Patent Application
20120142623
The present invention relates generally to methods for predicting inhibitors of protein targets related to treatment of disease, for example, infectious disease, bacterial, viral, or parasitic diseases, or neoplastic disease. The invention further relates to methods for treatment of disease and to methods for predicting inhibitors of protein targets related to treatment of disease, for example, infectious disease, bacterial, viral, or parasitic diseases, or neoplastic disease, utilizing a docking with dynamics protocol to identify inhibitors, or utilizing a protein structure energy function to identify peptide or peptidomimetic inhibitors.
Current therapeutic strategies for several diseases, such as Human Immunodeficiency Virus Type 1 (HIV-1) infection, have evolved from initial single target therapies to multitarget ones [1]. Single antiretroviral drug regimens against HIV-1 are no longer recommended for clinical use due to the rapid emergence of drug resistant strains after initiation of therapy [2, 3]. A combination of antiretroviral drugs targeting different viral proteins is more effective at suppressing viral growth [4]. However, for many patients, these regimens are expensive, result in greater toxicity, and poor patient adherence [5-7]. New paradigms in multitarget drug discovery have emerged [8-11], particularly for the treatment of HIV-1 infection [12, 13]. An example of a new multitarget antiretroviral drug is Cosalane, developed to inhibit multiple HIV-1 proteins (gp120, integrase, protease, and reverse transcriptase) simultaneously [14-19].
Computational screening of small molecule chemical compounds against protein targets implicated in disease has been widely used to discover lead inhibitors against diseases of interest. This process typically involves “docking” chemical compounds into the active site of the three dimensional (3D) structure of a protein target by computer simulation to identify putative leads based on calculated binding affinities of the compounds to the target. Since the number of high resolution protein structures and computer processing capabilities have increased exponentially in recent years, computational screening methods have complemented experimental high throughput screening (HTS) methods to improve the efficiency and efficacy of discovering lead inhibitors.
Malaria is one of the deadliest tropical diseases, causing more than 300 million infections yearly. Successful clearance of the malarial parasites, Plasmodium sp, from a patient's body by antimalarial drugs is impeded by the emergence of drug resistant strains. Drugs that effectively eliminate Plasmodium require short exposure durations, which reduce risk of treatment failure and emergence of drug resistant strains. Baird, N Engl J Med 352: 1565-1577, 2005.
Antimalarial drugs currently target single Plasmodium proteins. Effective therapeutic regimens require a combination of drugs that have different mechanisms of action during the same stage of the parasite's life cycle. Baird, N Engl J Med 352: 1565-1577, 2005. However, malaria is a disease that occurs mostly in tropical and subtropical areas where patients have limited access to drugs, and combination drug regimens may not succeed due to poor adherence. Fungladda, et al., Bull World Health Organ 76 Suppl 1: 59-66, 1998. New antimalarial therapies that include multi-target drugs, which are currently being used extensively to treat both infectious and inherited diseases, may have higher efficacy than single target drugs and provide a simpler regimen for antimalarial therapy. Csermely et al., Trends Pharmacol Sci 26:178-182, 2005; Ravi Chandra et al., Protein Eng Des Sel 17: 175-182, 2004.
Drug resistance is a major concern in patients treated for HIV infection and a major reason for treatment failure. There is no evidence that people infected with HIV can be cured by the currently available therapies. In fact, individuals who are treated for up to three years and are repeatedly found to have no virus in their blood experience a prompt rebound increase in the number of viral particles when therapy is discontinued. This resistance then limits the options for future treatment. A major reason that resistance develops is the patient's failure to correctly follow the prescribed treatment, such as not taking the medications at the correct time. In addition, the likelihood of suppressing the virus to undetectable levels is not as good for patients with lower CD4 cell counts and higher viral loads. Finally, if virus remains detectable on any given regimen, resistance eventually will develop.
Glycoprotein 41 (gp41) is a crucial molecule in the human immunodeficiency virus type 1 (HIV-1) envelope and is a drug target for treatment of HIV disease. Gp41 consists of four major parts: a N-terminal hydrophobic fusion peptide, a cysteine loop, and heptad repeats 1 & 2 (HR1 & 2). Enfuvirtide is the first approved peptide-based HIV-1 fusion inhibitor. It corresponds to amino acid residues 127-162 of HIV-1 gp41 (part of the HR2 domain) or residues 643-678 in the gp160 precursor of the HIV envelope glycoprotein. The inhibitor competes with the viral HR2 in binding to the HR1 trimeric coiled-coil hydrophobic groove, thereby blocking viral HR1/HR2 association. Wild et al., Proc Natl Acad Sci USA 89: 10537-10541, 1992; Jiang et al., Nature 365: 113, 1993; Wild et al., AIDS Res Hum Retroviruses 9: 1051-1053, 1993; Wild et al., Proc Natl Acad Sci USA 91: 9770-9774, 1994. Mutations of HR1 residues at the hydrophobic groove (G36, V38, Q40, N42, N43 and L45) have been reported to cause enfuvirtide resistance. Roman et al., J Acquir Immune Defic Syndr 33: 134-139, 2003; Marcelin et al., AIDS 18: 1340-1342, 2004; Wei et al., Antimicrob Agents Chemother 46: 1896-1905, 2002. Although HIV-1 strains with these HR1 mutations can escape from enfuvirtide, these strains are significantly less fit than the wild-type. Wei et al., Antimicrob Agents Chemother 46: 1896-1905, 2002; Lu et al., J Virol 78: 4628-4637, 2004; Menzo et al., Antimicrob Agents Chemother 48: 3253-3259, 2004. It is unclear how viral HR1 and HR2 mutations reduce the effectiveness of the enfuvirtide and whether these mutations subsequently restore viral fitness.
A need exists in the art for more effective treatments for microbial infectious disease, e.g., bacterial, viral, or parasitic disease, such as malaria, HIV, and herpesvirus infection. Single drug treatment against multiple targets within a disease-causing organism would improve compliance with drug treatment protocols, decrease the appearance of drug resistant strains, and decrease morbidity and mortality as a result of the bacterial, viral, or parasitic disease.
The invention provides a method for predicting inhibitors of one or more protein targets for treatment of disease, such as infectious disease or neoplastic disease, utilizing a docking with dynamics protocol to identify multi-target inhibitors useful in the treatment of infectious disease. The disease states can be, for example, infectious disease, bacterial, viral, or parasitic diseases, or neoplastic disease. The invention further provides a method for identifying candidate peptide inhibitors or candidate peptidomimetic inhibitors utilizing a peptide-based inhibitor discovery method using protein structure energy function analysis. The invention further provides a method for predicting inhibitors of one or more protein targets for treatment of one or more diseases, by calculating a binding affinity, for example, using a docking with dynamics protocol, for one or more compounds against one or more protein targets, and predicting high-ranking binding compounds as inhibitors of the one or more protein target for treatment of the one or more diseases. Pharmaceutical compositions are provided for the treatment of a broad spectrum of disease states, for example, infectious disease, bacterial, viral, or parasitic diseases, or neoplastic disease, wherein the therapeutic applications for these compositions have not been previously identified.
A method for predicting inhibitors of one or more protein targets for treatment of one or more diseases is provided which comprises providing a set of experimentally-synthesized or naturally-occurring compounds, clustering the compounds by structural similarity, calculating a binding affinity for one or more compounds representing each structurally similar cluster against one or more protein targets, ranking each representative compound by inhibitory concentration based upon calculation of binding affinity against each of the one or more protein targets for the disease or the disease-causing organism, selecting one or more high-ranking clusters of compounds, ranking compounds within the one or more high-ranking clusters based upon calculation of binding affinity against each of the one or more protein targets for the disease, and predicting high-ranking compounds as inhibitors of one or more protein target for treatment of the one or more diseases. The set of experimentally-synthesized or naturally-occurring compounds can be compounds that have been screened for one or more of toxicity, absorption, distribution, metabolism excretion, or pharmacokinetics. The set of experimentally-synthesized or naturally-occurring compounds that have been approved by the U.S. Food and Drug Administration. In a further aspect, the method comprises calculating the binding affinity using a docking with dynamics protocol. In a further aspect, the method comprises comprising ranking each compound by inhibitory concentration against two or more protein targets for treatment of the disease. In a further aspect, the method comprises ranking each compound by inhibitory concentration against the protein target for treatment of two or more diseases. In a further aspect, the method comprises predicting the inhibitor for treatment of disease using the lowest inhibitory concentration to calculate the highest binding affinity. In a further aspect, the method comprises reducing the screening time to predict inhibitors of one or more protein target for treatment of disease. The disease includes, but is not limited to, bacterial disease, viral disease, parasitic disease, or neoplastic disease.
A method for predicting inhibitors of two or more protein targets for treatment of one or more disease in a mammalian subject is provided which comprises providing a set of experimentally-synthesized or naturally-occurring drug or drug-like compounds, calculating a binding affinity using a docking with dynamics protocol for one or more compounds against two or more protein targets, ranking compounds by inhibitory concentration based upon calculation of binding affinity against each of the two or more protein targets for the disease or a disease-causing organism, and predicting high-ranking compounds as inhibitors of two or more protein target for treatment of the one or more diseases. The set of experimentally-synthesized or naturally-occurring compounds can be compounds that have been screened for one or more of toxicity, absorption, distribution, metabolism excretion, or pharmacokinetics. The method can further comprise predicting the inhibitor for treatment of disease using the lowest inhibitory concentration to calculate the highest binding affinity. The set of experimentally-synthesized or naturally-occurring compounds that have been approved by the U.S. Food and Drug Administration. The disease includes, but is not limited to, bacterial disease, viral disease, parasitic disease, or neoplastic disease.
A computer readable medium bearing computer executable instructions is provided for carrying out the method for predicting inhibitors of one or more protein targets for treatment of one or more diseases. A modulated data signal carrying computer executable instructions for performing the method is provided. At least one computing device comprising means for performing the method is provided.
A method for treating herpesvirus infection in a mammalian subject is provided which comprises administering to the mammalian subject a pharmaceutical composition in an amount effective to reduce or eliminate infection by two or more classes or species of herpesvirus or to prevent its occurrence or recurrence in the mammalian subject. The class of herpesvirus includes, but is not limited to, α-herpesvirus, β-herpesvirus, or γ-herpesvirus. In a further aspect, the species of herpesvirus is herpes simplex virus, cytomegalovirus, Kaposi's sarcoma virus, varicella zoster virus, or Epstein Barr virus.
In an embodiment, the composition is an inhibitor of a herpesvirus protease. In a detailed aspect, the composition comprises meso-5,10,15,20-Tetrakis-(N-methyl-4-pyridyl)porphine tetratosylate (TMPyP4).
A method for treating Plasmodium falciparum infection in a mammalian subject is provided which comprises administering to the mammalian subject a pharmaceutical composition capable of inhibiting two or more Plasmodium falciparum target proteins, in an amount effective to reduce or eliminate the Plasmodium falciparum infection or to prevent its occurrence or recurrence in the mammalian subject. In one aspect, the pharmaceutical composition includes, but is not limited to, KN62 (ID 274), u-74389g 2321), daunorubicin (ID 1989), nitrotetrazolium bt (ID 2174), STI-571/Imatinib (ID 637), or TMPyP4 (ID 2303). In a further aspect, the pharmaceutical composition is a telomerase inhibitor including, but is not limited to, v (ID 2288), bisindolylmaleimide iii (ID 546), methylgene—05 (ID 463), remiszewski—013 (ID 449), remiszewski—010 (ID 448), phthalylsulfathiazole (ID 1576), or sulfaphenazole (ID 916).
A method for treating human immunodeficiency virus infection in a mammalian subject is provided which comprises administering to the mammalian subject a pharmaceutical composition comprising an inhibitor of HIV integrase in an amount effective to reduce or eliminate infection by human immunodeficiency virus or to prevent its occurrence or recurrence in the mammalian subject. The HIV integrase inhibitor includes, but is not limited to, TMPyP4, calmidazolium chloride, paromomycin, aurintricarboxylic acid, ro 31-8220 (548), dichlorobenzamil (36), catenulin (1198), kanamycin (670), or capreomycin (893).
A method for treating microbial infection in a mammalian subject is provided which comprises administering to the mammalian subject a pharmaceutical composition comprising meso-5,10,15,20-Tetrakis-(N-methyl-4-pyridyl)porphine tetratosylate (TMPyP4) in an amount effective to reduce or eliminate the microbial infection or to prevent its occurrence or recurrence in the mammalian subject. The method treats microbial infection including, but not limited to, a viral infection, bacterial infection, or parasitic infection. In a further aspect, the method treats microbial infection including, but not limited to, herpesvirus, human immunodeficiency virus, or Plasmodium falciparum.
A method for identifying a candidate peptide inhibitor or candidate peptidomimetic inhibitor of a protein target for treatment of disease is provided which comprises performing a stability analysis using a protein structure energy function to identify highly stable, partially surface-exposed elements of the protein target, designing peptide inhibitors or peptidomimetic inhibitors having the same amino acid sequence as the highly stable elements or having amino acid sequences that interacts with the highly stable element, designing derivative inhibitors by computationally mutating side chains of the peptide inhibitors or peptidomimetic inhibitors and evaluating the protein structure energy of the derivative inhibitors, and identifying the derivative inhibitor with a lower protein structure energy as the candidate peptide inhibitor of the protein target or the candidate peptidomimetic inhibitor of the protein target for treatment of disease. In one aspect, the method further comprises identifying derivative inhibitors as candidate peptide inhibitors or candidate peptidomimetic inhibitors of two or more highly stable elements in one protein target. In a further aspect, the candidate peptide inhibitors or candidate peptidomimetic inhibitors target one or more diseases. In another aspect, the method further comprises identifying the candidate peptide inhibitor or the candidate peptidomimetic inhibitor of homologous highly stable elements in two or more protein targets. In a further aspect, the candidate peptide inhibitor or the candidate peptidomimetic inhibitor target one or more diseases. In a detailed aspect, the highly stable element is a secondary structure element, a tertiary structure element, or a quaternary structure element. In a further aspect, the disease is bacterial disease, viral disease, parasitic disease, or neoplastic disease. A computer readable medium bearing computer executable instructions is provided for carrying out the method for identifying a candidate peptide inhibitor or candidate peptidomimetic inhibitor of a protein target for treatment of disease. A modulated data signal carrying computer executable instructions for performing the method is provided. At least one computing device comprising means for performing the method is provided.
A method for predicting inhibitors of two or more protein targets for treatment of one or more diseases is provided which comprises providing a set of experimentally-synthesized or naturally-occurring compounds, calculating a binding affinity for each compound against a multiplicity of protein targets, and ranking each compound by inhibitory concentration based upon calculation of binding affinity against each of the one or more protein targets for treatment of disease. In one aspect, the set of experimentally-synthesized or naturally-occurring compounds are FDA approved compounds. In a further aspect, the method comprises calculating the binding affinity using a docking with dynamics protocol. In a further aspect, the method comprises ranking each compound by inhibitory concentration against two or more protein targets for treatment of disease. In a further aspect, the method comprises ranking each compound by inhibitory concentration against the protein target for treatment of two or more diseases. In a further aspect, the method comprises predicting the inhibitor for treatment of disease by calculating the highest binding affinity. In a detailed aspect, the disease includes, but is not limited to, bacterial disease, viral disease, parasitic disease, or neoplastic disease. A computer readable medium bearing computer executable instructions is provided for carrying out the method for predicting inhibitors of two or more protein targets for treatment of one or more diseases. A modulated data signal carrying computer executable instructions for performing the method is provided. At least one computing device comprising means for performing the method is provided.
The invention provides a method for predicting inhibitors of one or more protein targets for treatment of disease, for example, infectious disease, bacterial, viral, or parasitic diseases, or neoplastic disease, utilizing a docking with dynamics protocol to identify multi-target inhibitors useful in the treatment of infectious disease. The invention further provides a method for identifying candidate peptide inhibitors or candidate peptidomimetic inhibitors utilizing a peptide-based inhibitor discovery method using protein structure energy function analysis. The candidate small chemical molecule inhibitors, peptide inhibitors, or peptidomimetic inhibitors can be further tested by in vitro cell assay or in an animal model and further determined to be effective to inhibit virus, bacteria, or parasite replication, and useful to reduce or eliminate infectious disease or to prevent its occurrence or recurrence in the vertebrate or mammalian subject. The candidate small chemical molecule inhibitors, peptide inhibitors, or peptidomimetic inhibitors can be further tested by in vitro cell assay or in an animal model and further determined to be effective against replication of neoplastic cells, and useful to reduce or eliminate neoplastic disease or to prevent its occurrence or recurrence in the vertebrate or mammalian subject.
Studies have shown that the success rates of HTS are increased by several fold when compounds were prefiltered by computational screening [20-22]. Here, we present a new computational paradigm for inhibitor discovery that is based on a combination of three factors: (1) Incorporation of dynamics of protein side chains and main chain during the docking process to more accurately evaluate binding affinities. (2) Selection of single inhibitors that bind to multiple protein targets simultaneously. (3) Using a screening library consisting of drug and drug-like compounds.
We compare the efficacy of lead compound identification by our multitarget computational screening approach to the traditional experimental HTS and single target screening approaches (
Computational Multitarget Screening for Diseases Caused by Multiple Microorganisms: HIV-1 and Opportunistic Pathogen Infections
Traditionally, treatment of complex diseases involving several microorganisms, especially those with a high mutation rate, requires the use multiple drugs in the therapeutic regimen, where each drug inhibits a single target in a particular microorganism. Multiple drug regimens have successfully been used in several studies to treat complex diseases and to control emergence of drug resistant strains of infectious agents [1, 4]. However, since several drugs are used in treatment regimens, this typically causes serious adverse effects and is associated with low patient adherence due to toxicity and high costs [5-7].
HIV-1, first discovered in 1981, is a pandemic human pathogen that has resulted in more than 25 million deaths caused by the Acquired Immune Deficiency Syndrome (AIDS) where the immune system ceases to function, leading to life threatening opportunistic infections. HIV-1 infected patients need to take a regimen consisting of drugs to treat both HIV-1 and opportunistic infections that arise due to immunosuppression. These patients thus present a therapeutic challenge where multitarget computational screening can provide an effective solution, since a therapeutic regimen consisting of a single drug that could simultaneously inhibit targets from multiple microorganisms would be ideal for the treatment and control of complex infectious disease combinations present these patients.
There are several HIV-related opportunistic pathogens (Table 1) that are inhibited using prophylactics [23]. Cotrimoxazole is a broad spectrum antibiotic that is effective at preventing a number of opportunistic infections. This drug is both cheap and widely available [24]. However, cotrimoxazole does not inhibit HIV-1 replication. Since HIV-1 infection is a chronic disease that requires life long antiretroviral treatment, a new generation of antiretroviral drugs simultaneously control HIV-1 and opportunistic pathogens would benefit HIV-1 patients, especially those with limited access to antiretroviral and prophylactic drugs.
Several drugs approved for treatment of human diseases other than HIV-1 infection have been shown to inhibit HIV-1 proteins (Table 2). These include drugs Alzheimer's disease, cancer, and infectious diseases caused by bacteria, fungi, protozoa, and viruses including HIV-1. The multitargeting features of these drugs against HIV-1 and its opportunistic pathogens were largely identified by HTS through serendipity. However, computational multitarget screening using the x-ray diffraction structures of HIV-1 protein targets from the Protein Data Bank (PDB; http://www.pdb.org) would have helped enable rational identification of these multitarget drugs.
Aspergillus fumigatus
Candida albicans
Candida krusei
Candida parapsilosis
Candida tropicalis
Cryptococcus neoformans
Fusarium species
Histoplasma capsulatum
Cryptococcus neoformans
Mycobacterium tuberculosis
Plasmodium berghei
Plasmodium falciparum
Candida albicans
Cryptococcus neoformans
Cryptosporidium parvum
Toxoplasma gondii
Aspergillus fumigatus
Candida albicans
Cryptococcus neoformans
Histoplasma capsulatum
Encephalitozoon cuniculi
Encephalitozoon intestinalis
Enterocytozoon bieneusi
Plasmodium falciparum
Vittaforma corneae
Plasmodium falciparum
Plasmodium falciparum
Cryptosporidium parvum
Enterococcus faecalis
Enterococcus faecium
Mycobacterium fortuitum
Mycobacterium tuberculosis
Mycoplasma pneumoniae
Staphylococcus aureus
Staphylococcus pyogenes
Streptococcus pneumoniae
Toxoplasma gondii
The data presented in Table 2 provides evidence for single drugs (or a combination of 2-3 drugs) that can inhibit infection by multiple bacteria, fungi, protozoa, and viruses, including HIV-1, simultaneously. A striking example is the inhibitor KNI-764/JE-2164 (row 9, Table 2) that inhibits both HIV-1 protease and the plasmepsin enzyme target from the malarial parasite Plasmodium malariae, the complexes of which have both been solved by x-ray diffraction (PDB identifiers 1msm and 2anl, respectively). Another example is minocycline (row 9, Table 2), a broad spectrum antibiotic that has been shown to possess inhibitory activity against HIV-1 in vitro. Our docking simulations predict that it inhibits HIV-1 integrase (Jenwitheesuk and Samudrala, manuscript submitted). The former example provides strong evidence for the existence and utility of multitarget drugs (since the binding mode of a single inhibitor bound to targets from two very different and destructive pathogens has been elucidated to atomic detail). The latter illustrates how computational screening methods can be used to identify targets and binding modes of multitarget inhibitors discovered fortuitously.
Table 2 focuses on drugs for which there is published evidence supporting their simultaneous effectiveness against HIV-1 and associated opportunistic pathogen infections. Below, we illustrate how our computational multitarget screening approach can be used to discover effective inhibitors against the malarial parasite P. falciparum.
Computational Multitarget Screening for Diseases Caused by a Single Microorganism: Plasmodium falciparum
Previous studies using structure-based single target computational screening of two different large compound libraries against two cysteine proteases (falcipain-2 and falcipain-3) of the malarial parasite P. falciparum have shown low success rates [25, 26]. A computational screen using 355,000 compounds from the Available Chemical Directory (ACD) database predicted 100 putative inhibitors, of which only seven demonstrated experimental inhibitory activity in vitro [25]. A second experiment on the same targets using 241,000 compounds from the ChemBridge database predicted 100 putative inhibitors, of which eleven demonstrated experimental inhibitory activity in vitro [26]. The results of these single target computational screening studies not only indicated a low success rate of approximately 10% at identifying P. falciparum inhibitors, but also that this approach was not able to identify potential targets of a given compound since some of the predicted compounds inhibited P. falciparum growth but failed to inhibit the expected targets.
Two recent experimental HTS studies yielded an even lower success rate of approximately 3% for P. falciparum growth inhibition: Chong et al. screened 2,687 drug and drug-like compounds for P. falciparum growth inhibition and found 87 antimalarial compounds with activity ≦10 μM [27]. Weisman et al. similarly screened 2,160 compounds and found 72 antimalarial compounds with >70% growth inhibition relative to control at 1 μM [28].
We previously screened a library of 2,344 drug and drug-like compounds against fourteen P. falciparum proteins [29] (
Experimental verification was performed by adding compounds in serial dilutions to the chloroquine-sensitive strain 3D7 and the chloroquine-resistant strain K1 of P. falciparum cultures. The mean ED50 was determined from at least two or more measurements for each compound. Six of sixteen top predictions had ED50s (≦1 μM against either the 3D7 or K1 strains, and all five negative control compounds did not inhibit 3D7 P. falciparum growth. The overall prediction accuracy was 52% ( 11/21), with a success rate of 38% ( 6/16) at identifying promising lead candidate compounds against chloroquine-sensitive and chloroquine-resistant strains of P. falciparum (Table 3). The success rate (38%) of our multitarget screening approach is a significant improvement over the previous single target computational screening (10%) [25, 26] and HTS (3%) rates [27, 28].
Table 3 footnote. For each compound, the number of proteins predicted to be inhibited, a consensus weighted rank (the average of the ranks of the compound observed in all our simulations divided by the number of proteins predicted to be inhibited by that compound; the lower the rank, the better the predicted efficacy), which is a measure of the multitargeting capability of a compound, and the experimental result for P. falciparum growth inhibition are given. (A) Experimental verification of multitarget compounds predicted to inhibit P. falciparum growth. Of the 21 compounds tested, sixteen compounds were predicted to have high inhibition based on their multitargeting capability, and five compounds were used as a negative control. All computational predictions were repeated in triplicate with randomized starting positions for the simulations. Experimental verification was performed by adding compounds in serial dilutions to the chloroquine-sensitive strain 3D7 and the chloroquine-resistant strain K1 of P. falciparum cultures. The mean effective dose where 50% of P. falciparum growth was inhibited (ED50) was determined from at least two or more measurements for each compound. Six of sixteen top predictions had ED50s ≦1 μM against either the 3D7 or K1 strains, and all five negative control compounds did not inhibit 3D7 P. falciparum growth. Our overall prediction accuracy is 52% ( 11/21), with a success rate of 38% ( 6/16) at identifying promising lead inhibitors against chloroquine-sensitive and chloroquine-resistant strains of P. falciparum. (B) Experimental verification of compounds predicted to inhibit P. falciparum growth based on the experimental high throughput screening studies. Chong et al. screened 2,687 compounds for P. falciparum growth inhibition and found 87 antimalarial compounds with activity ≦10 μM [27]. Weisman et al. tested 2,160 compounds and found 72 antimalarial compounds with >70% growth inhibition relative to control at 1 μM [28]. The thirteen unique compounds listed from the two sets (dihydroergotamine is repeated) were selected from 73 and 15 overlapping compounds that we had screened computationally for which experimental data were provided. These compounds would have been predicted by us to inhibit P. falciparum growth based on their multitargeting capability (i.e., low consensus weighted rank). All the other compounds that overlapped with the HTS libraries have high consensus weighted ranks, and we hypothesize that any inhibitory activities of these other compounds result from other mechanisms and not by inhibition of the fourteen proteins screened by us. All the thirteen compounds listed are considered antimalarial inhibitors using the criteria of the HTS studies. Using our more stringent criteria of ED50 of ≦1 μM or 95% inhibition at 10 μM would have resulted in a success rate of 54% ( 7/13). The success rates of the multitarget computational screening of 38% (A) and 54% (B) are thus significantly higher than the HTS success rates (3%), and are achieved by screening only sixteen compounds experimentally, at a fraction of the time, effort, and cost that would have been required to perform experimental HTS.
Multitarget computational screening may also be applied to predict potential targets of a given inhibitor identified by HTS. This is illustrated in
Toxicity Minimization
Although a multitarget inhibitor is expected to bind to multiple disease protein targets with high affinity, it may undesirably inhibit other human proteins, leading to toxicity. Strategies to identify and predict side effects such as acute toxicity, mutagenicity, and carcinogenicity have been extensively studied and reviewed [32-38].
In terms of computational screening, a library of approved drug and drug-like compounds being evaluated in clinical trials or those with known toxicity profiles may be used to identify initial lead inhibitors, thereby reducing the likelihood of deleterious side effects. Additional compounds may be selected from larger libraries containing synthetic and natural compounds, where the entire library is filtered and categorized into groups according to their onset and severity of toxicity. This can be accomplished by using data in the TOXNET database (http://toxnet.nlm.nih.gov) [39] or examining their Absorption Distribution Metabolism Elimination Toxicity (ADME-Tox) profiles [40]. Focusing on infectious disease targets that are not similar to essential proteins in humans also reduces the likelihood of a toxic reaction.
Toxicity filtering may also be done by structural similarity comparison or SMILES strings similarity search [41] between successful lead candidates and compounds with known toxicity profiles. The purpose of categorizing compounds is to prioritize the experimental verification of the computational screening results for a given set of targets or diseases. Compounds with moderate toxicity may be included in our screening library for diseases that require short courses of treatment. On the other hand, compounds with a moderate degree of toxicity may be eliminated from our library for chronic diseases.
Potential side effects may also be predicted using computational multitarget screening lead inhibitors against essential human proteins with known structure. Lead inhibitors can also be screened against proteins involved in human drug metabolism (such as the Cytochrome P450 family of enzymes) to ensure their proper metabolism and minimize the risk of producing toxic metabolites.
Efficacy and Efficiency of Multitarget Computational Screening
Multitarget computational screening using a docking with dynamics protocol and drug-like compound library has the promise to significantly enhance the identification of lead inhibitors for drug development. This protocol identifies inhibitors that simultaneously and selectively bind to multiple targets with high affinity, in contrast to most drug development strategies that focus only on single target inhibition. The efficacy and efficiency of multitarget computational screening has the potential to significantly reduce time, effort, and cost to obtain promising lead candidates for drug development.
The present study provides evidence that multitarget inhibitors exist for complex diseases involving several microorganisms such as HIV-1 and associated opportunistic pathogen infections, and that these lead compounds are excellent starting points for further chemical modification to improve potency and specificity against targets of interest. We also demonstrate that computationally predicted multitarget antimalarial inhibitors show high potency at inhibiting P. falciparum growth in vitro, with a higher success rate than single-target computational screening and experimental HTS. Onset of drug resistance, a significant problem with both HIV-1 and P. falciparum infection, may be significantly delayed by inhibiting multiple targets simultaneously.
An important application of multitarget computational screening is that it may be used to identify potential targets for a drug whose inhibitory mechanism is unknown. Since we start with drug and drug-like compounds that are well characterized in terms of their pharmacological properties, the probability of success as a drug further down the development pipeline is increased. Modification of lead chemical compounds using medicinal chemistry rules can be performed in silico. Side effect screening against essential human proteins can also be performed computationally to refine these candidates, and screening against important human enzymes involved in eliminating drugs from the body may help ensure proper metabolism with nontoxic metabolite buildup. The opinion and evidence presented here is largely in the context of infectious disease targets. However, our computational multitarget approach can be readily extended to other complex human diseases such as cancer, which require inhibition of multiple proteins in developmental pathways to be effective.
Developing a comprehensive computational pipeline that integrates the concepts presented here will not only lead to the discovery of new inhibitors but also has the potential to enable significant advances in the efficacy and efficiency of the entire process of drug discovery and development, from in vitro and in vivo preclinial studies to clinical trials.
The present methods have identified small molecule compounds, small chemical molecule inhibitors, peptide inhibitors, or peptidomimetic inhibitors useful as broad spectrum antimicrobial treatments. For example, the compound TMPyP4 has been identified by methods of the present invention as a candidate inhibitor of herpesvirus replication, and as a candidate therapeutic composition for treatment of a broad spectrum of herpesvirus infectious disease. This compound has been shown by molecular modeling studies to bind to herpesvirus protease and by in vitro studies to inhibit infection and replication of several classes of herpesvirus, e.g., α-herpesvirus, β-herpesvirus, or γ-herpesvirus. The compound TMPyP4 is also a candidate inhibitor of HIV-1 integrase and a therapeutic composition for treatment of human HIV-1 infection. The compound TMPyP4 is a candidate multitarget inhibitor of Plasmodium falciparum proteins and a therapeutic for treatment of Plasmodium falciparum infection.
A method for identifying a candidate peptide inhibitor or candidate peptidomimetic inhibitor of a protein target for treatment of disease is provided which comprises performing a stability analysis using a protein structure energy function to identify highly stable, partially surface-exposed elements of the protein target, designing peptide inhibitors or peptidomimetic inhibitors having the same amino acid sequence as the highly stable elements or having amino acid sequences that interacts with the highly stable element, designing derivative inhibitors by computationally mutating side chains of the peptide inhibitors or peptidomimetic inhibitors and evaluating the protein structure energy of the derivative inhibitors, and identifying the derivative inhibitor with a lower protein structure energy as the candidate peptide inhibitor of the protein target or the candidate peptidomimetic inhibitor of the protein target for treatment of disease.
A method for predicting inhibitors of two or more protein targets for treatment of one or more diseases is provided which comprises providing a set of experimentally-synthesized or naturally-occurring compounds, calculating a binding affinity for each compound against a multiplicity of protein targets, and ranking each compound by inhibitory concentration based upon calculation of binding affinity against each of the one or more protein targets for treatment of disease.
A method for predicting inhibitors of one or more protein targets for treatment of one or more diseases is provided which comprises providing a set of experimentally-synthesized or naturally-occurring compounds, clustering the compounds by structural similarity, calculating a binding affinity for one or more compounds representing each structurally similar cluster against one or more protein targets, ranking each representative compound by inhibitory concentration based upon calculation of binding affinity against each of the one or more protein targets for the disease or the disease-causing organism, selecting one or more high-ranking clusters of compounds, ranking compounds within the one or more high-ranking clusters based upon calculation of binding affinity against each of the one or more protein targets for the disease, and predicting high-ranking compounds as inhibitors of one or more protein target for treatment of the one or more diseases.
“Docking with dynamics” is a computational protocol that predicts the binding mode (configuration) and energy of a small molecule (chemical compound) to a protein structure. This is essentially a combination of two techniques: molecular docking (implemented by the software AutoDock; http://www.scripps.edu/mb/olson/doc/autodock/; Morris, et al., J. Computational Chemistry, 19: 1639-1662, 1998.) and molecular dynamics (implemented by the software NAMD; http://www.ks.uiuc.edu/Research/namd/; Phillips, et al., Journal of Computational Chemistry, 26: 1781-1802, 2005).
Docking with dynamics or docking with dynamics and clustering has been used to predict susceptibility of infectious viruses to drug treatment. Docking with dynamics has been used to predict HIV protease mutant drug binding affinities and to predict HIV protease drug resistance/susceptibility. Jenwitheesuk E, and Samudrala R., Bioorg Med Chem Structural Biology, 3: 2-10, 2003. Jenwitheesuk E, and Samudrala R., Antiviral Therapy 10: 157-166, 2005. Docking with dynamics has been used to predict inhibitors against the SARS coronavirus proteinase. Jenwitheesuk E, and Samudrala R., Bioorg Med Chem Lett. 13: 3989-3992, 2003.
Multi-Target Inhibitor Discovery Using Docking with Dynamics Protocol
“Highly stable element” refers to a secondary, tertiary, or quaternary structural element that is highly stable as measured by techniques known in the art, for example, by RAPDF stability scores of protein structure as described herein.
“Highly stable surface exposed element” refers to highly stable elements that are exposed on the protein surface.
It is to be understood that this invention is not limited to particular methods, reagents, compounds, compositions or biological systems, which can, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting. As used in this specification and the appended claims, the singular forms “a”, “an” and “the” include plural referents unless the content clearly dictates otherwise. Thus, for example, reference to “a cell” includes a combination of two or more cells, and the like.
“About” as used herein when referring to a measurable value such as an amount, a temporal duration, and the like, is meant to encompass variations of ±20% or ±10%, more preferably ±5%, even more preferably ±1%, and still more preferably ±0.1% from the specified value, as such variations are appropriate to perform the disclosed methods.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Although any methods and materials similar or equivalent to those described herein can be used in the practice for testing of the present invention, the preferred materials and methods are described herein. In describing and claiming the present invention, the following terminology will be used.
“Patient”, “subject” or “mammal” are used interchangeably and refer to mammals such as human patients and non-human primates, as well as experimental animals such as rabbits, rats, and mice, and other animals. Animals include all vertebrates, e.g., mammals and non-mammals, such as sheep, dogs, cows, chickens, amphibians, and reptiles.
“Treating” or “treatment” includes the administration of the compositions, compounds or agents of the present invention to prevent or delay the onset of the symptoms, complications, or biochemical indicia of a disease, alleviating or ameliorating the symptoms or arresting or inhibiting further development of the disease, condition, or disorder (e.g., a microbial infectious disease). “Treating” further refers to any indicia of success in the treatment or amelioration or prevention of the disease, condition, or disorder (e.g., a microbial infectious disease), including any objective or subjective parameter such as abatement; remission; diminishing of symptoms or making the disease condition more tolerable to the patient; slowing in the rate of degeneration or decline; or making the final point of degeneration less debilitating. The treatment or amelioration of symptoms can be based on objective or subjective parameters; including the results of an examination by a physician. Accordingly, the term “treating” includes the administration of the compounds or agents of the present invention to prevent or delay, to alleviate, or to arrest or inhibit development of the symptoms or conditions associated with an autoimmune disease. The term “therapeutic effect” refers to the reduction, elimination, or prevention of the disease, symptoms of the disease, or side effects of the disease in the subject. “Treating” or “treatment” using the methods of the present invention includes preventing the onset of symptoms in a subject that can be at increased risk of a microbial infectious disease but does not yet experience or exhibit symptoms, inhibiting the symptoms of a microbial infectious disease (slowing or arresting its development), providing relief from the symptoms or side-effects of microbial infectious disease (including palliative treatment), and relieving the symptoms of microbial infectious disease (causing regression). Treatment can be prophylactic (to prevent or delay the onset of the disease, or to prevent the manifestation of clinical or subclinical symptoms thereof) or therapeutic suppression or alleviation of symptoms after the manifestation of the disease or condition.
“Experimentally-synthesized or naturally-occurring drug or drug-like compounds” refers to compounds that have been screened or tested for one or more of toxicity, absorption, distribution, metabolism excretion, or pharmacokinetics. The experimentally-synthesized or naturally-occurring drug or drug-like compounds may also be approved for use by the U.S. Food and Drug Administration.
The term “modulator” includes inhibitors and activators. Inhibitors are agents that, e.g., bind to, partially or totally block stimulation, decrease, prevent, delay activation, inactivate, desensitize, or block replication of the infectious virus, bacteria, or parasite, e.g., antagonists. Activators are agents that, e.g., bind to, stimulate, increase, open, activate, facilitate, enhance activation, sensitize a receptor or factor that will block replication of the infectious virus, bacteria, or parasite, e.g., agonists. Modulators include agents that, e.g., alter the interaction of the infectious virus, bacteria, or parasite with proteins that bind activators or inhibitors, receptors, including proteins, peptides, lipids, carbohydrates, polysaccharides, or combinations of the above, e.g., lipoproteins, glycoproteins, and the like. Modulators include genetically modified versions of naturally-occurring receptor ligands, e.g., with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, small chemical molecules and the like. Such assays for inhibitors and activators include, e.g., applying putative modulator compounds to a cell infected with a virus, bacteria, or parasite and then determining the functional effects on virus, bacteria, or parasite replication, as described herein. Samples or assays comprising cells with infectious virus, bacteria, or parasite can be treated with a potential activator, inhibitor, or modulator are compared to control samples without the inhibitor, activator, or modulator to examine the extent of inhibition of replication by the infectious virus, bacteria, or parasite. Control samples (untreated with inhibitors) can be assigned a relative activity value of 100%. Inhibition of replication by the infectious virus, bacteria, or parasite is achieved when the activity value relative to the control is about 80%, optionally 50% or 25-0%.
“Inhibitors,” “activators,” and “modulators” of infectious microbial disease, e.g., an infectious disease caused by a herpesvirus, a human immunodeficiency virus, or Plasmodium falciparium. in cells are used to refer to inhibitory, activating, or modulating molecules, respectively, identified using in vitro and in vivo assays for compounds that block replication of the infectious virus, bacteria, or parasite.
“ED50” means the dose of a drug which produces 50% of its maximum response or effect.
“Effective amount” refers to concentrations of components such as drugs or small molecule inhibitors, or compositions effective for producing an intended result including a method for treating a disease or condition in a mammalian subject, e.g., herpesvirus infection, malaria, cancer or neoplastic disease, with compounds or therapeutic compositions of the invention. An effective amount of compounds or therapeutic compositions reduces or eliminates infectious disease or cancer, or prevents it's occurrence or recurrence in the mammalian subject.
“Administering” or “administration” refers to the process by which compounds or therapeutic compositions of the invention are delivered to a patient for treatment purposes for a disease or condition in the patient, e.g., herpesvirus infection, malaria, cancer or neoplastic disease. Compounds or therapeutic compositions can be administered a number of ways including parenteral (e.g. intravenous and intraarterial as well as other appropriate parenteral routes), oral subcutaneous, inhalation, or transdermal. compounds or therapeutic compositions of the invention are administered in accordance with good medical practices taking into account the patient's clinical condition, the site and method of administration, dosage, patient age, sex, body weight, and other factors known to physicians.
“Animal” or “mammalian subject” refers to mammals, preferably mammals such as humans, primates, rats, or mice. Likewise, a “patient” or “subject” to be treated by the method of the invention can mean either a human or non-human animal, to whom treatment, including prophylactic treatment, with the compounds or therapeutic compositions of the present invention, is provided. For treatment of those conditions or disease states that are specific for a specific animal such as a human patient, the term refers to that specific animal.
Therapeutic Applications
The compounds and modulators identified by the methods of the present invention can be used in a variety of methods of treatment. Thus, the present invention provides compositions and methods for treating an infectious microbial disease, e.g., an infectious disease caused by a herpesvirus, a human immunodeficiency virus, or Plasmodium falciparium.
Exemplary infectious disease, include but are not limited to, viral, bacterial, fungal, or parasitic diseases. The polypeptide or polynucleotide of the present invention can be used to treat or detect infectious agents. For example, by increasing the immune response, particularly increasing the proliferation and differentiation of B and/or T cells, infectious diseases can be treated. The immune response can be increased by either enhancing an existing immune response, or by initiating a new immune response. Alternatively, the polypeptide or polynucleotide of the present invention can also directly inhibit the infectious agent, without necessarily eliciting an immune response.
Viruses are one example of an infectious agent that can cause disease or symptoms that can be treated or detected by a polynucleotide or polypeptide of the present invention. Examples of viruses, include, but are not limited to the following DNA and RNA viral families: Arbovirus, Adenoviridae, Arenaviridae, Arterivirus, Birnaviridae, Bunyaviridae, Caliciviridae, Circoviridae, Coronaviridae, Flaviviridae, Hepadnaviridae (Hepatitis), Herpesviridae (such as, Cytomegalovirus, Herpes Simplex, Herpes Zoster), Mononegavirus (e.g., Paramyxoviridae, Morbillivirus, Rhabdoviridae), Orthomyxoviridae (e.g., Influenza), Papovaviridae, Parvoviridae, Picornaviridae, Poxyiridae (such as Smallpox or Vaccinia), Reoviridae (e.g., Rotavirus), Retroviridae (HTLV-I, HTLV-II, Lentivirus), and Togaviridae (e.g., Rubivirus). Viruses falling within these families can cause a variety of diseases or symptoms, including, but not limited to: arthritis, bronchiollitis, encephalitis, eye infections (e.g., conjunctivitis, keratitis), chronic fatigue syndrome, hepatitis (A, B, C, E, Chronic Active, Delta), meningitis, opportunistic infections (e.g., AIDS), pneumonia, Burkitt's Lymphoma, chickenpox, hemorrhagic fever, Measles, Mumps, Parainfluenza, Rabies, the common cold, Polio, leukemia, Rubella, sexually transmitted diseases, skin diseases (e.g., Kaposi's, warts), and viremia. A polypeptide or polynucleotide of the present invention can be used to treat or detect any of these symptoms or diseases.
Similarly, bacterial or fungal agents that can cause disease or symptoms and that can be treated or detected by a polynucleotide or polypeptide of the present invention include, but not limited to, the following Gram-Negative and Gram-positive bacterial families and fingi: Actinomycetales (e.g., Corynebacterium, Mycobacterium, Norcardia), Aspergillosis, Bacillaceae (e.g., Anthrax, Clostridium), Bacteroidaceae, Blastomycosis, Bordetella, Borrelia, Brucellosis, Candidiasis, Campylobacter, Coccidioidomycosis, Cryptococcosis, Dermatocycoses, Enterobacteriaceae (Klebsiella, Salmonella, Serratia, Yersinia), Erysipelothrix, Helicobacter, Legionellosis, Leptospirosis, Listeria, Mycoplasmatales, Neisseriaceae (e.g., Acinetobacter, Gonorrhea, Menigococcal), Pasteurellacea Infections (e.g., Actinobacillus, Heamophilus, Pasteurella), Pseudomonas, Rickettsiaceae, Chlamydiaceae, Syphilis, and Staphylococcal. These bacterial or fungal families can cause the following diseases or symptoms, including, but not limited to: bacteremia, endocarditis, eye infections (conjunctivitis, tuberculosis, uveitis), gingivitis, opportunistic infections (e.g., AIDS related infections), paronychia, prosthesis-related infections, Reiter's Disease, respiratory tract infections, such as Whooping Cough or Empyema, sepsis, Lyme Disease, Cat-Scratch Disease, Dysentery, Paratyphoid Fever, food poisoning, Typhoid, pneumonia, Gonorrhea, meningitis, Chlamydia, Syphilis, Diphtheria, Leprosy, Paratuberculosis, Tuberculosis, Lupus, Botulism, gangrene, tetanus, impetigo, Rheumatic Fever, Scarlet Fever, sexually transmitted diseases, skin diseases (e.g., cellulitis, dermatocycoses), toxemia, urinary tract infections, wound infections. A polypeptide or polynucleotide of the present invention can be used to treat or detect any of these symptoms or diseases.
Moreover, parasitic agents causing disease or symptoms that can be treated or detected by a polynucleotide or polypeptide of the present invention include, but not limited to, the following families: Amebiasis, Babesiosis, Coccidiosis, Cryptosporidiosis, Dientamoebiasis, Dourine, Ectoparasitic, Giardiasis, Helminthiasis, Leishmaniasis, Theileriasis, Toxoplasmosis, Trypanosomiasis, and Trichomonas. These parasites can cause a variety of diseases or symptoms, including, but not limited to: Scabies, Trombiculiasis, eye infections, intestinal disease (e.g., dysentery, giardiasis), liver disease, lung disease, opportunistic infections (e.g., AIDS related), Malaria, pregnancy complications, and toxoplasmosis. A polypeptide or polynucleotide of the present invention can be used to treat or detect any of these symptoms or diseases.
Preferably, treatment using a small chemical molecule inhibitor, a polypeptide inhibitor, or a peptidomimetic inhibitor of viral, bacterial, or parasite replication of the present invention could either be by administering an effective amount of the small chemical molecule inhibitor, the polypeptide inhibitor, or the peptidomimetic inhibitor to the patient, or by removing cells from the patient, supplying the cells with a polynucleotide of the present invention, and returning the engineered cells to the patient (ex vivo therapy). Moreover, the polypeptide or peptidomimetic of the present invention can be used as an antigen in a vaccine to raise an immune response against infectious disease.
Formulation and Administration of Pharmaceutical Compositions
The invention provides pharmaceutical compositions comprising small chemical molecule inhibitors, a polypeptide inhibitors, or a peptidomimetic inhibitors of the invention. As discussed above, the inhibitors of the invention can be used to inhibit expression or activity of viral, bacterial, or parasitic proteins involved in infection or replication. Such inhibition in a cell or a non-human animal can generate a screening modality for identifying compounds to treat or ameliorate a microbial infectious disease. Administration of a pharmaceutical composition of the invention to a subject is used to generate a toleragenic immunological environment in the subject. This can be used to tolerize the subject to an antigen.
The small chemical molecule inhibitor, polypeptide inhibitor, or peptidomimetic inhibitor of the invention can be combined with a pharmaceutically acceptable carrier (excipient) to form a pharmacological composition. Pharmaceutically acceptable carriers can contain a physiologically acceptable compound that acts to, e.g., stabilize, or increase or decrease the absorption or clearance rates of the pharmaceutical compositions of the invention. Physiologically acceptable compounds can include, e.g., carbohydrates, such as glucose, sucrose, or dextrans, antioxidants, such as ascorbic acid or glutathione, chelating agents, low molecular weight proteins, compositions that reduce the clearance or hydrolysis of the peptides or polypeptides, or excipients or other stabilizers and/or buffers. Detergents can also used to stabilize or to increase or decrease the absorption of the pharmaceutical composition, including liposomal carriers. Pharmaceutically acceptable carriers and formulations for peptides and polypeptide are known to the skilled artisan and are described in detail in the scientific and patent literature, see e.g., the latest edition of Remington's Pharmaceutical Science, Mack Publishing Company, Easton, Pa. (“Remington's”).
Other physiologically acceptable compounds include wetting agents, emulsifying agents, dispersing agents or preservatives which are particularly useful for preventing the growth or action of microorganisms. Various preservatives are well known and include, e.g., phenol and ascorbic acid. One skilled in the art would appreciate that the choice of a pharmaceutically acceptable carrier including a physiologically acceptable compound depends, for example, on the route of administration of the peptide or polypeptide of the invention and on its particular physio-chemical characteristics.
In one aspect, a solution of a small chemical molecule inhibitor, a polypeptide inhibitor, or a peptidomimetic inhibitor of the invention are dissolved in a pharmaceutically acceptable carrier, e.g., an aqueous carrier if the composition is water-soluble. Examples of aqueous solutions that can be used in formulations for enteral, parenteral or transmucosal drug delivery include, e.g., water, saline, phosphate buffered saline, Hank's solution, Ringer's solution, dextrose/saline, glucose solutions and the like. The formulations can contain pharmaceutically acceptable auxiliary substances as required to approximate physiological conditions, such as buffering agents, tonicity adjusting agents, wetting agents, detergents and the like. Additives can also include additional active ingredients such as bactericidal agents, or stabilizers. For example, the solution can contain sodium acetate, sodium lactate, sodium chloride, potassium chloride, calcium chloride, sorbitan monolaurate or triethanolamine oleate. These compositions can be sterilized by conventional, well-known sterilization techniques, or can be sterile filtered. The resulting aqueous solutions can be packaged for use as is, or lyophilized, the lyophilized preparation being combined with a sterile aqueous solution prior to administration. The concentration of small chemical molecule, polypeptide, or peptidomimetic in these formulations can vary widely, and will be selected primarily based on fluid volumes, viscosities, body weight and the like in accordance with the particular mode of administration selected and the patient's needs.
Solid formulations can be used for enteral (oral) administration. They can be formulated as, e.g., pills, tablets, powders or capsules. For solid compositions, conventional nontoxic solid carriers can be used which include, e.g., pharmaceutical grades of mannitol, lactose, starch, magnesium stearate, sodium saccharin, talcum, cellulose, glucose, sucrose, magnesium carbonate, and the like. For oral administration, a pharmaceutically acceptable nontoxic composition is formed by incorporating any of the normally employed excipients, such as those carriers previously listed, and generally 10% to 95% of active ingredient (e.g., peptide). A non-solid formulation can also be used for enteral administration. The carrier can be selected from various oils including those of petroleum, animal, vegetable or synthetic origin, e.g., peanut oil, soybean oil, mineral oil, sesame oil, and the like. Suitable pharmaceutical excipients include e.g., starch, cellulose, talc, glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk, silica gel, magnesium stearate, sodium stearate, glycerol monostearate, sodium chloride, dried skim milk, glycerol, propylene glycol, water, ethanol.
Small chemical molecule inhibitor, polypeptide inhibitor, or peptidomimetic inhibitor of the invention, when administered orally, can be protected from digestion. This can be accomplished either by complexing the nucleic acid, peptide or polypeptide with a composition to render it resistant to acidic and enzymatic hydrolysis or by packaging the nucleic acid, peptide or polypeptide in an appropriately resistant carrier such as a liposome. Means of protecting compounds from digestion are well known in the art, see, e.g., Fix, Pharm Res. 13: 1760-1764, 1996; Samanen, J. Pharm. Pharmacol. 48: 119-135, 1996; U.S. Pat. No. 5,391,377, describing lipid compositions for oral delivery of therapeutic agents (liposomal delivery is discussed in further detail, infra).
Systemic administration can also be by transmucosal or transdermal means. For transmucosal or transdermal administration, penetrants appropriate to the barrier to be permeated can be used in the formulation. Such penetrants are generally known in the art, and include, e.g., for transmucosal administration, bile salts and fusidic acid derivatives. In addition, detergents can be used to facilitate permeation. Transmucosal administration can be through nasal sprays or using suppositories. See, e.g., Sayani, Crit. Rev. Ther. Drug Carrier Syst. 13: 85-184, 1996. For topical, transdermal administration, the agents are formulated into ointments, creams, salves, powders and gels. Transdermal delivery systems can also include, e.g., patches.
The small chemical molecule inhibitor, polypeptide inhibitor, or peptidomimetic inhibitor of the invention can also be administered in sustained delivery or sustained release mechanisms, which can deliver the formulation internally. For example, biodegradable microspheres or capsules or other biodegradable polymer configurations capable of sustained delivery of a peptide can be included in the formulations of the invention (see, e.g., Putney, Nat. Biotechnol. 16: 153-157, 1998).
For inhalation, the small chemical molecule inhibitor, polypeptide inhibitor, or peptidomimetic inhibitor of the invention can be delivered using any system known in the art, including dry powder aerosols, liquids delivery systems, air jet nebulizers, propellant systems, and the like. See, e.g., Patton, Biotechniques 16: 141-143, 1998; product and inhalation delivery systems for polypeptide macromolecules by, e.g., Dura Pharmaceuticals (San Diego, Calif.), Aradigrn (Hayward, Calif.), Aerogen (Santa Clara, Calif.), Inhale Therapeutic Systems (San Carlos, Calif.), and the like. For example, the pharmaceutical formulation can be administered in the form of an aerosol or mist. For aerosol administration, the formulation can be supplied in finely divided form along with a surfactant and propellant. In another aspect, the device for delivering the formulation to respiratory tissue is an inhaler in which the formulation vaporizes. Other liquid delivery systems include, e.g., air jet nebulizers.
In preparing pharmaceuticals of the present invention, a variety of formulation modifications can be used and manipulated to alter pharmacokinetics and biodistribution. A number of methods for altering pharmacokinetics and biodistribution are known to one of ordinary skill in the art. Examples of such methods include protection of the compositions of the invention in vesicles composed of substances such as proteins, lipids (for example, liposomes, see below), carbohydrates, or synthetic polymers (discussed above). For a general discussion of pharmacokinetics, see, e.g., Remington's, Chapters 37-39.
The small chemical molecule inhibitor, polypeptide inhibitor, or peptidomimetic inhibitor of the invention can be delivered alone or as pharmaceutical compositions by any means known in the art, e.g., systemically, regionally, or locally (e.g., directly into, or directed to, a tumor); by intraarterial, intrathecal (IT), intravenous (IV), parenteral, intra-pleural cavity, topical, oral, or local administration, as subcutaneous, intra-tracheal (e.g., by aerosol) or transmucosal (e.g., buccal, bladder, vaginal, uterine, rectal, nasal mucosa). Actual methods for preparing administrable compositions will be known or apparent to those skilled in the art and are described in detail in the scientific and patent literature, see e.g., Remington's. For a “regional effect,” e.g., to focus on a specific organ, one mode of administration includes intra-arterial or intrathecal (IT) injections, e.g., to focus on a specific organ, e.g., brain and CNS (see e.g., Gurun, Anesth Analg. 85: 317-323, 1997). For example, intra-carotid artery injection if preferred where it is desired to deliver a nucleic acid, peptide or polypeptide of the invention directly to the brain. Parenteral administration is a preferred route of delivery if a high systemic dosage is needed. Actual methods for preparing parenterally administrable compositions will be known or apparent to those skilled in the art and are described in detail, in e.g., Remington's, See also, Bai, J. Neuroimmunol. 80: 65-75, 1997; Warren, J. Neurol. Sci. 152: 31-38, 1997; Tonegawa, J. Exp. Med. 186: 507-515, 1997.
In one aspect, the pharmaceutical formulations comprising a small chemical molecule inhibitor, a polypeptide inhibitor, or a peptidomimetic inhibitor of the invention are incorporated in lipid monolayers or bilayers, e.g., liposomes, see, e.g., U.S. Pat. Nos. 6,110,490; 6,096,716; 5,283,185; 5,279,833. The invention also provides formulations in which water soluble small chemical molecule inhibitors, polypeptide inhibitors, or peptidomimetic inhibitors of the invention have been attached to the surface of the monolayer or bilayer. For example, peptides can be attached to hydrazide-PEG-(distearoylphosphatidyl)ethanolamine-containing liposomes (see, e.g., Zalipsky, Bioconjug. Chem. 6: 705-708, 1995). Liposomes or any form of lipid membrane, such as planar lipid membranes or the cell membrane of an intact cell, e.g., a red blood cell, can be used. Liposomal formulations can be by any means, including administration intravenously, transdermally (see, e.g., Vutla, J. Pharm. Sci. 85: 5-8, 1996), transmucosally, or orally. The invention also provides pharmaceutical preparations in which the small chemical molecule inhibitors, polypeptide inhibitors, or peptidomimetic inhibitors of the invention are incorporated within micelles and/or liposomes (see, e.g., Suntres, J. Pharm. Pharmacol. 46: 23-28, 1994; Woodle, Pharm. Res. 9: 260-265, 1992). Liposomes and liposomal formulations can be prepared according to standard methods and are also well known in the art, see, e.g., Remington's; Akimaru, Cytokines Mol. Ther. 1: 197-210, 1995; Alving, Immunol. Rev. 145: 5-31, 1995; Szoka, Ann. Rev. Biophys. Bioeng. 9: 467, 1980, U.S. Pat. Nos. 4,235,871, 4,501,728 and 4,837,028.
The pharmaceutical compositions are generally formulated as sterile, substantially isotonic and in full compliance with all Good Manufacturing Practice (GMP) regulations of the U.S. Food and Drug Administration.
Treatment Regimens: Pharmacokinetics
The pharmaceutical compositions of the invention can be administered in a variety of unit dosage forms depending upon the method of administration. Dosages for typical nucleic acid, peptide and polypeptide pharmaceutical compositions are well known to those of skill in the art. Such dosages are typically advisorial in nature and are adjusted depending on the particular therapeutic context, patient tolerance, etc. The amount of small chemical molecule inhibitors, polypeptide inhibitors, or peptidomimetic inhibitors adequate to accomplish this is defined as a “therapeutically effective dose.” The dosage schedule and amounts effective for this use, i.e., the “dosing regimen,” will depend upon a variety of factors, including the stage of the disease or condition, the severity of the disease or condition, the general state of the patient's health, the patient's physical status, age, pharmaceutical formulation and concentration of active agent, and the like. In calculating the dosage regimen for a patient, the mode of administration also is taken into consideration. The dosage regimen must also take into consideration the pharmacokinetics, i.e., the pharmaceutical composition's rate of absorption, bioavailability, metabolism, clearance, and the like. See, e.g., Gennaro, (ed), Remington's Pharmaceutical Sciences, 20th edition, Mack Publishing Company, pp. 1127-1144, 2000; Egleton, Peptides 18: 1431-1439, 1997; Langer, Science 249: 1527-1533, 1990.
In therapeutic applications, compositions are administered to a patient suffering from an infectious disease in an amount sufficient to at least partially arrest the condition or a disease and/or its complications. For example, in one aspect, a soluble small chemical molecule, polypeptide, or peptidomimetic pharmaceutical composition dosage for intravenous (IV) administration would be about 0.01 mg/hr to about 1.0 mg/hr administered over several hours (typically 1, 3, or 6 hours), which can be repeated for weeks with intermittent cycles. Considerably higher dosages (e.g., ranging up to about 10 mg/ml) can be used, particularly when the drug is administered to a secluded site and not into the blood stream, such as into a body cavity or into a lumen of an organ, e.g., the cerebrospinal fluid (CSF).
The invention will be further described with reference to the following examples; however, it is to be understood that the invention is not limited to such examples.
The first experimental verification of our computational predictions were with TMPyP4, the top ranking inhibitor predicted to bind to all known herpesvirus proteases (see
Antimalarial drugs currently target single Plasmodium proteins. Effective therapeutic regimens require a combination of drugs that have different mechanisms of action during the same stage of the parasite's life cycle. Baird, N Engl J Med 352: 1565-1577, 2005. However, malaria is a disease that occurs mostly in tropical and subtropical areas where patients have limited access to drugs, and combination drug regimens may not succeed due to poor adherence. Fungladda, et al., Bull World Health Organ 76 Suppl 1: 59-66, 1998. New antimalarial therapies that include multi-target drugs, which are currently being used extensively to treat both infectious and inherited diseases, may have higher efficacy than single target drugs and provide a simpler regimen for antimalarial therapy. Csermely et al., Trends Pharmacol Sci 26:178-182, 2005; Ravi Chandra et al., Protein Eng Des Sel 17: 175-182, 2004. This study predicted a list of drugs that bind to the active site of multiple Plasmodium falciparum proteins with high affinity.
Protein-inhibitor docking with dynamics has been used as a general protocol to predict inhibitors from a pool of FDA experimental and approved drugs against multiple targets in malaria. A computational protein-inhibitor docking with dynamics protocol was used to calculate the binding affinities of 1105 approved and 1239 experimental drugs (obtained from ChemBank) against thirteen Plasmodium proteins whose structures have been determined by X-ray crystallography. <http://ligand.info/ligand_info_subset—1.sdf.gz>, accessed May 1, 2005. Binding affinity calculations were carried out using AutoDock version 3.0.5 with a Lamarckian genetic algorithm. Each drug was first placed into the active site of the protein to find the most stable binding mode. The protein-drug complexes were consequently solvated in a water shell with sodium and chloride ions. One hundred steps of energy minimization were applied, followed by 0.1 picoseconds (ps) of molecular dynamics simulation to each complex using the XPLOR software version 3.851. The conformations at 0.1 ps were used for the protein-drug binding affinity calculations.
For each protein, a given drug was docked into the active site and allowed to move in an exhaustive manner to find the most stable binding conformation. The protein-drug binding affinity in terms of the inhibitory constant (Ki) was calculated every time the drug molecule was moved. After repeating this procedure for all the drugs for each protein, the twenty drugs with the lowest Ki values were considered high affinity drug candidates. See
Twenty multi-target drugs that showed high affinity across two or more proteins were predicted. Four are approved drugs; KN62 (targeting three proteins), Protoporphyrin IX, Phthalylsulfathiazole, and Sulfaphenazole (targeting two proteins each), and the other sixteen are experimental, each targeting up to six proteins. The best drugs in terms of multi-target functionality were STI-571 (targeting six proteins), and Bisindolylmaleimide x, GW8510, and Piper (targeting five proteins each). The best combination of two drugs was Bisindolylmaleimide x and GW8510, which together target ten Plasmodium proteins. An analysis of five known single-target antimalarial drugs against these proteins showed that our calculated Kis for these drugs match well with experimentally determined values (when available), and usually rank within the top 5th percentile compared to all our drugs. See Table 4.
Vaccines attacking multiple Plasmodium proteins have been proposed with promising results. Nussenzweig et al., Science 265: 1381-1383, 1994. In a similar fashion, designing new antimalarial drugs that target multiple Plasmodium proteins simultaneously is proposed. Our computational drug screening protocol provides evidence for twenty approved and/or experimental drugs targeting thirteen Plasmodium proteins. The drug candidates listed here may be experimentally tested for inhibition of Plasmodium growth, and used as a starting point for further design of a high efficacy multi-target antimalarial drug.
ffinity. The calculated Ki values for these drugs are similar to the experimentally determined ones
ercentile in comparison to all our drugs.
ihydrofolate reductase with pyrimethamine
ihydrofolate reductase (1J3I)
asmepsin II (1LF3)
Adenosyl-L-homocysteine hydrolase (1V8B)
ymidylate synthase (1J3I)
indicates data missing or illegible when filed
Table 5 shows the results for the 16 inhibitors that were tested. Four inhibitors were found to have very strong binding (e.g., KN62, U-74389G, Daunorubicin, and Nitrotetrazolium) Two inhibitors have moderate binding (e.g., Imatinib (Gleevec) and TmPyP4). Based on this study, these six drugs work against malaria.
Glycoprotein 41 (gp41) is a crucial molecule in the human immunodeficiency virus type 1 (HIV-1) envelope and is a drug target for treatment of HIV disease. Gp41 consists of four major parts: a N-terminal hydrophobic fusion peptide, a cysteine loop, and heptad repeats 1 & 2 (HR1 & 2). gp41 mediates fusion of viral and target-cell membranes by inserting its fusion peptide into the target-cell membrane after formation of CD4/gp120/chemokine-receptor complex. The HR1 trimer is a three-stranded coiled-coil structure that associates with HR2 in an antiparallel orientation to form a six-helical bundle hairpin complex. Formation of the HR1/HR2 hairpin complex brings viral and target-cell membranes in close proximity to enable membrane fusion and viral entry. See
Enfuvirtide is the first approved peptide-based HIV-1 fusion inhibitor. It corresponds to amino acid residues 127-162 of HIV-1 gp41 (part of the HR2 domain) or residues 643-678 in the gp160 precursor of the HIV envelope glycoprotein. The inhibitor competes with the viral HR2 in binding to the HR1 trimeric coiled-coil hydrophobic groove, thereby blocking viral HR1/HR2 association. Wild et al., Proc Natl Acad Sci USA 89: 10537-10541, 1992; Jiang et al., Nature 365: 113, 1993; Wild et al., AIDS Res Hum Retroviruses 9: 1051-1053, 1993; Wild et al., Proc Natl Acad Sci USA 91: 9770-9774, 1994. Mutations of HR1 residues at the hydrophobic groove (G36, V38, Q40, N42, N43 and L45) have been reported to cause enfuvirtide resistance. Roman et al., J Acquir Immune Defic Syndr 33: 134-139, 2003; Marcelin et al., AIDS 18: 1340-1342, 2004; Wei et al., Antimicrob Agents Chemother 46: 1896-1905, 2002. Although HIV-1 strains with these HR1 mutations can escape from enfuvirtide, these strains are significantly less fit than the wild-type. Wei et al., Antimicrob Agents Chemother 46: 1896-1905, 2002; Lu et al., J Virol 78: 4628-4637, 2004; Menzo et al., Antimicrob Agents Chemother 48: 3253-3259, 2004. It is unclear how viral HR1 and HR2 mutations reduce the effectiveness of the enfuvirtide and whether these mutations subsequently restore viral fitness.
In this study, a computational protein modeling approach was used to investigate the effects of amino acid changes in HR2 at positions that directly interact with the enfuvirtide-resistant HR1 residues. Such changes in HR2 were shown to improve the structural stability of the HR1/HR2 hairpin complex, thereby enhancing drug resistance level and viral fitness of the enfuvirtide-resistant strains.
Generation of mutant theoretical structures. The theoretical structure of a six-helical bundle HIV-1 gp41 hairpin complex consisting of HR1, HR2 and the cysteine loop (Protein Data Bank identifier 1IF3) was used as a template for creating mutant structures. This structure was previously modeled using NMR restraints from the simian immunodeficiency virus (SIV) gp41 ectodomain as a template. Caffrey, Biochim Biophys Acta 1536: 116-122, 2001. Wild-type side chains were substituted with the mutant side chains based on a backbone-dependent side chain rotamer library and a linear repulsive steric energy term provided by SCWRL version 3.0. Bower et al., J Mol Biol 267: 1268-1282, 1997. The resulting all-atom models were energy minimized for 200 steps using the Energy Calculation and Dynamics (ENCAD) program. Levitt et al., J Mol Biol 46: 269-279, 1969; Levitt, J Mol Biol 82: 393-420, 1974; Levitt, J Mol Biol 168: 595-620, 1983; Levitt et al., Comp Phys Comm 91: 215-231, 1995.
Prediction of the stability of the hairpin complex structures. A residue-specific all-atom probability discriminatory function (RAPDF) score was used as an indicator of the structural stability of a given hairpin complex. Samudrala et al., J Mol Biol 275: 895-916, 1997. This function has been used as a key component of protein structure prediction methods that work well in the CASP blind prediction experiments. Hung et al., Nucleic Acids Res 33: W77-80, 2005.
A residue-specific all-atom probability discriminatory function (RAPDF) score was used as a proxy for the structural stability of a given hairpin complex. The RAPDF score is calculated based on the conditional probability of a conformation being native-like given a set of inter-atomic distances. The conditional probabilities are compiled by counting frequencies of distances between pairs of atom types in a database of protein structures. The distances observed are divided into 1.0 Å bins ranging from 3.0 Å to 20.0 Å. Contacts between atom types in the 0-3 Å range are placed in a separate bin, resulting in a total of 18 distance bins. Distances within a single residue are not included in the counts. Tables of scores were compiled proportional to the negative log conditional probability that one is observing a native conformation given an interatomic distance for all possible pairs of the 167 atom types for the 18 distance ranges from a database of known structures. Given a set of distances in a conformation, the probability that the conformation represents a correct fold is evaluated by summing the scores for all distances and the corresponding atom pairs. A complete description of this formalism has been published elsewhere. Samudrala et al., J Mol Biol 275: 895-916, 1997.
Comparison of the RAPDF stability scores with experimentally-determined inching temperatures. A set of ten gp41 mutant structures were generated for which the melting temperatures (Tm) are available. Sanders et al., J Virol 76: 8875-8889, 2002; Markosyan et al., Virology 10: 302:174-184, 2002. The RAPDF scores for these structures and the wild-type structure was calculated and compared to the melting temperatures. See Table 6. The goal was to determine how well the predicted RAPDF scores correlate with experimentally-determined gp41 stability.
Comparison of the RAPDF stability scores with the EC50 values and the viral fitness levels. A set of seven HR1-mutant/HR2-wild-type structures were generated for which the EC50 values (the molar concentrations of enfuvirtide that inhibits viral-target cell membrane fusion by 50%) and the viral fitness levels are available. See Table 7. Greenberg et al., J Antimicrob Chemother 54: 333-340, 2004; Lu et al., J Virol 78: 4628-4637, 2004. The second set of these mutants was duplicated from the first set with additional HR2 compensatory mutations (S138Y and Q139R). The RAPDF scores were calculated for the structures in both sets and compared the scores with the experimental enfuvirtide EC50 values and the viral fitness levels. The goal was to determine how well the RAPDF scores (and by inference, protein stability) predict EC50 and viral fitness.
Mapping of HR1/HR2 residue-residue interactions. The HR1/HR2 residue-residue interactions were mapped by finding the corresponding HR2 residues that had Cα-Cα distances within 7.5 Å from the following enfuvirtide-resistant HR1 residues: G36, I37, V38, Q40, N42, N43, L44 and L45. See
Generation of enfuvirtide-resistant HR1/HR2 hairpin structures. An initial set of 28 mutant structures of the HR1/HR2 hairpin complex were generated such that each structure consisted of one enfuvirtide-resistant mutation on HR1 and a wild-type amino acid at the corresponding HR2 residue. This initial set was used to generate nineteen other sets of HR1/HR2 double mutants such that the corresponding HR2 wild-type residue was changed to each of the remaining nineteen amino acids. At the end of this step, a total of 560 structures of the enfuvirtide-resistant HR1/HR2 mutant complex were obtained. The mutation patterns of the generated hairpin structures are shown in
Identification of the amino acids at the corresponding HR2 positions that improve structural stability of the hairpin complex. The RAPDF scores of 560 HR1/HR2 mutant structures calculated from the previous step were compiled in a 28×20 table. Each row of this table contains 20 RAPDF scores calculated from 20 hairpin structures. Each of these 20 hairpin structures consisted of one enfuvirtide-resistant mutation on HR1 and one of the 20 amino acids at the corresponding HR2 residue. The amino acid at the corresponding HR2 residue was identified that improved structural stability of the hairpin complex by calculating the mean and standard deviation of the RAPDF scores on each row. The cutoff was set at one standard deviation under the mean. The hairpin structure that had the RAPDF score lower than the cutoff was defined as having improved structural stability. The amino acid at the corresponding HR2 residue of this structure was defined as a “compensatory amino acid” that improved the structural stability of the hairpin complex. See
Designing enfuvirtide derivatives against enfuvirtide-resistant strains. From the mapping of residue-residue interaction and the identification of HR2 compensatory amino acid studies, six corresponding HR2 residues (134, 138, 139, 141, 142 and 145) were identified that were in close contact with the enfuvirtide-resistant HR1 residues. The HR2 compensatory amino acids identified based on the RAPDF scores were: D, H, (L), N, Q, S, Y for residue 134; H, N, Q, (S), T, W, Y for residue 138; K, N, (Q), R for residue 139; H, K, R, (Q) for residue 141; H, K, M, N, (Q), R, Y for residue 142 and F, (N), R, W, Y for residue 145. (Wild-type amino acids are indicated by parenthesis.)
An initial set of eighteen HR1 mutant structures reported to cause enfuvirtide resistance in patients were generated. Roman et al., J Acquir Immune Defic Syndr 33: 134-139, 2003; Marcelin et al., AIDS 18: 1340-1342, 2004; Wei et al., Antimicrob Agents Chemother 46: 1896-1905, 2002. The list of the HR1 mutations is shown in Table 7. For each HR1 mutant structure, mutations were introduced at residues 134, 138, 139, 141, 142 and 145 of the HR2. The wild-type amino acids of these six HR2 residues were randomly replaced by the compensatory amino acids. This yielded a total of 27,440 HR1/HR2 mutant structures, each of which had different HR2 mutation patterns. The same procedure was applied to all eighteen HR1 mutant structures so that a total of 493,920 HR1/HR2 mutant structures were obtained in this step.
All structures were constructed as previously described scored using the RAPDF function. The RAPDF scores were categorized into eighteen groups according to eighteen HR1 mutation patterns. The scores were ranked in ascending order to find the general patterns of HR2 mutations that could stabilize hairpin complexes of all enfuvirtide-resistant mutants. See Table 8.
Table 6 shows the RAPDF stability scores and the corresponding melting temperatures for 10 HR1 or HR2 single mutants, as well as the wild-type, from two sources. Sanders et al., J Virol 76: 8875-8889, 2002; Markosyan et al., Virology 10: 302:174-184, 2002. The correlation coefficient is 0.82 (0.86 when the single outlier (I62P) is removed) showing that as the RAPDF score increases (i.e., indicating lower stability), the melting temperature decreases. The best score is obtained for the wild-type (which also has the highest melting temperature reported in both sources). This result indicates that the RAPDF score, a key component of protein structure prediction methods that work well, may be used as a predictor of structural stability. Hung et al., Nucleic Acids Res 33: W77-80, 2005.
The RAPDF scores of seven HR1 mutants were compared with the EC50 values of enfuvirtide and the viral fitness levels. Table 7 shows that the wild-type structure had the best RAPDF score (−35.12). The scores increased to range from −34.98 to −33.78 for all seven HR1 mutant structures and were directly correlated with the EC50 values and inversely correlated with the viral fitness levels. The correlation coefficient between the RAPDF scores and the EC50 values was 0.9. See Table 7. This result indicates that the structural stability scores may be used to accurately estimate the viral fitness levels and the inhibitory activity of the enfuvirtide and its derivatives.
Structural arrangement of eight HR1 residues (G36, I37, V38, Q40, N42, N43, L44 and L45) that have been associated with enfuvirtide resistance were considered. Roman et al., J Acquir Immune Defic Syndr 33: 134-139, 2003; Marcelin et al., AIDS 18: 1340-1342, 2004; Wei et al., Antimicrob Agents Chemother 46: 1896-1905, 2002.
The RAPDF scores of the enfuvirtide-resistant HR1 mutant structures (G36D/S, V38A/E/M, Q40H, N42D/E/S/T, N43D/K/S and L45M) were calculated and compared to the wild-type structure score. The RAPDF scores for these mutant structures ranged from −35.06 to −34.09, which were higher than the score of the wild-type structure (−35.12). This indicates that the enfuvirtide-resistant mutants have lower hairpin structural stability than the wild-type.
The residue-residue mapping revealed six corresponding HR2 residues that interact with eight enfuvirtide-resistant HR1 residues. It was then hypothesized that the compensatory amino acid substitutions at these corresponding HR2 residues may improve structural stability of the HR1/HR2 hairpin complex. To identify these compensatory amino acids, the wild-type amino acid was replaced at the corresponding HR2 positions with each of the other nineteen amino acids.
The RAPDF scores of these HR1/HR2 mutant structures indicated that the HR2 compensatory amino acids were: D, H, (L), N, Q, S, Y for residue 134; H, N, Q, (S), T, W, Y for residue 138; K, N, (Q), R for residue 139; H, K, R, (Q) for residue 141; H, K, M, N, (Q), R, Y for residue 142 and F, (N), R, W, Y for residue 145. (Wild-type amino acids are indicated by parenthesis.) The RAPDF scores of the HR1 mutants possessing one of these HR2 compensatory amino acids ranged from −36.01 to −34.11 indicating enhancement of the structural stability of the hairpin complex after introducing the compensatory amino acids at the corresponding HR2 positions. See
It was further tested whether the HR2 compensatory mutations improve the structural stability of these seven hairpin complexes. The results from residue-residue interaction and compensatory amino acid identification studies suggest that Q139R and/or S138Y mutations in the HR2 are likely to improve the RAPDF scores for these HR1 mutants. Therefore, the Q139R mutation was introduced in all the HR1 mutant structures with an additional S138Y mutation for the N42T+N43K and N42T+N43S mutant structures. It was found that these two HR2 compensatory mutations improved the RAPDF scores of all seven HR1 mutants (ranging from −36.21 to −35.02).
The theoretical structural stability scoring suggests a possible enfuvirtide-resistance mechanism: Initially, mutations in HR1 may be selected to reduce structural stability of HR1/enfuvirtide complex. These mutations alter the biochemical properties (for example, polarity and hydrophobicity) and modify the conformation of the HR1 coiled-coil hydrophobic groove. Comparison of the side chain arrangement at the binding surface of wild-type and mutant HR1 grooves shows that conformational changes are prominent in G36D, Q40H and N43K mutations. See
Even though we are unable to make a direct comparison between the increased theoretical stability of compensatory HR2 mutations and a corresponding increase in experimentally determined melting temperatures, we have demonstrated that the RAPDF score is a reliable indicator of melting temperatures for an independent set of mutations See Table 6. In addition, we have also shown that the RAPDF score is a reliable indicator of the EC50 and viral fitness levels. See Table 7. Taken together, these results indicate that decreased stability of HR1 mutants (predicted by RAPDF scores that correlate well with experimentally-determined melting temperatures) is reversed by the compensatory HR2 mutants (as predicted by RAPDF), which in turn results in lower fusion inhibition and increased viral fitness (RAPDF scores also correlate well with these experimental measures of enfuvirtide activity). Our predictions and results are consistent with previously observed correlations between melting temperatures of the HR1/HR2 complex and fusion inhibition. Gallo et al., J Mol Biol 340: 9-14, 2004.
Previous experimental and clinical studies have identified eighteen mutation patterns in HR1 that are implicated in enfuvirtide resistance in patients [8-10]. In this study, six corresponding HR2 residues and the compensatory amino acids that play a role in improving structural stability of the enfuvirtide-resistant hairpin complex were identified. This suggests the possibility of designing enfuvirtide derivatives to inhibit these resistant strains.
To find the best derivative, eighteen enfuvirtide-resistant HR1 mutant structures were generated. For each HR1 mutant structure, the wild-type amino acids at six corresponding HR2 residues were randomly replaced by the compensatory amino acids yielding 27,440 HR1/HR2 mutant structures, each with a different HR2 mutation pattern. Finally, a total of 493,920 HR1/HR2 mutant structures were obtained after applying this procedure to all eighteen HR1 mutants.
Of the 493,920 mutant structures generated, a common HR2 mutation pattern was found that improved the RAPDF scores of all eighteen enfuvirtide-resistant strains, that is: L134H, S138Y, Q139R, Q141R, Q142R, N145Y/F/R. The scores ranged from −38.69 to −36.71, which were better than that of the HR1/HR2 wild-type strain. See Table 8. This finding suggests a list of the amino acids that may be used to design enfuvirtide derivatives. Modification of the enfuvirtide molecule should focus at the six corresponding residues with amino acid side chains replaced by the ones suggested in Table 8. Such a modification enhances interaction of the derivatives against the wild-type strain and the enfuvirtide-resistant mutants.
In this study, a residue-specific all-atom probability discriminatory function (RAPDF) was applied to score theoretical models of HIV-1 gp41 to demonstrate that the mutant enfuvirtide-resistant strains have low structural stability. The RAPDF scores of these resistant mutants improved after amino acid substitutions at the corresponding residues of HR2 that interact with the HR1 mutant. The findings suggest an enfuvirtide resistance mechanism: Mutations of HR1 modify the hydrophobic groove that limits the likelihood of enfuvirtide accessing its binding site. Additional mutations at the corresponding HR2 residues improve structural stability of the HR1/HR2 hairpin complex, thereby enhancing viral fitness of the mutant strains. This resistance mechanism leads to the idea of designing novel enfuvirtide derivatives that may compete with the viral HR2 for binding in the modified HR1 hydrophobic groove. A combination of such enfuvirtide derivatives along with the HR1-derived enfuvirtide-complement peptide (and its derivatives) may have high potency in reducing viral load and have a wide spectrum effect in controlling HIV-1 wild-type as well as fusion inhibitor resistant strains.
Binding energy and drug regimen prediction for protease inhibitors and HIV mutants has been completed. PIRSpred (protein inhibitor resistance/susceptibility prediction) software is available at http://protinfo.compbio.washington.edu/pirspred. The accuracy of the method is approximately 80% when used standalone and approximately 95% in combination with a knowledge based method when backtested. Jenwitheesuk E, Wang K, Mittler J, Samudrala R. Trends in Microbiology 13: 150-151, 2005; Jenwitheesuk E, Samudrala R., Antiviral Therapy 10: 157-166, 2005; Jenwitheesuk E, Wang K, Mittler J, Samudrala R., AIDS 18: 1858-1859, 2004; Wang K, Jenwitheesuk E, Samudrala R, Mittler J., Antiviral Therapy 9: 343-352, 2004.
Broad-spectrum inhibitors against herpes simplex virus (HSV) proteases (including HSV2, VZV, EBV, CMV, and KSHV) have been studied. Docking with dynamics has been used as a general protocol to predict inhibitors from a pool of FDA experimental and approved drugs) against single targets in different herpesviruses. First round of predictions have been completed, resulting in up to 100 predicted leads. Two predicted inhibitors have been experimentally tested in vitro, and one inhibitor, TMPyP4, has demonstrated 90% inhibition of lytic phase viral growth in a non-toxic dose-dependent manner starting at micromolar concentrations. See Tables 9, 10, and 11. Three dimensional molecular modeling of the inhibitor, TMPyP4, bound to herpesvirus protease is shown in
With regard to testing inhibitors predicted to be effective against herpesvirus infection, TMPyP4 was tested as the top prediction. The procedure for choosing the top prediction was as follows. The top 50 or top 100 list of drugs were chosen for all seeds against all proteins. One can then count how frequently each drug occurs and can rank each drug by its frequency. This final rank is used to suggest which inhibitors to test. For a candidate herpesvirus therapeutic composition, for example, TMPyP4 was the top ranking drug using this procedure.
Similarly, broad-spectrum inhibitors against HIV integrase have been studied. See Table 13. Reference to “Drug ID” is in von Grotthuss, et al., “Ligand.Info Small-Molecule Meta-Database,” Comb Chem High Throughput Screen, 8: 757-761, 2004.
Multi-target multi-condition inhibitors against multiple pathogens, such as inhibitors that target both HIV proteins as well as opportunistic infections that arise from HIV infection, for example, HIV and herpesviruses, or HIV and Pseudomonas. Predictions are in progress against targets from Pseudomonas aeruginosa, Pneumocystis carinii, Toxoplasma gondii, and Cryptosporidium. Natural outcome of other predictions (i.e., prediction of inhibitors against HIV integrase, protease, and herpesviruses). A study has shown predictions that HIV protease inhibitors also inhibit human cytomegalovirus protease. Jenwitheesuk E, and Samudrala R., AIDS 19: 529-533, 2005.
Predictions for broad-spectrum inhibitors are being studied against avian and dog influenza targets, e.g., protease.
HIV gp41 peptidomimetic inhibitors have been studied. Studies have shown that heptad-repeat-2 mutations enhance the stability of the enfuvirtide-resistant HIV-1 gp41 hairpin structure. Jenwitheesuk E, and Samudrala R., Antiviral Therapy 10: 893-900, 2005.
Predictions for broad-spectrum inhibitors are being studied against hepatitis virus.
Predictions for broad-spectrum inhibitors are being studied for inhibitors against proteins involved in cell cycle proliferation in brain cancer, e.g., medulloblastomas.
Predictions for multi-target Plasmodium falciparium inhibitors has been completed against 13 targets. Second round predictions including a 14th target are in progress. More than 20 FDA approved and experimental multi-target inhibitors have been identified against the 14 targets. Of the Plasmodium falciparium targets, Five to six known anti-malarial inhibitors rank in the top 5% in our lists of predictions of binding affinity.
Multi-target Trypanosoma and Leishmania inhibitor predictions are in progress for targets in Trypanosoma brucei, Trypanosoma cruzi, and Leishmania major (causing sleeping sickness, Chagas disease, and Leishmaniasis). A variety of human and animal diseases are caused by pathogens in these two genus, so drugs against these pathogens can be broadly effectively against these diseases.
SARS CoV protease inhibitors predicted that HIV protease inhibitors are effective against SARS CoV. It has been experimentally determined that HIV protease inhibitors are effective against SARS.
The use of docking with dynamics has been used to predict effectiveness of HIV protease inhibitors against CMV protease. Clearance of CMV viraemia in HIV-1 infected patients may result in part from inhibition of CMV protease by HIV-1 protease inhibitors contained in HAART. A computational method has been used to calculate the binding affinity of six HIV-1 protease inhibitors to CMV protease based on its x-ray crystallography structure. The calculations show that amprenavir and indinavir occupy the substrate-binding site of the CMV protease with high affinity and may be implicated in alleviating CMV infection. Cytomegalovirus (CMV) is an AIDS-related opportunistic pathogen that usually infects human immunodeficiency virus type 1 (HIV-1) patients with high level of plasma HIV-1 RNA and low CD4 counts (<200 cells/μL). Mentec et al., AIDS 8: 461-467, 1994; Alder et al., Ophthalmology 105: 651-657, 1998; Gellrich et al., Br J Ophthalmol 80: 818-822, 1996. Highly active antiretroviral therapy (HAART), consisting of HIV-1 protease and reverse transcriptase inhibitors, has been shown to lower plasma HIV-1 RNA levels and elevate CD4 cell counts, and is associated with a reduction in CMV replication and clearance of CMV viraemia. Macdonald et al., J Infect Dis 177: 1182-1187, 1998; Vrabec et al., Ophthalmology 105: 1259-1264, 1998; Casado et al., J Acquir Immune Defic Syndr Hum Retrovirol 19: 130-134, 1998; Jabs et al., Am J Ophthamol 126: 817-822, 1998; Deayton et al., AIDS 13: 1203-1206, 1999; Casado et al., AIDS 13: 1497-1502, 1999; Macdonald et al., Ophthalmology 107: 877-881, 2000; Reed et al., Retina 21: 339-343, 2001. Reports from several groups have shown that immune recovery that results from HAART without any specific anti-CMV therapy is able to suppress CMV infection in HIV-1 infected patients. Deayton et al., AIDS 13: 1203-1206, 1999; Casado et al., AIDS 13: 1497-1502, 1999; Macdonald et al., Ophthalmology 107: 877-881, 2000; Reed et al., Retina 21: 339-343, 2001. However, it is unresolved as to whether HIV-1 protease inhibitors aid clearance of CMV viraemia by inhibiting CMV protease activity.
In this study, an integrated molecular dynamics (MD) simulation and docking methods was used to calculate the ability of six Food and Drug Administration (FDA) approved HIV-1 protease inhibitors to bind to the CMV protease in terms of binding mode and binding energy. The x-ray crystallography structures of CMV protease and HIV-1 protease inhibitors were retrieved from the Protein Data Bank (PDB) (PDB codes: 1NKM for CMV protease, 1HPV for amprenavir, 1HSG for indinavir, 1MUI for lopinavir, 1OHR for nelfinavir, 1HXW for ritonavir and 1C6Z for saquinavir).
Docking calculations were carried out using AutoDock version 3.0.5 with a Lamarckian genetic algorithm. Morris et al, J Comput Chem 19: 1639-1662, 1998. Preliminary docking experiments were first performed to identify the potential binding sites of the inhibitors by generating a grid box that is big enough to cover the entire surface of the protein. The protein-inhibitor complexes derived from the first ranked docking solution in the preliminary docking procedure were consequently solvated in a TIP3-water shell and all atoms were allowed to relax using MD simulation. The MD simulation was carried out with the NAMD software version 2.5b18. Kale et al., J Comput Phys 151: 283-312, 1999. The topology and parameters for each inhibitor was obtained from the PRODRG server. van Aalten et al., J Comput Aided Mol Des 10: 255-262, 1996. One hundred steps of energy minimization of the protein-inhibitor-water complex were initially performed, followed by 0.1 picoseconds of MD simulation at 300 K. The simulations were repeated with three different starting seeds. The trajectories at 0.1 picoseconds were recorded and processed in a second docking step using similar docking parameters as used in the preliminary docking procedure. The primary exception was in the creation of a 3D affinity grid box, where the C-α atom of Ser132 of the catalytic triad was set as a grid center, and the number of grid points in the x, y, z-axes was set to 60×60×60.
AutoDock generates three energy terms: intermolecular energy, internal energy of the ligand, and torsional free energy. The final docked energy was calculated from the sum of the intermolecular energy and the internal energy of the ligand. The free energy of binding was calculated from the sum of the intermolecular and the torsional free energies, and consequently converted into an inhibitory constant (Ki) according to Hess's law. The lowest-energy solution was accepted as the calculated binding energy and its Ki value was used to define the binding affinity of the inhibitors. Further details of our MD simulation and docking protocols are given elsewhere. Jenwitheesuk et al., BMC Struct Biol 3: 2, 2003; Jenwitheesuk et al., Bioorg Med Chem Lett 13: 3989-3992, 2003.
Structural studies of the CMV protease show that it belongs to the serine protease family, with a novel Ser132-His63-His157 catalytic triad, with His157 representing the third member instead of the typical Asp. Tong et al., Nat Struct Biol 5: 819-826, 1998. The substrate-binding site is composed of several subsites: The S1 subsite is formed by residues Leu32, Ser132, Leu133, Arg165 and Arg166. The S1 and S4 subsites are fused together, forming a large pocket with residues His63 and Asp64 on one side, Ser135 on the other, and Lys156 in the middle. The S3 portion of this pocket is formed by salt bridges between residues Glu31, Ser135, Arg137, Arg165 and Arg166. Tong et al., Nat Struct Biol 5: 819-826, 1998. Theoretically, enzymatic activity would be significantly diminished if the catalytic triad, or part of the substrate-binding sites, were occupied by a small drug molecule or peptidomimetic inhibitor.
The first ranked docking solution derived from the preliminary docking procedure showed that all inhibitors bound to the substrate-binding site of the CMV protease. The binding energy and the calculated Ki obtained after MD simulation and second round docking showed that amprenavir and indinavir had high affinity for the CMV protease (as indicated by calculated Ki<10−8 and final docked energy <−14.00 kcal/mol) with the inhibitor occupying subsites S1, S2 and S3. See Table 12. The other four inhibitors, lopinavir, nelfinavir, ritonavir and saquinavir, only partially fit into one or two subsites. The docked energy, the calculated Ki and the binding modes of nelfinavir and lopinavir indicated that these two inhibitors bound the CMV protease more weakly than the other inhibitors. Identical results were obtained for all the three starting seeds used.
A number of studies suggest that protease inhibitors included in the HAART regimen have had a significant impact on CMV infection in decreasing the incidence, changing clinical course, and altering clinical presentation. Macdonald et al., J Infect Dis 177: 1182-1187, 1998; Vrabec et al., Ophthalmology 105: 1259-1264, 1998; Casado et al., J Acquir Immune Defic Syndr Hum Retrovirol 19: 130-134, 1998; Jabs et al., Am J Ophthalmol 126: 817-822, 1998; Deayton et al., AIDS 13: 1203-1206, 1999; Casado et al., AIDS 13: 1497-1502, 1999; Macdonald et al., Ophthalmology 107: 877-881, 2000; Reed et al., Retina 21: 339-343, 2001. However, none of them have identified the inhibitory activity of individual HIV-1 protease inhibitors against CMV.
This computational study provides evidence for the inhibitory activity of two approved inhibitors, amprenavir and indinavir, against the CMV protease. Including either of these two inhibitors in HAART regimen should help control the CMV viral load in HIV-1 infected patients. The activity of the CMV protease would be inhibited soon after starting HAART, in contrast to inhibition by promoting immune system restoration, which may take several weeks.
This study also provides a list of candidate inhibitors that may be experimentally tested for CMV protease inhibitory activity, and for further design of broad-spectrum inhibitors, to control both HIV-1 and CMV infection. Structural studies of human herpes proteases (of which CMV is one) indicate homology among several subtypes. Holwerda, Antiviral Res 35: 1-21, 1997; Qiu et al., Proc Natl Acad Sci USA 94: 2874-2879, 1997; Buisson et al., J Mol Biol 324: 89-103, 2002. Thus further studies to investigate the interaction and activity of these inhibitors, including approved drugs, against proteases from human herpesviruses may be fruitful in combating opportunistic infections originating in HIV-1 patients.
Table 13 shows the results of screening broad spectrum small molecule chemical inhibitors against HIV-1 integrase and TAR. The inhibitors with the highest predicted activity against HIV-1 integrase include, but are not limited to, TMPyP4 (2303), calmidazolium chloride (1951), paromomycin (1565), aurintricarboxylic acid (1921), ro 31-8220 (548), Dichlorobenzamil (36), catenulin (1198), kanamycin (670), and capreomycin (893).
Table 14 shows multitarget small molecule inhibitors of HIV-1 and predicted inhibitors of HIV-1 capsid.
Table 15 shows multitarget small molecule inhibitors of Mycobacterium tuberculosis.
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Each recited range includes all combinations and sub-combinations of ranges, as well as specific numerals contained therein.
All publications and patent applications cited in this specification are herein incorporated by reference in their entirety for all purposes as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference for all purposes.
Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, it will be readily apparent to one of ordinary skill in the art in light of the teachings of this invention that certain changes and modifications may be made thereto without departing from the spirit or scope of the appended claims.
This application claims the benefit of U.S. Provisional Application No. 60/819,426, filed Jul. 7, 2006, which is hereby incorporated by reference in its entirety.
This invention was made by government support by Grant No. GM 068152 from National Institutes of Health, Grant Nos. DBI-0217241 and IIS 0448502 from the National Science Foundation. The Government has certain rights in this invention.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/US2007/072985 | 7/6/2007 | WO | 00 | 9/14/2009 |
| Number | Date | Country | |
|---|---|---|---|
| 60819426 | Jul 2006 | US |
