of ClpS proteins from the bacterial phylum Planctomycetes with native binding to N-terminal leucine, isoleucine, and valine was discovered. Directed evolution techniques were applied to generate a Planctomycetes ClpS variant—P5961—with sub-micromolar affinity to N-terminal leucine, isoleucine, and valine, and recognition of these NAAs was demonstrated (FIG. 2B). The median PD of binding to peptides with N-terminal LAA, IAA, and VAA was 1.21, 0.28, and 0.21 s, respectively, in agreement with bulk characterization (FIG. 7C).

In a separate screen, a diverse set of UBR-box domains from the UBR family of ubiquitin ligases that natively bind N-terminal arginine, lysine, and histidine were investigated. The UBR-box domain from the yeast K. lactis UBR1 protein exhibited the highest affinity for N-terminal arginine, and this protein was used to generate an arginine recognizer, PS691. PS691 recognized arginine in a peptide with N-terminal RLA with a median PD of 0.23 s (FIG. 2C). Lower affinity binding to N-terminal lysine and histidine (FIGS. 7D-7E) was insufficient for single-molecule detection.

To demonstrate that amino acids in a single peptide molecule can be sequentially exposed by aminopeptidases and recognized in real time with distinguishable kinetics, an immobilized peptide containing the initial sequence FAAWAAYAA (SEQ ID NO: 832) was incubated with PS610 for 15 minutes, followed by addition of PhTET3, an aminopeptidase from P. horikoshii. The collected traces consisted of regions of distinct pulsing, which were referred to as recognition segments (RSs), separated by regions lacking recognition pulsing (non-recognition segments, NRSs). Analysis software was developed to automatically identify pulsing regions and transition points within traces (Methods). Traces began with recognition of phenylalanine with a median PD of 2.36 s (FIG. 2D), in agreement with the PD observed for FAA in recognition-only assays. This pattern terminated after aminopeptidase addition (on average 11 min after addition), and was followed by the ordered appearance of two RSs with median PDs of 0.25 s and 0.49 s (FIG. 2D), corresponding to the short and medium PDs obtained in YAA and WAA recognition-only assays. Thus, the introduction of aminopeptidase activity to the reaction resulted in the sequential appearance of discrete RSs with the expected kinetic properties in the correct order.

To demonstrate dynamic sequencing with two NAA recognizers, PS610 and PS961 were labeled with the distinguishable dyes atto-Rho6G and Cy3, respectively, and an immobilized peptide of sequence LAQFASIAAYASDDD (SEQ ID NO: 793) was exposed to a solution containing both recognizers. After 15 minutes, two P. horikoshii aminopeptidases with complementary activity covering all 20 amino acids were added—PhTET2 and PhTET3. The collected traces displayed discrete segments of pulsing alternating between PS961 and PS610 according to the order of recognizable amino acids in the peptide sequence (FIG. 2E). The average bin ratio and average PD associated with each RS readily distinguished the two dye labels and four types of recognized NAAs (FIG. 2F). Median PDs were 2.70, 1.43, 0.25, and 0.66 s for N-terminal LAQ, FAS, IAA, and YAS, respectively (FIG. 2G).

NAA-bound ClpS and UBR proteins also make contacts with the residues at position 2 (P2) and position 3 (P3) from the N-terminus that influence binding affinity. These influences are reflected in the modulation of PD depending on the downstream P2 and P3 residues, as observed above for LAA (1.21 s) compared to LAQ (2.70 s). It was found that these influences on PD vary within informatically advantageous ranges and can be determined empirically or approximated in silico to model peptide sequencing behavior a priori (FIGS. 7F-7H). A powerful feature of this recognition behavior in regards to peptide identification is that each RS contains information about potential downstream P2 and P3 residues or PTMs, whether or not these positions are the targets of an NAA recognizer.

To evaluate the kinetic principles of the dynamic sequencing method when applied to diverse sequences, the synthetic peptide DQQRLIFAG (SEQ ID NO: 794), corresponding to a segment of human ubiquitin, was characterized (FIGS. 3A-3D). Sequencing reactions were performed using a combination of three differentially-labeled recognizers—PS610, PS961, and PS691—and two aminopeptidases—PhTET2 and PhTET3 (Materials and Methods). The example trace in FIG. 3A starts with an NRS that corresponds to the time interval during which residues in the initial DQQ motif are present at the N-terminus. The first RS starts at 120 min, upon exposure of N-terminal arginine to recognition by PS691. Subsequent cleavage events sequentially expose N-terminal leucine, isoleucine, and phenylalanine to their corresponding recognizers, with fast transitions (average <10 s) from one RS to the next. The transition from leucine to isoleucine recognition by PS961 is readily identified as a sharp change in average PD. This overall pattern is replicated across many instances of sequencing of the same peptide, with similar PD statistics across traces, as each peptide molecule follows the same reaction pathway over the course of the sequencing run (FIGS. 3B-3C). Due to the stochastic timing of cleavage events, each trace displays distinct start times and durations for each RS (FIG. 3C).

This approach reports the binding kinetics at each recognizable amino acid position and the kinetics of aminopeptidase cleavage along the peptide sequence. High-precision kinetic information on binding is obtained from a single trace, since each RS typically contains tens to hundreds of on-off binding events, resulting in a distribution of PD and interpulse duration (IPD) measurements that can be analyzed statistically. The repetitive probing of each NAA also provides accurate recognizer calling, since calls are not based on the error-prone detection of a single event associated with one fluorophore molecule (FIG. 6F). Recognizer concentration governs IPD for each RS; higher recognizer concentrations result in shorter average IPDs and faster rates of pulsing (FIGS. 8A-8B). Higher recognizer concentrations, however, increase the fluorescence background from freely diffusing recognizers, resulting in lower pulse signal-to-noise, and can compete with aminopeptidases for N-terminal access. In practice, IPDs in the range of approximately 2 to 10 s provide a favorable balance among these factors.

The distribution of RS durations across an ensemble of replicate traces defines the rate of cleavage of each recognizable NAA. For DQQRLIFAG (SEQ ID NO: 794) peptide, average cleavage times of 31, 54, 39, and 86 min were observed for N-terminal arginine, leucine, isoleucine, and phenylalanine, respectively, with approximate single-exponential decay statistics for each position (FIG. 3D, FIG. 8C). The distribution of NRS durations reports the cleavage rate of a run of one or more non-recognized NAAs. The average NRS duration for the initial DQQ motif was 153 min (FIG. 3D). Average cleavage rates are a key parameter and are controlled by the aminopeptidase concentration in the assay (FIGS. 8D-8E). Given the exponential behavior, average RS durations of 10 to 40 min were targeted to provide sufficient time for pulsing data collection, avoid missed RSs due to rapid cleavage, and minimize excessively long RS durations. It was found helpful to visualize the sequencing profiles of peptides as kinetic signature plots—simplified trace-like representations of the time course of complete peptide sequencing containing the median PD for each RS, and the average duration of each RS and NRS (FIG. 3E). These highly characteristic features provide a wealth of sequence-dependent information for mapping traces from peptides to their proteins of origin.

To demonstrate that this core methodology and its kinetic principles apply to a wide range of peptide sequences, the synthetic peptides DQQIASSRLAASFAAQQYPDDD (SEQ ID NO: 795), RLAFSALGAADDD (SEQ ID NO: 796), and EFIAWLV (SEQ ID NO: 797) (a segment of human GLP-1) were sequenced under the same sequencing conditions used for DQQRLIFAG (SEQ ID NO: 794) (FIG. 3F). Each peptide generated a characteristic kinetic signature in accordance with its sequence (FIG. 3G). Readouts as far as position 18 (the furthest recognizable amino acid) in the peptide DQQIASSRLAASFAAQQYPDDD (SEQ ID NO: 795) were obtained, illustrating that the method is compatible with long peptides and capable of deep access to sequence information in peptides of lengths found in typical protein digests.

To illustrate how the kinetic parameters acquired from sequencing are sensitive to changes in sequence composition, sequencing was performed with a set of three peptides RLAFAYPDDD (SEQ ID NO: 798), RLIFAYPDDD (SEQ ID NO: 799), and RLVFAYPDDD (SEQ ID NO: 800)—that differ only at a single position, located immediately downstream from the PS961 N-terminal target leucine. Each type of amino acid at this position had a distinct effect on the PD acquired during recognition of N-terminal leucine by PS961. Median PDs of 1.29 s, 2.22 s, and 4.21 s were observed for LAF, LIF, and LVF, respectively (FIG. 4B). In addition to differences in PD for leucine, each peptide displayed a characteristic RS or NRS in the interval between leucine and phenylalanine recognition (FIG. 4A, FIG. 9A). These results demonstrate the sensitivity of the sequencing readout to variation at a single position and illustrate that both directly recognized NAAs and adjacent residues can influence the full kinetic signature obtained from sequencing.

Since the aminoacyl-proline bond of the YP motif in peptides such as RLIFAYPDDD (SEQ ID NO: 799) cannot be cleaved by the PhTET aminopeptidases, observation of YP pulsing at the end of a trace ensures that cleavage progressed completely from the first to last recognizable amino acid. The sequencing output from RLIFAYPDDD (SEQ ID NO: 799), therefore, provided a convenient dataset for examining biochemical sources of non-ideal behavior that could lead to errors in peptide identification. The main sources of incomplete information in traces were deletions of expected RSs due to the stochastic occurrence of rapid sequential cleavage events (FIG. 9B) and early termination of reads resulting from photodamage or surface detachment (FIG. 9C).

In addition to changes in amino acid sequence composition, sequencing readouts are sensitive to changes due to PTMs. As an example, methionine oxidation was examined. The thioether moiety of the methionine side chain is susceptible to oxidation during peptide synthesis and sequencing. It was determined that PS961 binds a peptide with N-terminal methionine with a K_Dof 947 nM (FIG. 9D) and it was hypothesized that oxidation, resulting in a polar methionine sulfoxide side chain, would eliminate binding and reduce NAA binding affinity when located at P2. It was determined computationally that methionine sulfoxide is highly unfavorable in the PS961 NAA binding pocket and that non-polar residues are preferred at P2 (FIG. 9E). The synthetic peptide RLMFAYPDDD (SEQ ID NO: 801) was sequenced, and two populations of traces with distinct kinetic signatures were observed—a first population containing leucine recognition with median PD of 0.86 s, and a second population with median PD of 0.35 s (FIG. 4C). Traces from the first population also displayed methionine recognition with short PD in the time interval between leucine and phenylalanine recognition (FIG. 4E). Methionine recognition was absent in traces from the second population (FIG. 4D), indicating that the methionine side chain in these peptides was not capable of recognition by PS961. When methionine was fully oxidized by preincubation with hydrogen peroxide (Materials and Methods), elimination of both methionine recognition and of the leucine recognition cluster was observed with long median PD, as expected (FIG. 4E). These results demonstrate the capability for extremely sensitive detection of PTMs due to their kinetic effects on recognition.

Proteomics applications require identification of peptides in mixtures derived from biological sources. To extend the results to peptide mixtures and biologically-derived peptides, two experiments were performed. First, DQQRLIFAG (SEQ ID NO: 794) and RLAFSALGAADDD (SEQ ID NO: 796) peptides were mixed, immobilized on the same chip, and a sequencing run was performed. Data analysis (Materials and Methods) identified two populations of traces corresponding to each peptide, with kinetic signatures in close agreement with those identified in runs with individual peptides (FIG. 5A, FIG. 9F). Second, to demonstrate that the method extends to biologically derived peptides, sequencing runs were performed with peptide libraries generated using a simple workflow from recombinant human ubiquitin (76 amino acids) and GLP-1 (37 amino acids) proteins digested with AspN/LysC and trypsin, respectively (Materials and Methods). For both libraries, data analysis readily identified traces matching the expected recognition pattern for the protease cleavage products DQQRLIFAGK (SEQ ID NO: 802) and EFIAWLVK (SEQ ID NO: 803) for ubiquitin and GLP-1, respectively, and produced kinetic signatures in agreement with synthetic versions of these peptides (FIG. 5B, FIG. 9G). Matches to the kinetic signature of the ubiquitin peptide DQQRLIFAGK (SEQ ID NO: 802) were identified across the human proteome, taking advantage of simple sequence constraints provided by kinetic information (Materials and Methods). Only one protein other than ubiquitin was found containing a peptide that could potentially match this signature; thus even short signatures can exhibit proteome abundance of less than one in 10⁴proteins. These results illustrate the potential of the full kinetic output from sequencing to enable digital mapping of peptides to their proteins of origin.

Discussion

The simple, real-time dynamic approach differs markedly from other recently described single-molecule approaches that rely on complex, iterative methods involving stepwise Edman chemistry or hundreds of cycles of epitope probing. Nanopore approaches offer the potential for real-time readouts and simplicity, but face substantial challenges related to the size and biophysical complexity of polypeptides. The sequencing technology described herein is readily expanded in its capabilities, and there are multiple areas for improvement. Expansion of proteome coverage can be achieved through directed evolution and engineering of recognizers. The NAA targets demonstrated here comprise approximately 35.6% of the human proteome, but lower-affinity NAA targets require longer PD to enable detection in all sequence contexts.

Recognizers for new amino acids or PTMs can be evolved from current recognizers or identified in screens of other scaffolds, such as other types of NAA- or PTM-binding proteins or aptamers. Overall, scaling to detection of all 20 natural amino acids and multiple PTMs is feasible for de novo sequencing; however partial sequences are sufficient for most proteomics applications, which rely on mapping to pre-defined sets of candidate proteins. Aminopeptidases can be engineered to optimize cleavage rates and minimize RS deletions from rapid sequential cleavage. It is envisioned that the dynamic range of samples and the applications most suitable for the system will tend to scale with the number of reaction chambers on the chip, and that compression of dynamic range will be necessary for certain applications.

It is anticipated that the sequencing technology demonstrated here will increase the accessibility of proteomics studies, enable new discoveries in biological and clinical research, and help power a new generation of precision medicine.

Materials and Methods

Semiconductor Device Operation and Bin Ratio Calculation

Experiments were performed on pre-production semiconductor chips with 296K active wells, taking into account some loss to flow cell occlusion of the sensor array. A dual chamber flow cell allows for two independent samples to be sequenced in parallel, each utilizing 148K active wells. Initial production devices have 2M active wells, scaling to tens of millions of active wells using standard CMOS processing for the first product line. Pulsed 532 nm excitation light from a 67 MHz mode-locked laser is coupled into a grating coupler at the edge of the semiconductor chip. The use of a single laser wavelength—in combination with fluorescent dye discrimination by fluorescence intensity and lifetime—reduces size, cost, and complexity, contributing to the scalability of the platform. A network of optical waveguides divides the excitation light and routes it to the sensor array to illuminate each reaction chamber. Each CMOS pixel contains a single light-sensitive photodiode with two high-speed global shutters (a reject gate and a collect gate) that discard and collect photoelectrons (chip photonic structures reduce pixel-to-pixel crosstalk to less than 2%). Control waveforms are applied to the collect and reject gates synchronously with the incident pulsed light source (FIG. 6B). Approximately 1 ns before the excitation pulse, the reject gate is charged to >3 volts and the collect gate is discharged below 1 volt. Scattered 532 nm excitation photons generate photoelectrons in the photodiode. The photoelectrons are quickly transferred to a high voltage drain by built-in potential fields within the photodiode and the reject gate potential. Between 1 and 3 ns after excitation, the collect gate is charged to >3 volts, the reject gate is discharged to <1 volt. Photoelectrons generated from emitted photons that arrive in the photodiode after the collect gate is opened are transferred to a storage node within each pixel. Photoelectrons are accumulated for 7.5 to 30 ms, configurable, within each pixel across approximately 500,000 to 2,000,000 laser pulses (FIG. 6B). The accumulated charge in the storage node is measured with the standard transfer gate, floating diffusion, source follower, row select, and on-chip analog-to-digital converters common to all CMOS image sensors, enabling scaling to large array sizes with small pixels. Fluorescence lifetime information is obtained by alternating the timing of the collect and reject gate waveforms between subsequent measurements. In the first measurement, only emission photoelectrons that arrive >3 ns after the excitation pulse (bin 0) are collected. In the second measurement, emission photoelectrons that arrive >1 ns after the excitation pulse (bin 1) are collected. Signal measured from the pixel as the phase relationship between the excitation source and the gate waveforms is adjusted throughout the entire excitation cycle demonstrates the pixel transitioning from 100% collection of photons during the collect phase to extinction of greater than 99.99% of photons during the rejection phase in less than lns (FIG. 6C). The ratio of these two measurements (bin ratio) provides an estimate of the fluorescence lifetime (FIG. 6D). We have demonstrated the ability to differentiate multiple dyes based on bin ratio alone (FIG. 6E).

Peptide Synthesis and Labeling

Peptides were synthesized on Rink Amide Resin on a PurePrep Chorus Solid-phase peptide synthesizer (Gyros Protein Technology) using Standard Fmoc chemistry. All synthetic peptides contained C-terminal Fmoc-azidolysine. The resin was deprotected in a mixture of TFA/TIPS/H20 (2.5%/2.5%/95%) at room temperature for 1.5 h. The deprotection mixture was concentrated under an argon stream. The peptides were precipitated from cold diethyl ether, resuspended in 1:1 water-acetonitrile, and purified on reverse phase HPLC (X-bridge C18, Waters) with a gradient of 10-70% acetonitrile (0.05% TFA) over 20 min. The residue was dried under high vacuum to generate white pellets. Into a solution of DBCO-DNA-biotin (2 nmol in 100 uL PBS) was added the peptide stock solution (4 uL, 5 mM) at room temperature. The reaction progress was monitored on LC-MS (Thermo UltiMate 3000 Executive Plus). After the reaction was completed, the mixture was conjugated to an excess of streptavidin. The peptide-DNA-streptavidin complex was purified on an ion exchange HPLC (DNAPac 200, Thermo). Gradient, buffer A, 20 mM sodium phosphate buffer, pH 8.5, buffer B, 1 M NaBr, 20 mM sodium phosphate buffer, pH 8.5, 20-60% B over 15 min. The purified complex was buffer-exchanged to a solution containing 50 mM MOPS (pH 8.0) and 60 mM potassium acetate on a 30K MWCO spin filter before use. The peptide containing fully oxidized methionine was prepared by mixing 3% hydrogen peroxide with the methionine peptide in 1:1 water-methanol at room temperature for 20 minutes. The product was immediately purified on a reverse-phase HPLC using the same peptide purification method described above, the purity was verified by reverse-phase HPLC (Thermo UltiMate 3000) on an analytical column (Zorbax SB-Aq, 5 μm, 4.6×250 mm), and the correct mass of the oxidized product was verified by LC-MS (Agilent LC-MSD-iQ, positive mode).

Protein Digestion and Labeling

GLP-1 7-37, GLP-2, and Ubiquitin (1-76) recombinant proteins were purchased from RnD Systems as lyophilized powder. Each protein was reconstituted in 100 mM HEPES, pH 8.0 (20% acetonitrile) to a final concentration of 200 μM. When necessary, cysteines were reduced and alkylated using TCEP (2 mM) and iodoacetamide (10 mM). GLP1 and GLP2 were digested using 1 μg of Trypsin (LCMS grade, Pierce) at 37° C. overnight. Ubiquitin was digested using 1 μg of LysC (LCMS grade, Pierce) and 1 μg of rAspN (LCMS grade, Promega). After protease digestion, pH of peptide mixtures was adjusted to pH 10.5 using potassium carbonate (57 mM), and lysines were converted to azidolysines using imidazole-1-sulfonyl azide (ISA, 2 mM) and copper sulfate catalyst (0.5 mM). ISA was quenched using polyurethane beads bearing an amine functionality (Oligo Factory). The mixture was then filtered and adjusted to pH 7-8 using 1 M acetic acid. The solution was diluted in 50% (v/v) of 10 mM MOPS, 10 mM KOAc, pH 7.5, added to DNA-streptavidin-DBCO complex, and incubated at 37° C. for 12-16 h. When required, the detergent Cetrimonium bromide was added to the reaction at a final concentration of 0.25 mM.

Recognizer Purification, Labeling, and Characterization

Expression vectors (with pET30 a+backbone) for recognizers and Biotin ligase were co-transformed into BL21(DE3) chemically competent E. coli cells. The transformed cells were plated on Luria agar plates containing carbenicillin (50 μg/mL) and kanamycin (25 μg/mL) and incubated overnight at 37° C. to obtain single colonies. The starter liquid cultures inoculated with colonies were grown in Luria broth with ampicillin (50 μg/mL) and kanamycin (25 μg/mL) and inoculated into large cultures at a starting optical density (0D600) of ˜0.01. The expression cultures were incubated at 37° C. at 230 rpm until OD600 approached ˜0.7. The cultures were then induced with 4 mM IPTG. The expressed recognizer was biotinylated in vivo by adding 8 mM biotin at the same time as IPTG. Cells were harvested after -12 hrs of expression by centrifugation at 10,000 g at 4° C., and the cell pellets were washed with lx PBS buffer pH 7.4. The cells were resuspended in Bug buster HT (Thermo Fisher Scientific) and incubated at room temperature for 30 mins on a magnetic stirrer. The cell suspension was then diluted with equal volume of 2× lysis buffer (100 mM Tris-HCl pH 7.5, 10% glycerol, 0.5 M NaCl) and incubated at room temperature for 30 mins on a magnetic stirrer. The lysate was centrifuged at 21,000 g at 4° C. to remove cell debris. Supernatant was collected and loaded on a Nickel NTA resin (Cytiva) affinity column pre-equilibrated with Buffer A (50 mM Tris-HCl pH 7.5, 10% glycerol, 0.5 M NaCl) on an AKTA Pure (Cytiva) system. The column was washed with at least ten column volumes of the buffer containing 10 mM imidazole. Elution was performed using a 10-300 mM imidazole gradient. Eluted fractions were dialyzed in a 10 kDa cassette against 4 L of dialysis buffer (50 mM Tris-HC1 pH 7.5, 0.2 M NaCl, 50% glycerol) at 4° C. overnight.

For labeling of the recognizers, equal volumes of recognizer and DNA-Dye-Streptavidin complex were mixed at 5:1 (recognizer:DNA-dye-SV) molar ratio. The mixture was incubated on ice for 30 m and dialyzed overnight against SEC buffer (25 mM HEPES pH 8.0, 150 mM KCl). The recognizer-dye conjugate was harvested from the dialysis and centrifuged at 10,000 g at 4° C. Supernatant was collected and concentrated using 10 kDa cut off concentrators. The concentrated conjugate was purified on an Agilent 1260 Infinity HPLC system using a size exclusion column (BioSEC-3 300 A, 3 μm).

Binding affinity was measured by polarization using a labeled peptide. The polarization response and total intensity measurements were carried out at 20° C. on a microplate fluorometer with 480 nm excitation and 530 nm emission. The interaction of recognizer with labeled peptide containing a target N-terminal residue (XAKLDEESILKQK-FITC (SEQ ID NO: 833)) was performed in PBS buffer at pH 7.4 and readings were collected after 30 min. Multiple analyses were performed at increasing recognizer concentration at a fixed concentration of a target peptide to obtain a titration curve. An equilibrium polarization response at each concentration was plotted and fit to calculate the K_D.

The off-rate (k_off) of PS610 was measured for various peptides using a stopped flow instrument. Labeled peptide (50 nM) was mixed with PS610 in PBS buffer pH 7.4 with 0.01% Tween-20 and incubated at 30° C. After 30 min of incubation, the recognizer:peptide complex was rapidly mixed with 10-20 fold molar excess of unlabeled trap peptide and the reaction was followed in real time by measuring the fluorescence intensity. At least three-time course traces were averaged and fit to an exponential equation.

Aminopeptidase Purification

Expression vectors (with pET30 a+backbone) for aminopeptidases PhTET2 and PhTET3 were transformed into BL21(DE3) chemically competent E. coli cells. The transformed cells were plated on Luria agar plates containing kanamycin (25 μg/mL) and incubated overnight at 37° C. to obtain single colonies. The starter liquid cultures inoculated with colonies were grown in Luria broth (LB) with kanamycin (25 μg/mL) and inoculated into large cultures at a starting optical density (OD600) of ˜0.01. The expression cultures were incubated at 37° C. at 230 rpm until OD600 approached ˜0.7. The cultures were then induced with 0.4 mM IPTG. The expressed aminopeptidase was purified as described above for recognizers. For conditioning, the aminopeptidase protein was dialyzed against 50 mM MOPS pH 8.0/ 60 mM potassium acetate and then exposed to cobalt acetate at a final concentration of 400μM for 1-1.5 h at 65° C. to form the active dodecamer complex. The conditioned aminopeptidase preparation was dialyzed further against 50 mM MOPS pH 8.0/60 mM potassium acetate, aliquoted, and flash frozen.

Peptide Loading, Recognition, and Dynamic Sequencing

The semiconductor chip was placed in the sequencing device and a chip check was performed to test electronic circuit function and to optimize laser coupling alignment. The chip was then removed from the device socket and the chip was washed twice with 50 μL of 70% isopropanol, followed by four washes with 30 μL of wash buffer (50 mM MOPS pH 8.0, 60 mM potassium acetate, 50 mM glucose, 20 mM magnesium acetate, and surfactant mix) through a flow cell attached to the chip. A second chip check was then performed. The laser was then blocked via an integrated software-controlled shutter, peptide complex was added to a final concentration of 1-10 nM and mixed thoroughly, and the chip was incubated for 15 min. The chip was then washed six times with wash buffer, followed by addition of an imaging solution (wash buffer with 5 mM Trolox and an oxygen scavenging system). The laser was unblocked and the occupancy percentage (target 10-30%, Poisson distributed) was recorded by acquiring a photobleaching signal from a fluorophore attached to the peptide complex during 5 min of laser illumination. For NAA recognition-only assays, after peptide loading, labeled recognizer was added to a final concentration of 50 nM PS610, 100 nM PS691, or 250 nM PS961 (as indicated according to the experiment), and data was recorded for 10 hours. For dynamic sequencing assays, after peptide loading, a mixture of labeled recognizers was added to obtain final concentrations of 50 nM PS610, 100 nM PS691, and 250 nM PS961. Data was recorded for 15 min. The laser was then blocked briefly and aminopeptidases were added to the sequencing reaction via the flow cell and mixed thoroughly (final concentration 2-8 μM PhTET2 and/or 20-80 μM PhTET3, as indicated according to the experiment). The laser was then unblocked, and data was recorded for 10 hours. For all runs, 30 μL of mineral oil was added to fluid reservoirs at each port of the flow cell to prevent evaporation during the run.

Signal Processing and Trace Segmentation

The measured signal on-chip comprises various noise components, the most dominant one being due to fluorescent emissions from diffusing recognizers in the reaction chamber. The pulse caller algorithm for a given reaction chamber starts by estimating the statistical properties of this background noise component. Once an estimate within certain error bounds has been established, the algorithm works in an online fashion observing new frames of data as they are generated. At each point in time, the algorithm maintains state indicating whether the signal is due to the background component only or a pulse from a recognizer-NAA interaction is being observed. The state transition from background to pulse is triggered using an edge detection test where the shift in signal is expected to be significant with respect to the background component's statistical distribution. The state transition from pulse to background is triggered when a small window of the most recent frames of the signal appears to conform to the background component's distribution again. The algorithm maintains an updated model of the background component as new background frames are observed. This provides robustness against drift in the signal intensity together with a feedback control loop that maintains a stable optical coupling of the laser into the chip based on any such detected drift. As detected pulses can be due to true recognizer-to-dipeptide interaction events as well as other occasional transient noise spikes, a downstream filter layer is employed to test the significance of pulse events based on their duration, intensity, and noise patterns within the context of the full timeline of the run and the entire dataset of reaction chambers.

Initial regions are determined by performing a sliding window calculation of pulse rate along the time dimension of a series of pulses. Regions with a mean pulse rate >1 pulse/min are then subdivided according to a greedy bisection approach. Here, the pulses on the left and right of each potential split are assessed for statistically significant deviation in any of four separate pulse properties—intensity, bin ratio, pulse duration, and interpulse duration—using a Mann-Whitney U Test. To define RSs, the split point with the lowest p-value for any of the four properties is used to sub-divide the region and the process continues until no regions remain with a candidate split point with p-value <10⁻⁵in any comparison. In this manner, transitions from one RS to the next in a region of continuous pulsing are determined a priori on the basis of changes in fluorescence properties of pulsing kinetics. The resulting regions are called recognition segments (RSs).

Recognition Segment Classification

RS classification for reactions containing single synthetic peptides was performed using an unsupervised clustering algorithm. A subset of RSs including those with mean signal-to-noise ratio of their constituent pulses of ≥3 were used to pre-train a Gaussian mixture model (GMM) to identify approximate centroids for each of N classes of recognition, where N equals the number of expected recognizable peptide states with F, Y, W, L, I, V, or R at the N-terminus. Identified clusters were assigned to recognizable peptide states by matching the predominant order of cluster sequences observed to the expected amino acid sequence and by using prior knowledge of dye properties to identify the binders active during each RS. Subsequent rounds of GMM fitting were performed on all RSs matching the expected order of these events to refine the GMM model until no further sequences appeared in the expected order. The final model was then applied to all RSs in a given reaction.

RS classification for reactions containing library prepared peptides and mixes of peptides was performed using a random forest classifier that was pre-trained on annotated RS pulse features from prior synthetic peptide experiments. Unless otherwise noted, figures and statistics produced from classified RSs are derived from reaction chambers containing the expected sequence of RSs.

Molecular Dynamics and Binding Energy Calculation

Homology models of PS961 complexed to peptide were generated using an internal crystal structure, mutations were applied and optimized using protCAD prior to molecular dynamics. AMBER20 implicit solvent molecular dynamics simulations using the generalized Born solvation potential were performed using the ff19SB force field with no atomic distance cutoff. Minimization was performed using steepest descent, followed by conjugate gradient minimization. The system was thermalized from 0 to 300K using Langevin dynamics and a collision frequency of 3 ps⁻¹. Molecular dynamics simulations of the equilibrated recognizer-peptide complex, free recognizer and free peptide were independently run for 5 nanoseconds at 300 K to perform the binding energy calculation using MMPBSA. Where 125 frames, each containing 10,000 2 femtosecond steps, were used for the calculation from the three simulations.

Binding energy and the decomposition of all residues contributing to the binding energy was computed in 0.15 M salt concentration.

Example 2
Peptide Identification Using Modeled Proteome-Wide Kinetic Signatures

Sequencing and biochemical data was used to determine predicted pulse durations for recognizers binding all possible tripeptide targets. FIGS. 10A-10C show heatmaps of predicted pulse durations for PS961 binding tripeptide targets having leucine (FIG. 10A), isoleucine (FIG. 10B), or valine (FIG. 10C) at the N-terminal position. FIGS. 10D-10F show heatmaps of predicted pulse durations for PS610 binding tripeptide targets having phenylalanine (FIG. 10D), tyrosine (FIG. 10E), or tryptophan (FIG. 10F) at the N-terminal position. FIG. 10G shows a heatmap of predicted pulse durations for PS1122 binding tripeptide targets having arginine at the N-terminal position. The predicted pulse durations displayed high correlation with actual pulse durations from on-chip experimental results for PS961 (FIG. 10H, left plot) and PS610 (FIG. 10H, right plot).

With this database of predicted tripeptide pulse durations, the expected kinetic signature of every peptide in the human proteome can be modeled, which could provide an improved understanding and utilization of the ability to identify proteins from sequencing output. A kinetic signature is an average representation of the sequencing behavior of a peptide on-chip, as detailed above in Example 1. The information in kinetic signatures derived from single-molecule traces dramatically improves the ability to map sequencing data to the proteome (e.g., compared to methods based on alignment of text strings, as in DNA sequencing). Kinetic information can include, for example, pulse duration, interpulse duration, and recognition segment (RS) duration.

To prepare a model demonstrating the ability to uniquely map peptides to the human proteome (with the recognizers PS961, PS610, and PS1122), an in silico digest of the proteome with AspN/LysC was performed, followed by a selection of all peptides that end in lysine (used for on-chip immobilization) and are greater than 7 amino acids in length. The results are shown below.

Human proteins (SWISS-Prot):
20,595 proteins

Peptides from AspN/LysC digest:
1,148,192

Peptides ending in lysine:
652,225

Peptides with >7 amino acids:
273,112

A predicted pulse duration was assigned to every visible amino acid in the set of 273,112 peptides (positions with predicted average PD of less than 0.18 s were treated as invisible). The distribution of predicted RSs in the first 15 residues is shown in FIG. 10I (left plot). 82,068 peptides contained 4 or more RSs (and thus were considered potentially informative). Kinetic signatures were created for each of these peptides.

The kinetic signature contains the expected binder and average PD at each visible position, and a gap to represent runs of one or more invisible amino acids. Next, for each peptide, the number of peptides with identical kinetic signatures was determined (signatures were considered identical if they had the same order of RSs and gaps, and the predicted PDs at each RS were somewhat similar (shorter PD not less than half the longer PD in any pairwise comparison)). According to this analysis, 38,849 out of 82,068 peptides produced a unique kinetic signature with no other matches in the human proteome. A further 10,571 peptides had only 1 other match. The distribution of kinetic matches per peptide is shown in FIG. 10I (middle plot). 14,167 proteins (69% of all proteins) contained at least one uniquely mappable peptide. On average, there were 2.5 uniquely mappable peptides per protein. The distribution of uniquely mappable peptides per protein is shown FIG. 10I (right plot).

To further illustrate this data and how it might be used to model protein behavior, results with IL6 protein are shown in FIG. 10J (for simplicity, residues immediately before C-terminal lysine were treated as invisible and XP motifs were treated as cleavable). As shown in FIG. 10J, two peptides contain at least 4 RSs. As shown in FIG. 10K, one of these peptides maps uniquely to IL6, and the other peptide matches the kinetic signature of 8 different peptides from 8 proteins.

To provide an illustrative example using a smaller proteome, the E. coli proteome (containing only 4,392 proteins) was analyzed as described above for the human proteome. The results are shown below.

E. Coli Proteins:
4,392

Peptides from AspN/LysC digest:
126,439

Peptides ending in lysine:
59,697

Peptides with >7 amino acids:
28,046

Peptides containing 4+ visible RSs
9,925

in first 15 residues:

Peptides having unique kinetic signatures:
7,740 (78%)

Proteins having at least one peptide with
3,527

4+ RSs in first 15 residues:

Proteins having at least one uniquely
3,187 out of 3527

mappable peptide (mean 2.4 peptides):

The distribution of predicted RSs in the first 15 residues is shown in FIG. 10L (left plot). 9,925 peptides contained 4 or more RSs (and thus were considered potentially informative). Kinetic signatures were created for each of these peptides. For each peptide, the number of peptides with identical kinetic signatures was determined. According to this analysis, 7,740 out of 9,925 peptides produced a unique kinetic signature with no other matches in the E. coli proteome. The distribution of kinetic matches per peptide is shown in FIG. 10L (middle plot). 3,187 proteins contained at least one uniquely mappable peptide. On average, there were 2.4 uniquely mappable peptides per protein. The distribution of uniquely mappable peptides per protein is shown FIG. 10L (right plot). To illustrate this data and how it might be used to model protein behavior, results with a protein from E. coli containing 6 peptides that are uniquely mappable are shown in FIG. 10M.

These results demonstrate the utility of a kinetics-centric view of peptide identification. This view also provides the ability to accurately model the informatic impact of changes to reaction conditions, such as the addition of new recognizers, increases in recognizer pulse duration, changes in frame rate, and addition of new dye labels.

Example 3
Direct Identification of Arginine Post-Translational Modifications

Proteins undergo a diverse array of post-translational modifications (PTMs) to their amino acid side chains that can strongly affect protein function and mediate intricate cellular events. Measuring the diversity, dynamics, and functional consequences of PTM states of proteins across the proteome is essential to understanding the role of proteins in health and disease. However, discovery and detection of PTMs and routine measurement of complex PTM states remains highly challenging and the diversity of proteoforms in the human proteome remains largely unmapped. New methods to enable sensitive detection of PTMs will greatly aid biomarker discovery, drug discovery, and the development of precision and personalized approaches to medicine.

Modifications of the arginine side chain are of particular biomedical interest. Methylation and citrullination of arginine residues in a number of human proteins have been shown to play key roles in disease states such as cardiovascular disease, autoimmune disease, and cancer. In this example, aspects of the technology described herein were applied to the detection of arginine methylation and citrullination with single-molecule resolution and sensitivity.

Arginine plays an important role in protein structure and function due to the unique properties of the guanidinium group that forms the terminus of its side chain (FIG. 11A). This group is both positively charged and capable of forming extended hydrogen bond networks and cation-n interactions with other amino acids and with nucleic acids. Arginine, therefore, often mediates key interactions between protein binding partners or between proteins and DNA.

The two most common arginine PTMs, dimethylation and citrullination, alter the arginine side chain and change its properties (FIG. 11A), potentially resulting in important downstream effects on cellular processes. Dimethylation retains arginine's positive charge but increases its size and hydrophobicity and blocks hydrogen bond formation. Citrullination eliminates arginine's positive charge, resulting in a neutral side chain with altered properties that can greatly impact protein conformation and function.

Dimethylation and citrullination of arginine are carried out by enzymes and may be part of the normal regulation of cellular processes or involved in disease states. Arginine dimethylation is catalyzed by protein arginine methyltransferases (PRMTs). PRMTs transfer two methyl groups either asymmetrically onto the same nitrogen atom, resulting in asymmetric dimethyl arginine (ADMA) or symmetrically onto opposite nitrogen atoms, resulting in symmetric dimethyl arginine (SDMA). These modifications increased size and hydrophobicity and block hydrogen bonding. Arginine citrullination is catalyzed by protein arginine deiminases (PADs). PADs carry out the hydrolysis of arginine's positively-charged guanidinium group, resulting in a neutral ureido group. This transformation results in a negligible mass increase of 0.9840 Da, but the loss of positive charge can dramatically alter protein conformation and function. FIG. 11A illustrates the structures of SDMA, ADMA, canonical arginine, and citrulline.

Arginine PTMs have emerged as important targets of biomedical research. Methylated arginine residues and their respective PRMTs have been implicated in important diseases such as cardiovascular disease and cancers. Critical involvement of arginine citrullination in immune system function, skin keratinization, myelination, and the regulation of gene expression has also been demonstrated. Notably, the removal of arginine's positive charge in some cases can cause proteins to activate the immune system, contributing to autoimmune diseases.

Challenges for the Detection of Arginine PTMs

Research into these arginine PTMs has been particularly challenging because they are difficult to detect and differentiate with current proteomic methods. Mass spectrometry is the most frequently utilized tool for detecting protein PTMs. However, mass spectrometry cannot easily distinguish ADMA and SDMA because they are constitutional isomers with identical mass. Likewise, deimination of arginine to citrulline results in a negligible mass increase of 0.9840 Da. This mass difference can easily be confused with a ¹³C isotope or misinterpreted as deamidation of nearby asparagine or glutamine residues. In addition, mass spectrometry techniques for arginine PTM detection require highly specialized knowledge and training and advanced analysis methods.

Enzyme-linked immunosorbent assay (ELISA), another common method for PTM detection, uses antibodies specifically generated to detect a modified protein of interest. Although arginine PTMs are estimated to be widespread in human cells, commercially available antibodies against arginine PTMs are limited to specific sites on a few highly studied proteins. The requirement to generate new antibodies, along with complex workflows, expense, antibody reproducibility, and other challenges associated with ELISA assay development, is likely to hinder discovery and further study of novel arginine PTM sites.

Continued development toward novel methods is needed to facilitate direct detection of arginine PTMs in proteins. Single-molecule protein sequencing offers an alternative approach to the detection of ADMA, SDMA, and citrulline that is not based on mass to charge ratio or antibody specificity, but rather on the kinetic signature of binding between recognizers and N-terminal amino acids (NAAs).

Aspects of the technology described herein gain insight into these PTMs with single molecule resolution, overcoming current technological gaps, and providing direct detection of arginine PTMs.

Methodology & Workflow

PTM detection involved isolating peptides and subjecting them to a real-time single-molecule protein sequencing reaction. Proteins were first digested into peptide fragments and conjugated C-terminally to macromolecular linkers. The peptide complexes were immobilized at the bottom of nanoscale wells on a semiconductor chip, resulting in single peptide molecules with exposed N-termini ready for sequencing. During the sequencing reaction, the surface-immobilized peptides were exposed to a solution containing dye-labeled NAA recognizers that bound on and off to their cognate NAAs with characteristic kinetic properties. Aminopeptidases in solution sequentially removed individual NAAs to expose subsequent amino acids for recognition. Fluorescence lifetime, intensity, and kinetic data were collected in real time and analyzed to determine amino acid sequence and PTM content.

The trace-level output included distinct pulsing regions called recognition segments (RSs); each RS corresponded to a period of time between aminopeptidase cleavage events during which an NAA recognizer bound on and off to its exposed target NAA. Chemical modifications to a target NAA or to a nearby downstream amino acid can modulate recognizer affinity, resulting in a characteristic change in the average pulse duration (PD) during an RS relative to an unmodified peptide. These modifications can also influence the rate of aminopeptidase cleavage of an NAA, resulting in a characteristic change in average duration of the corresponding RS.

A summary of the workflow for sequencing of peptides and detection of PTMs is presented in FIG. 11B.

Results & Discussion

Detection of Arginine Dimethylation

First, the detection and differentiation of arginine, ADMA, and SDMA by single-molecule protein sequencing was demonstrated. The focus was on a key segment of the signaling protein P38MAPKa. Dimethylation of arginine residue 70 of P38MAPKa in myoblast cells by PRMT7 is a critical regulatory step in the activation of myoblast differentiation in humans.

Synthetic peptides corresponding to residues 69 to 76 of P38MAPKa were generated in three versions containing either arginine, ADMA, or SDMA at position 2: YRELRLLK (SEQ ID NO: 834), YRA_DMAELRLLK (SEQ ID NO: 835), and YR_SDMAELRLLK (SEQ ID NO: 836). Each peptide was sequenced using three recognizers—PS610 (F, Y, W), PS961 (L, I, V), and PS621 (R)—and data were analyzed to identify RSs, determine the mean PD of each RS, and characterize the kinetic signature of each peptide. Each peptide displayed a distinguishable pattern due to the distinct kinetic influences of arginine, ADMA, and SDMA on recognizer binding (see example traces in FIG. 11C-A).

Arginine and ADMA residues exhibited binding with the recognizer PS621 with similar PD, whereas SDMA exhibited no binding (FIG. 11C-A, 11C-B). This result indicated that symmetric dimethylation of arginine—in contrast to asymmetric dimethylation—reduced the affinity of PS621 for N-terminal arginine, providing a clear kinetic difference between these isomeric arginine PTMs. The NAA recognizers used in this example contact residues at positions 2 and 3 from the N-terminus when they bind to their target NAAs; therefore, modification of these downstream residues can influence recognizer binding affinity. A strong influence of arginine dimethylation on recognition of the upstream tyrosine residue in these peptides by PS610 was observed (FIG. 11C). The median pulse duration of tyrosine recognition increased from 0.69 s for YRE to 1.47 s and 1.48 s for YRA_DMAEand YR_SDMArespectively (FIG. 11C-B). In addition, the median interpulse duration (IPD) of arginine recognition by PS621 decreased from 10.05 s for unmodified arginine to 5.82 s for ADMA (FIG. 11C-C).

The influence that these dimethylated arginine residues have on the recognition of preceding NAAs serves as a powerful feature of protein sequencing with single-molecule sensitivity and precision. These results demonstrate the capacity for unprecedented sensitivity in detection of arginine dimethylation using aspects of technology described herein.

Detection of Arginine Citrullination

It was next demonstrated that differential binding kinetics could be used to rapidly differentiate citrullinated arginine residues from native arginine residues. Two synthetic peptide sequences containing either arginine or citrulline at position 2—LRLAFAYPDDDK (SEQ ID NO: 817) and LCitLAFAYPDDDK (SEQ ID NO: 839)—were generated and sequenced using three recognizers as described above. Each peptide displayed a highly distinguishable kinetic signature due to the influence of the different arginine and citrulline side chains on recognition (FIG. 11D-A, 11D-B). Citrullination eliminated N-terminal arginine recognition by PS621 (see example traces in FIG. 11D-A). Citrullination at position 2 also resulted in a large increase in the median PD of recognition of the N-terminal leucine located at the preceding position by PS961. Median PD was 0.43 s for LRL increased to 0.78 s for LCitL (FIG. 11D-B). These results demonstrate the capability to detect and digitally quantify arginine citrullination.

Conclusion

In this example, arginine PTMs were directly detected. Arginine PTMs play important roles in human health and disease but have been challenging to study. Current proteomic methods such as mass spectrometry and ELISA have been capable of just indirect identification of these arginine PTMs using highly specialized techniques or limited to a small set of specific proteins on the basis of antibody availability and other challenges. The ability to directly detect PTMs offers great potential for accelerated biomedical research and for a wide range of commercial applications in drug discovery and biomarker development.

Example 4
Identification of Threonine Post-Translational Modification

Sequencing reactions using the recognizers PS691 (R), PS610 (FYW), and PS961 (LIV) were performed separately for the peptides RLTFIAYPDDD (SEQ ID NO: 821) and RLpTFIAYPDDD (SEQ ID NO: 822) (where pT is phosphothreonine). Recognition of the N-terminal leucine preceding threonine or phosphothreonine by PS961 was observed, with distinct pulse duration for leucine followed by threonine (RS mean PD=1.2 s; FIG. 14A) compared to leucine followed by phosphothreonine (RS mean PD=0.3 sec; FIG. 14B). Moreover, recognition segment (RS) durations for leucine recognition were longer when leucine was followed by phosphothreonine (RS mean duration=130 min; FIG. 14C, right panel) compared to threonine (RS mean duration=8.1 min; FIG. 14C, left panel). These data demonstrate the ability to discriminate between unmodified and post-translationally modified threonine side chains.

Example 5
Identification of Tyrosine Post-Translational Modification

Sequencing reactions using the recognizers PS691 (R), PS610 (FYW), and PS961 (LIV) were performed separately for the peptides RLYFIAYPDDD (SEQ ID NO: 823) and RLpYFIAYPDDD (SEQ ID NO: 824) (where pY is phosphotyrosine). Recognition of the N-terminal arginine and leucine residues preceding tyrosine or phosphotyrosine by PS691 and PS961, respectively, was observed, with distinct pulse durations depending on whether the peptide contained tyrosine (FIG. 15A) or phosphotyrosine (FIG. 15B). Recognition of N-terminal arginine occurred with RS mean PD of 0.9 s for RLY and 0.45 s for RLpY. Recognition of N-terminal leucine occurred with RS mean PD of 2.45 s for LYF and 3.4 s for LpYF. Moreover, traces from the peptide RLpYFIAYPDD (SEQ ID NO: 840) contained a consensus gap between L and F, since pY was not recognized by PS610, whereas traces from the peptide RLYFIAYPDDD (SEQ ID NO: 823) contained Y recognition by PS610 during this interval. These data demonstrate the ability to discriminate between unmodified and post-translationally modified tyrosine side chains.

Example 6
Identification of Lysine Post-Translational Modification

Sequencing reactions using the recognizers PS691 (R), PS610 (FYW), PS961 (LIV), and PS1165 (A) were performed separately for the peptides RLYFKAYPDDD (SEQ ID NO: 825) and RLK{acetyl}FIAYPDDD (SEQ ID NO: 826) (where K{acetyl} is an acetylated lysine). Recognition of the N-terminal phenylalanine and alanine residues preceding lysine or acetyl-lysine by PS610 and PS1165, respectively, was observed, with distinct pulse durations depending on whether the peptide contained lysine (F=1.4 s, A=1.3 s; FIG. 16A) or acetylated lysine (F=1.8 s, A=2.2 s; FIG. 16B). Recognition of N-terminal phenylalanine occurred with RS mean PD of 1.4 s for FAK and 1.8 s for FAK{acetyl }. Recognition of N-terminal alanine occurred with RS mean PD of 1.3 s for AK and 2.2 s for AK{acetyl}. These data demonstrate the ability to discriminate between unmodified and post-translationally modified lysine side chains.

Example 7
Identification of Beta-Amyloid Variants

Introduction and Significance

Alzheimer's is a neurogenerative disease that affects tens of millions of people worldwide and carries no clear genetic marker. A hallmark of Alzheimer's is the accumulation of mutated beta-amyloid proteins, creating plaques around neurons that disrupt normal cell function in the brain. The technology described herein may be used to sequence and identify key β-amyloid variants that are indicative of early-onset Alzheimer's, which enables understanding of the underlying disease's pathway to further optimize treatment responsiveness and identify targets with therapeutic potential.

Alzheimer's is a very complex disease and less than 1% of cases can be connected to a single inherited gene. Therefore, DNA sequencing alone can only give a limited view of the disease, its causes, and its pathways; further exploration of the disease mechanisms must occur at the protein level. There is evidence that point mutations in β-amyloid can lead to protein misfolding, which can contribute to the cause of disease or provide markers for early disease progression. Several variants of β-amyloid have been shown to induce misfolding, which exposes hydrophobic regions and causes protein deposition around neurons, then altering cellular function in the brain. The fibril forming peptides 16KLVF19 (SEQ ID NO: 843) and 17LVFF20 (SEQ ID NO: 844) have been explored for targeted drug developments via the β-sheet breaker mechanism.

FIG. 17A illustrates an example of a β-amyloid variant. The β-amyloid variant induces misfolding of the protein, exposing hydrophobic regions, which induces aggregation. This alteration in structure morphs the β-amyloid into long filamentous chains or fibril formation, which generate insoluble deposits, which are referred to as pathological plaque.

The research around different types of recognizable proteins and potential PTMs has been largely limited in traditional proteomics. B-amyloid plaque formation is shown to be driven by a single mutation in a folded region of the protein, making their presence challenging to detect by legacy proteomic methods. Aspects of the technology described herein may be used to assess proteins at the individual amino acid level without the need for developing binding affinity assays, an invaluable tool to fully understand biological processes and monitor disease states directly.

Methodology and Workflow

Aspects of the technology described herein may be used for protein preparation, peptide library preparation, peptide sequencing and peptide profiling of synthetic samples of ß-amyloid. In this example, the wild type (LVFFAE (SEQ ID NO: 827)) and variants (17LVFFAK22 (SEQ ID NO: 828), 17LVFFGK22 (SEQ ID NO: 829), 17LVFFAG22 (SEQ ID NO: 830), and 17LVPFAE22 (SEQ ID NO: 831)) of β-amyloid were digested and labeled for further analysis. Alternatively, β-amyloid may be purified from common sources, such as cerebrospinal fluid (CSF), for downstream analysis.

FIG. 17B illustrates an example workflow for β-amyloid variant detection. As shown in FIG. 17B, β-amyloid cerebrospinal fluid may be isolated. A peptide library may be prepared utilizing specific proteolytic enzymes. The sample may be loaded onto a chip, as described herein, and sequencing may be run. Results may include identification of amino acid sequences that demarcate potential Alzheimer's causing mutations.

A chip including aspects of the technology described herein was used for the downstream sequencing of the sample material. The chip contained millions of wells, each of which acted as an independent sequencing machine. Once the sample was loaded, cloud technology was used to set up the sequencing run and collect all the data for visualization. Once collected in the cloud, a set of proprietary algorithms, which can identify amino acids based on the specialized optical pulse patterns of each binding event, determined the sequence of the peptide and mapped that sequence back to a specific protein or protein variant.

Here, the protein sequencing technology and analysis pipeline was successfully used to distinguish a variety of clinically significant ß-amyloid point mutations. The sequencing traces containing pulse patterns of the variants, 17LVFFAK22 (SEQ ID NO: 828), 17LVFFGK22 (SEQ ID NO: 829), 17LVFFAG22 (SEQ ID NO: 830), and 17LVPFAE22 (SEQ ID NO: 831), were compared to the wild type, 17LVFFAE22 (SEQ ID NO: 827). These patterns are shown in FIGS. 17C-17G. Software automatically identified pulses containing the same intensity, lifetime, and kinetics, which determined a recognition segment for a specific amino acid. Each recognition segment was color coded based on the N-terminal amino acid, and the collection of recognition segments provided a characteristic signature of the peptide.

Time domain sequencing functionality can observe sequence changes indirectly during peptide profiling. The specific PTMs and folding of each variant cause them to display distinctly different patterns, which can then be inferred via alterations in pulse width. For example, a point mutation in a sequence—at the N-terminal end, or at the penultimate and antepenultimate positions, of the peptide—can generate an altered pulse pattern, compared to another sequence.

TABLE 2

Average Pulse Width of Tripeptides and Variants

Tripeptide
Variant
Average Pulse Width

LVX
WT
3.26 (LVF)

F19P
1.86 (LVP)

FXX
WT
2.43 (FAE)

E22G
2.99 (FAG)

E22K
2.79 (FAK)

E22Q
2.67 (FAQ)

A21G
1.31 (FGE)

This was shown with the wild type tripeptide LVF and the tripeptide LVP from the F19P mutant. A mutation in the antepenultimate position changed the average pulse width when sequencing L from 3.26 seconds to 1.86 seconds. Likewise, the pulse width for the FAE tripeptide in the wild type changed from an average pulse width of 2.43 seconds to between 1.31 and 2.99 seconds for the mutants. Each change in pulse width provided a hint of change, and each amino acid was potentially interrogated three times when it was at the antepenultimate, penultimate, and N-terminal position. Integration of each piece of evidence can further improve the detection of mutations and PTMs.

This example demonstrates the ability to leverage aspects of the technology described herein to detect single amino acid changes known to be linked to disease progression and severity in β-amyloid. The ease of use and benchtop form factor make the technology described herein available to any lab to leverage in the analysis of other protein families to address a range of important questions related to cell and tissue function in regular and disease scenarios.

Example 8
Using Kinetic Signature Approach to Differentiate Disease-Relevant Peptides

This example demonstrates use of the kinetic signature approach to differentiate citrullinated and non-citrullinated peptide fragments of vimentin protein. The presence of citrullinated vimentin in a sample from a subject (e.g., a human subject) may indicate that the subject has rheumatoid arthritis and/or a cancer.

In this example, two peptide fragments of vimentin, QP706 and QP1073, were obtained. The sequences of QP706 and QP1073 are shown in Table 3 (where Cit indicates citrulline). The two sequences are identical except that the arginine residue of QP706 is citrullinated in QP1073.

TABLE 3

Sequences of Vimentin Peptide Fragments

Peptide
SEQ ID NO
Sequence

QP706
841
VRFLEQQNK

QP1073
842
VCitFLEQQNK

Sequencing reactions using the recognizers PS610 (FYW), PS1220 (R), and PS1223 (LIV) were performed separately for the QP706 and QP1073 peptide fragments. Each recognizer was labeled with a unique dye and/or unique number of dyes. A scatter plot of bin ratio v. pulse duration is shown for the QP706 peptide fragment in FIG. 18A and for the QP1073 peptide fragment in FIG. 18B. In the plot of FIG. 18A, three clusters corresponding to FLE, LEQ, and RFL segments are visible. The presence of these three clusters indicates that PS610 recognized the phenylalanine (F) residue, PS1223 recognized the leucine (L) residue, and PS1220 recognized the arginine (R) residue of QP706. In the plot of FIG. 18B, two clusters corresponding to FLE and LEQ segments are visible, but there is no cluster corresponding to RFL. This indicates that PS1220, which recognized the arginine (R) residue of QP706, did not recognize citrulline.

Results from additional sequencing reactions performed using the recognizers PS610 (FYW), PS1220 (R), and PS1223 (LIV) and the QP706 and QP1073 peptide fragments are shown in FIGS. 19A-19D and 20A-20D. Traces from the QP706 reactions are shown in FIGS. 19A-19B, and corresponding scatter plots of intensity v. bin ratio are shown in FIGS. 19C-19D. The traces shown in FIGS. 19A and 19B include recognition segments corresponding to arginine (R), phenylalanine (F), and leucine (L), and each of the plots of FIGS. 19C and 19D shows three separate clusters corresponding to PS610, PS1220, and PS1223. These results demonstrate recognition of the arginine (R) residue by PS1220, recognition of the phenylalanine (F) residue by PS610, and recognition of the leucine (L) residue by PS1223 for the QP706 peptide fragment. Traces from the QP1073 reactions are shown in FIGS. 20A-20B, and the corresponding scatter plots of intensity v. bin ratio are shown in FIGS. 20C-20D. The traces shown in FIGS. 20A and 20B include recognition segments corresponding to phenylalanine (F) and leucine (L) but do not include any recognition segments corresponding to arginine (R). Similarly, each of the plots of FIGS. 20C and 20D shows two separate clusters corresponding to PS610 and PS1223 but does not show a cluster corresponding to PS1220. These results demonstrate that PS1220 does not recognize the citrulline residue of the QP1073 peptide fragment.

Thus, the results of this example suggest that the absence of signal pulses from an arginine recognizer (e.g., PS1220) in a reaction with a peptide expected to contain arginine may indicate the presence of citrulline (i.e., citrullination of an arginine residue). These results demonstrate the ability to discriminate between unmodified and post-translationally modified arginine residues based on the absence of pulses from arginine recognizers. As demonstrated in this example, this ability to discriminate between unmodified and post-translationally modified arginine residues may be used to detect a disease-relevant peptide, such as a fragment of citrullinated vimentin. Detection of the disease-relevant peptide may be used as a clinical diagnostic tool to diagnose a disease, such as rheumatoid arthritis and/or a cancer, in a subject from which the disease-relevant peptide was obtained.

Example 9
Pulsing Characterization of Citrulline-Containing Peptides

This example demonstrates that signal pulse characteristics (e.g., pulse width) associated with recognition of an N-terminal acid of a peptide may be affected by the presence of a penultimate citrulline residue. In this example, sequencing reactions were conducted for 4 pairs of unmodified and citrullinated peptides: QP1028 & QP1029, QP1030 & QP1031, QP1032 & QP1033, and QP707 & QP789. The sequences of each peptide are shown in Table 4. The sequences of each pair of peptides were identical except that one peptide had an unmodified arginine residue and one peptide had a corresponding citrulline residue. For the QP1028 & QP1029 and QP1030 & QP1031 pairs, sequencing reactions were conducted using the PS610 (FYW) recognizer. For the QP1032 & QP1033 and QP707 & QP789 pairs, sequencing reactions were conducted using the PS1223 (LIV) recognizer.

Pulse widths associated with recognition of the N-terminal amino acid of each peptide are shown in Table 4. In each pair of peptides, an N-terminal amino acid (X) was followed by either unmodified arginine (X-R) or citrulline (X-Cit). Table 4 shows that presence of a citrulline residue in the penultimate position (i.e., immediately adjacent to the N-terminal amino acid) may affect (e.g., increase) pulse width. For example, Table 4 shows that the pulse width associated with recognition of phenylalanine (F) followed by unmodified arginine (R) in QP1028 was 4.94 seconds, while the pulse width associated with recognition of phenylalanine (F) followed by citrulline (Cit) in QP1029 was 5.24 seconds. Similarly, Table 4 shows that the pulse width associated with recognition of tyrosine (Y) followed by unmodified arginine (R) in QP1030 was 0.77 seconds, while the pulse width associated with recognition of tyrosine (Y) followed by citrulline (Cit) in QP1031 was 1.12 seconds. As shown in Table 4, it was found that the pulse width was longer for an N-terminal amino acid followed by citrulline compared to an N-terminal amino acid followed by an unmodified arginine. This trend was observed for both PS610 and PS1223. Thus, these results demonstrate the ability to discriminate between peptides containing unmodified arginine and citrulline residues based on pulse width associated with recognition of the immediately upstream amino acid. These results also demonstrate that recognizers provide information concerning the presence and configuration of residues beyond the subset of terminal amino acids with which the recognizers are associated. For example, PS610 (associated with N-terminal FYW) and PS1223 (associated with N-terminal LIV), which are not recognizers for N-terminal arginine, nonetheless exhibit binding kinetics that provide valuable information about arginine (modified or unmodified) when arginine is situated adjacent to the N-terminal end of a peptide.

TABLE 4

Pulse Widths of

Unmodified and Citrullinated Peptides

SEQ

Recog-
Pulse

Peptide
ID NO
Sequence
nizer
Width(s)

QP1028
845
FRLAFAYPDDDK
PS610
4.94

QP1029
846
FCitLAFAYPDDDK
PS610
5.24

QP1030
847
YRIAFAYPDDDK
PS610
0.77

QP1031
848
YCitIAFAYPDDDK
PS610
1.12

QP1032
849
IRLAFAYPDDDK
PS1223
0.58

QP1033
850
ICitLAFAYPDDDK
PS1223
0.84

QP707
817
LRLAFAYPDDDK
PS1223
0.42

QP789
839
LCitLAFAYPDDDK
PS1223
0.92

Example 10
Kinetic Differential Between ADMA and Arginine

This example demonstrates that signal pulse characteristics (e.g., pulse width, recognition segment duration) may be affected by modification of an arginine residue to asymmetric dimethyl arginine (ADMA). In this example, sequencing reactions were performed using PS621 (R), PS610 (FYW), and PS961 (LIV) recognizers for 9 pairs of peptides. Each pair comprised one peptide comprising an unmodified arginine residue followed by a non-arginine amino acid (referred to as an R-X peptide) and one peptide having an identical sequence except that the unmodified arginine was modified to be ADMA (referred to as an ADMA-X peptide). The sequences of the R-X and ADMA-X peptides are shown in Table 5.

TABLE 5

Sequences of ADMA and Unmodified Arginine Peptides

Peptide
SEQ ID NO
Sequence

QP707
817
LRLAFAYPDDDK

QP729
910

LR_ADMALAFAYPDDDK

QP749
911

LRIAFAYPDDDK

QP745
912

LR_ADMAIAFAYPDDDK

QP746
913

LRYAFAYPDDDK

QP742
914

LR_ADMAYAFAYPDDDK

QP748
915

LRSAFAYPDDDK

QP744
916

LR_ADMASAFAYPDDDK

QP747
917

LRAAFAYPDDDK

QP743
918

LR_ADMAAAFAYPDDDK

QP938
919

LREAFAYPDDDK

QP939
920

LR_ADMAEAFAYPDDDK

QP942
921

LRTAFAYPDDDK

QP945
922

LR_ADMATAFAYPDDDK

QP941
923

LRQAFAYPDDDK

QP944
924

LR_ADMAQAFAYPDDDK

QP943
925

LRVAFAYPDDDK

QP946
926

LR_ADMAVAFAYPDDDK

Pulse widths and RS durations for R-X and ADMA-X peptides were obtained. For each peptide, pulse width and RS duration values were obtained by averaging results from 10 sequencing reactions. Table 6 shows the identity of X for each pair of peptides, along with the corresponding pulse width and RS duration values. As shown in Table 6, pulse widths were longer for almost all ADMA-X peptides relative to corresponding R-X peptides. In almost all cases where the pulse width of the R-X peptide was short (e.g. less than 0.12 s or 0.06 s), the pulse width of the corresponding ADMA-X peptide was longer. Additionally, RS durations were longer for ADMA-X peptides relative to corresponding R-X peptides. These results suggest that ADMA may be a better binder (e.g., bind more strongly to an arginine recognizer) than unmodified arginine, and they demonstrate the ability to discriminate between peptides comprising unmodified arginine and ADMA.

TABLE 6

Kinetic Information for Peptides Comprising ADMA or

Unmodified Arginine

PW of
PW of
RS R-X
RS ADMA-

Peptide Pairs
X
R-X (s)
ADMA-X (s)
(min)
X (min)

QP707/QP729
L
0.47
0.48
17.3
48.5

QP749/QP745
I
0.28
0.32
15.4
46.9

QP746/QP742
Y
0.18
0.25
9.6
39.2

QP748/QP744
S
<0.12
0.55
—
—

QP747/QP743
A
<0.12
0.19
—
—

QP938/QP939
E
<0.06
0.34
—
—

QP942/QP945
T
<0.06
<0.06
—
—

QP941/QP944
Q
<0.06
0.21
—
—

QP943/QP946
V
0.41
0.32
25.5
33.8

Example 11
Protein Identification Via Next-Generation Protein Sequencing and Proteome-Wide Mapping

In this example, proteins were sequenced using real-time dynamic sequencing. Briefly, proteins were digested into peptide fragments and conjugated to macromolecular linkers. The conjugated peptides were then immobilized on a semiconductor chip with exposed N-termini for sequencing. Dye-labeled recognizers bound on and off to N-terminal amino acids (NAAs), generating pulsing patterns with characteristic fluorescence and kinetic properties. Aminopeptidases in solution sequentially removed individual NAAs to expose subsequent amino acids for recognition. Fluorescence lifetime, intensity, and kinetic data were collected in real time and analyzed to determine amino acid sequence. The sequencing profiles of peptides were visualized as kinetic signature plots—simplified trace-like representations of the time course of complete peptide sequencing containing the median pulse duration (PD) for each RS and the average duration of each RS and non-recognition segment (NRS).

A kinetic model that accurately predicts the PD for every possible 4-amino-acid sequence that starts with an N-terminal recognizer target was developed. The kinetic model allowed prediction of the kinetic signature for every peptide in a protein database of interest, for example the entire human proteome. Analysis software that automatically identified clusters of traces with highly similar patterns and generated an empirical kinetic signature for each cluster was also developed. With the kinetic model and clustering software, empirical kinetic signatures were generated from protein sequencing data and the protein of origin in the proteome was pinpointed by identifying peptides with matching predicted kinetic signatures.

The human protein cerebral dopamine neurotrophic factor (CDNF, 161 amino acids) was used to demonstrate protein identification from sequencing data based on the kinetic model and proteome mapping software. Recombinant CDNF was sequenced using a set of four recognizers—a recognizer recognizing N-terminal arginine (R), a recognizer recognizing N-terminal L, I, and V, a recognizer recognizing F, Y, and W, and PS1259, which recognizes N-terminal glutamine (Q) and asparagine (N) amino acids. This set of four recognizers recognized a total of 9 NAAs. CDNF was digested using the endopeptidase Lys-C and prepared a peptide library for on-chip sequencing. Sequencing analysis indicated that five peptides were expected to be readily observed on-chip because they were predicted to produce informative kinetic signatures with four or more RSs.

TABLE 7

Sequences of CDNF Peptides

Peptide
SEQ ID NO
Sequence

1
851
EFLNRFYK

2
852
SLIDRGVNFSLDTIEK

3
853
ELISFCLDTK

4
854
ENRLCYYLGATK

5
855
TDYVNLIQELAPK

Five main clusters of traces were identified in the sequencing output based on similarity of the pattern and kinetics of recognition using analysis software. The analysis software produced a characteristic kinetic signature summarizing the pattern of recognition and average PD for the traces grouped in each cluster. These kinetic signatures were then used as input into a mapping algorithm to identify potential matches across the entire human proteome. The database of candidate peptides consisted of over 300,000 peptides of 8 or more amino acids in length derived from an in silico digest of the human proteome, representing roughly 20,000 human proteins. FIG. 21A shows the results of proteome-wide mapping. Candidate matching peptides are shown for each cluster, with candidates corresponding to CDNF peptides outlined. The number to the right of each predicted kinetic signature indicates the number of RS s with predicted average PD that were not very close matches to the observed PD, which can be used as a ranking metric.

Each of the 5 kinetic signatures mapped to a set of candidate proteins that included CDNF as a top match or as the only match. Signatures containing 5 or more RSs were particularly successful at pinpointing CDNF, generating sets with 5 or fewer matching candidate proteins. Taken together, these results identified CDNF as the only human protein capable of generating the complete observed sequencing output with extremely high confidence, as shown in FIG. 21B.

In this example, sequencing data was matched with the human proteome for protein identification. It was shown that sequencing data from multiple peptide fragments can be used to generate highly characteristic kinetic signatures and identify a protein by mapping to the human proteome based on the predicted kinetic signatures of human peptides. These results demonstrate the ability to identify known or unknown proteins in biological samples via proteome-wide mapping with high accuracy.

EQUIVALENTS AND SCOPE

In the claims articles such as “a,” “an,” and “the” may mean one or more than one unless indicated to the contrary or otherwise evident from the context. Claims or descriptions that include “or” between one or more members of a group are considered satisfied if one, more than one, or all of the group members are present in, employed in, or otherwise relevant to a given product or process unless indicated to the contrary or otherwise evident from the context. The invention includes embodiments in which exactly one member of the group is present in, employed in, or otherwise relevant to a given product or process. The invention includes embodiments in which more than one, or all of the group members are present in, employed in, or otherwise relevant to a given product or process.

Furthermore, the invention encompasses all variations, combinations, and permutations in which one or more limitations, elements, clauses, and descriptive terms from one or more of the listed claims is introduced into another claim. For example, any claim that is dependent on another claim can be modified to include one or more limitations found in any other claim that is dependent on the same base claim. Where elements are presented as lists, e.g., in Markush group format, each subgroup of the elements is also disclosed, and any element(s) can be removed from the group. It should it be understood that, in general, where the invention, or aspects of the invention, is/are referred to as comprising particular elements and/or features, certain embodiments of the invention or aspects of the invention consist, or consist essentially of, such elements and/or features. For purposes of simplicity, those embodiments have not been specifically set forth in haec verba herein.

The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.

As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of” or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.” “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.

In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03. It should be appreciated that embodiments described in this document using an open-ended transitional phrase (e.g., “comprising”) are also contemplated, in alternative embodiments, as “consisting of” and “consisting essentially of” the feature described by the open-ended transitional phrase. For example, if the application describes “a composition comprising A and B,” the application also contemplates the alternative embodiments “a composition consisting of A and B” and “a composition consisting essentially of A and B.”

Where ranges are given, endpoints are included. Furthermore, unless otherwise indicated or otherwise evident from the context and understanding of one of ordinary skill in the art, values that are expressed as ranges can assume any specific value or sub-range within the stated ranges in different embodiments of the invention, to the tenth of the unit of the lower limit of the range, unless the context clearly dictates otherwise.

This application refers to various issued patents, published patent applications, journal articles, and other publications, all of which are incorporated herein by reference. If there is a conflict between any of the incorporated references and the instant specification, the specification shall control. In addition, any particular embodiment of the present invention that falls within the prior art may be explicitly excluded from any one or more of the claims. Because such embodiments are deemed to be known to one of ordinary skill in the art, they may be excluded even if the exclusion is not set forth explicitly herein. Any particular embodiment of the invention can be excluded from any claim, for any reason, whether or not related to the existence of prior art.

Those skilled in the art will recognize or be able to ascertain using no more than routine experimentation many equivalents to the specific embodiments described herein. The scope of the present embodiments described herein is not intended to be limited to the above Description, but rather is as set forth in the appended claims. Those of ordinary skill in the art will appreciate that various changes and modifications to this description may be made without departing from the spirit or scope of the present invention, as defined in the following claims.

The recitation of a listing of chemical groups in any definition of a variable herein includes definitions of that variable as any single group or combination of listed groups. The recitation of an embodiment for a variable herein includes that embodiment as any single embodiment or in combination with any other embodiments or portions thereof. The recitation of an embodiment herein includes that embodiment as any single embodiment or in combination with any other embodiments or portions thereof.

	Number	Date	Country
	63395325	Aug 2022	US
	63293054	Dec 2021	US

COMPOSITIONS AND METHODS FOR POLYPEPTIDE ANALYSIS

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