Immunoinformatics Approach to Design T-cell Epitope-Based Vaccine Against Hendra Virus

Screening of HLA class II epitope-based peptides as potential vaccine candidates is one of the most rational approach for vaccine development against Hendra virus (HeV) infection, for which currently there is no successful vaccine in practice. In this study, screening of epitopes from HeV proteins viz matrix, glycoprotein, nucleocapsid, fusion, C protein, V protein, W protein and polymerase, followed by highest binding affinity & molecular dynamic simulation of selected T-cell epitopes with their corresponding HLA class II alleles has been done. The server ProPred facilitates the binding prediction of HLA class II allele specific epitopes from the antigenic protein sequences of HeV. PEPstrMOD server was used for PDB structure modeling of the screened epitopes and MODELLER was used for HLA alleles modeling. We docked the selected T-cell epitopes with their corresponding HLA allele structures using the AutoDock 4.2 tool. Further the selected docked complex structures were optimized by NAnoscale Molecular Dynamics program (NAMD) at 5 ps, with the CHARMM-22 force field parameter incorporated in Visual Molecular Dynamics (VMD 1.9.2) and complex structure stability was evaluated by calculating RMSD values. Epitopes IRIFVPATN (Nucleocapsid), MRNLLSQSL (Nucleocapsid), VRRAGKYYS (Matrix) and VRLKCLLCG (Fusion) proteins have shown considerable binding with DRB1*0806, DRB1*1304, DRB1*0701 and DRB1*0301 HLA class II allele respectively. Toxicity, antigenicity and population coverage of epitopes IRIFVPATN, MRNLLSQSL, VRRAGKYYS and VRLKCLLCG were analyzed by Toxin Pred, Vexijen and IEDB tool, respectively. The potential T-cell epitopes can be utilized in designing comprehensive epitope-based vaccines and diagnostic kits against Hendra virus after further in-vivo studies.

     

Epitope-based immunoinformatics approach on RNA-dependent RNA polymerase (RdRp) protein complex of Nipah virus (NiV)

Persistent outbreaks of Nipah virus (NiV) with severe case fatality throw a major challenge on researchers to develop a drug or vaccine to combat the disease. With little knowledge of its molecular mechanisms, we utilized the proteome data of NiV to evaluate the potency of three major proteins (phosphoprotein, polymerase, and nucleocapsid protein) in the RNA-dependent RNA polymerase complex to count as a possible candidate for epitope-based vaccine design. Profound computational analysis was used on the above proteins individually to explore the T-cell immune properties like antigenicity, immunogenicity, binding to major histocompatibility complex class I and class II alleles, conservancy, toxicity, and population coverage. Based on these predictions the peptide ‘ELRSELIGY’ of phosphoprotein and ‘YPLLWSFAM’ of nulceocapsid protein were identified as the best-predicted T-cell epitopes and molecular docking with human leukocyte antigen-C (HLA-C*12:03) molecule was effectuated followed by validation with molecular dynamics simulation. The B-cell epitope predictions suggest that the sequence positions 421 to 471 in phosphoprotein, 606 to 640 in polymerase and 496 to 517 in nucleocapsid protein are the best-predicted regions for B-cell immune response. However, the further experimental circumstance is required to test and validate the efficacy of the subunit peptide for potential candidacy against NiV.     

Epitope Based Peptide Prediction from Proteome of Enterotoxigenic <Emphasis Type="Italic">E.coli</Emphasis>

Enterotoxigenic Escherichia coli causes diarrhea mostly in children under the age of 5 years in developing countries as well as individuals travelling to endemic regions. Every year globally there are 1.7 million cases of diarrhea, at present there are no available vaccines for ETEC therefore demand of an effective vaccine is urgently needed to recuperate diarrhea. So here, we are emphasizing on immuno-informatics approaches to develop an epitope-based vaccine against a global threat disease diarrhea. In this study, 4915 proteins of enterotoxigenic Escherichia coli proteome were screened for the identification of potential antigens that can be used as a good vaccine candidate. Binding of the promiscuous epitopes with Major Histocompatibility Complex (MHC) class I molecules, antigenicity, allergenicity, adhesion properties, population coverage, epitope conservancy and toxicity of the predicted epitopes were analyzed. Three epitopes NAIIFSPLL, AQTNNGQAN and ATDAAGSAR were found most antigenic in comparison to other epitopes predicted with the highest VaxiJen score above 1.7. Further the binding stability of the epitope and allele complex were validated by using in silico docking study. The epitope NAIIFSPLL and ATDAAGSAR have shown the highest binding score of ?4.5 and ?4.16 kcal/mol with HLA-B*5102 and HLA-A*6810 MHC class I allele, respectively. These two predicted epitopes are considered to have high potential to trigger a T cell-mediated immune response and could be a good choice in designing epitope-based vaccines against enterotoxigenic Escherichia coli after further investigation. Thus, in silico analysis results recommended the future development of an epitope vaccine that would be helpful in controlling the diarrheal infections worldwide.     

Immunoinformatic Identification of Potential Epitopes Against Shigellosis

Diarrhoeal diseases due to Shigellosis account for deaths of ~1.5 million children every year in developing countries. Outer membrane proteins (OMPs) of Gram negative bacteria have been shown to be excellent subunit vaccine candidates against various pathogens. However, effective immune response can be generated using specific immunogenic determinants or peptides instead of whole protein or pathogen. In the present study, we chose six OMPs of Shigella flexneri 2a to predict peptides with good antigenic potential. Various tools were used in a systematic flow to predict B- and T-cell epitopes. Stringent selection criteria were used for epitope screening to ensure generation of both arms of immunity. These epitopes are predicted to be effective against a significantly large population of the diarrhoea afflicted countries in Southeast Asia. Most of the predicted epitopes are located towards the outer exposed region of proteins. The epitopes were docked with respective MHC Class I and II molecules to study peptide–MHC interactions. In conclusion, we have predicted an epitope ensemble against Shigellosis which can be experimentally validated for its immunogenic efficacy. We also propose a systematic workflow for immune-optimization to design effective peptide vaccines.     

Prediction of Epitope-Based Peptides for Vaccine Development from Coat Proteins GP2 and VP24 of Ebola Virus Using Immunoinformatics

This study aims to design epitope-based peptides for the utility of vaccine development by targeting Glycoprotein 2 (GP2) and Viral Protein 24 (VP24) of the Ebola virus (EBOV) that, respectively, facilitate attachment and fusion of EBOV with host cells. Using various databases and tools, immune parameters of conserved sequences from GP2 and VP24 proteins of different strains of EBOV were tested to predict probable epitopes. Binding analyses of the peptides with major histocompatibility complex (MHC) class I and class II molecules, population coverage, and linear B cell epitope prediction were peroformed. Predicted peptides interacted with multiple MHC alleles and illustrated maximal population coverage for both GP2 and VP24 proteins, respectively. The predicted class-I nonamers, FLYDRLAST, LFLRATTEL and NYNGLLSSI were found to cover the maximum number of MHC I alleles and showed interactions with binding energies of ?7.8, ?8.5 and ?7.7 kcal/mol respectively. Highest scoring class II MHC binding peptides were EGAFFLYDRLASTVI and SPLWALRVILAAGIQ with binding energies of ?6.2 and -5.6 kcal/mol. Putative B cell epitopes were also found on 4 conserved regions in GP2 and two conserved regions in VP24. Our in silico analysis suggests that the predicted epitopes could be a better choice as universal vaccine component against EBOV irrespective of different strains and should be subjected to in vitro and in vivo analyses for further research and development.     

HLA-DP2 binding prediction by molecular dynamics simulations

Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the "single amino acid substitution" approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.     

Design of a heterosubtypic epitope-based peptide vaccine fused with hemokinin-1 against influenza viruses

Influenza viruses continue to emerge and re-emerge, posing new threats for public health. Control and treatment of influenza depends mainly on vaccination and chemoprophylaxis with approved antiviral drugs. Identification of specific epitopes derived from influenza viruses has significantly advanced the development of epitope-based vaccines. Here, we explore the idea of using HLA binding data to design an epitope-based vaccine that can elicit heterosubtypic T-cell responses against circulating H7N9, H5N1, and H9N2 subtypes. The hemokinin-1(HK-1) peptide sequence was used to induce immune responses against the influenza viruses. Five conserved high score cytotoxic T lymphocyte(CTL) epitopes restricted to HLA-A*0201-binding peptides within the hemagglutinin(HA) protein of the viruses were chosen, and two HA CTL/HK-1 chimera protein models designed. Using in silico analysis, which involves interferon epitope scanning, protein structure prediction, antigenic epitope determination, and model quality evaluation, chimeric proteins were designed. The applicability of one of these proteins as a heterosubtypic epitopebased vaccine candidate was analyzed.     

MHC class I bound to an immunodominant Theileria parva epitope demonstrates unconventional presentation to T cell receptors

T cell receptor (TCR) recognition of peptide-MHC class I (pMHC) complexes is a crucial event in the adaptive immune response to pathogens. Peptide epitopes often display a strong dominance hierarchy, resulting in focusing of the response on a limited number of the most dominant epitopes. Such T cell responses may be additionally restricted by particular MHC alleles in preference to others. We have studied this poorly understood phenomenon using Theileria parva, a protozoan parasite that causes an often fatal lymphoproliferative disease in cattle. Despite its antigenic complexity, CD8+ T cell responses induced by infection with the parasite show profound immunodominance, as exemplified by the Tp1(214-224) epitope presented by the common and functionally important MHC class I allele N*01301. We present a high-resolution crystal structure of this pMHC complex, demonstrating that the peptide is presented in a distinctive raised conformation. Functional studies using CD8+ T cell clones show that this impacts significantly on TCR recognition. The unconventional structure is generated by a hydrophobic ridge within the MHC peptide binding groove, found in a set of cattle MHC alleles. Extremely rare in all other species, this feature is seen in a small group of mouse MHC class I molecules. The data generated in this analysis contribute to our understanding of the structural basis for T cell-dependent immune responses, providing insight into what determines a highly immunogenic p-MHC complex, and hence can be of value in prediction of antigenic epitopes and vaccine design.     

Peptide binding inhibits aggregation of soluble MHC class II in solution

Affinity-purified major histocompatability complex (MHC) class II molecules are known to bind antigenic peptide in vitro. This peptide-bound MHC class II is known to undergo a change in structure upon stable binding of antigenic peptide. Previous results from our, and other laboratories, have suggested a relationship between MHC class II structure and peptide association that enables class II to enter into a stable conformation upon peptide binding. In this report we describe that stable binding of high-affinity antigenic peptide to MHC class II molecule results in transition of aggregated purified MHC class II proteins to a stable heterodimeric state. Such transition was demonstrated by using purified human HLA-DR2 class II molecule and high-affinity myelin basic protein (MBP) 83-102)Y83 peptide. Highly aggregated purified DR2 (high molecular weight; HMW) was first separated from heterodimer (low molecular weight: LMW) in the presence of 50-fold molar excess of MBP(83-102)Y83 peptide. We then show that the aggregated HMW preparation can be successfully converted into a stable dimer by further incubation with MBP(83-102)Y83 and changing various binding parameters such as pH, temperature, reducing agent, and peptide concentrations. Under optimized conditions, the highly aggregated inactive DR2 molecules can be completely loaded with the antigenic peptide. The transformed heterodimers with bound peptide prepared by this method are biologically active, as shown by their ability to induce the production of gamma-interferon by SS8T-transformed human T cells. These results suggest that in solution, MHC class II molecules may be aggregated in the absence of bound peptide. Such aggregated MHC class II molecules can be converted to stable and biologically active heterodimers in the presence of high-affinity antigenic peptide.     

Sequence and Structure Based Binding Prediction Study of HLA Class I and cTAP Binding Peptides for Japanese Encephalitis Vaccine Development

Japanese encephalitis is a major threat in developing countries, even the availability of several conventional vaccines, which demand development of more effective vaccines. The present study used propred I and Immune Epitope Database Artificial Neural Network (ANN) algorithm (IEDB-ANN) to identify the conserve and promiscuous T cell epitopes from JEV proteome followed by structure based analysis of potential epitopes. Among all identified 102 epitopes, ten epitope were promiscuous but two epitopes of glycoprotein viz. ⁵⁵LVTVNPFVA⁶³ and ³⁸IPIVSVASL⁴⁶ were found most promiscuous, highly conserved and high population coverage in comparison of known antigenic positive control peptides. The B cell epitopes of glycoprotein also share these two T cell epitopes revealed by BCPred algorithm which can be a basis to confer the protection by neutralizing antibody combined with an effective cell-mediated response. Further, Autodock 4.2 and NAMD–VMD molecular dynamics simulation were used for docking and molecular dynamics simulation respectively, to validate epitope and allele complex binding stability. The 3D structure models were generated for epitopes and corresponding HLA allele by Pepstr and Modeller 9.10 respectively. Epitope LVTVNPFVA–B5101 allele complex showed best energy minimization and stability over the time window during simulation. Here we also present the binding sequel of epitope LVTVNPFVA and its eventual transport through cTAP1 (PDB ID: 1JJ7) revealed by Autodock 4.2, which is an essential path for HLA class I binding epitopes to elicit immune response. The docking experiment of epitope LVTVNPFVA and cTAP1 very well show a 2 H-bond with a binding energy of ?1.88 kcal/mol and other binding state of epitope forming no H-bond with a binding energy of ?1.13 kcal/mol in the lower area of cTAP1 cavity. These results show a smooth pass through of the epitope across the channel of cTAP1. Overall, identified peptides have potential application in the design and development of short peptide based vaccines and diagnostic agents for Japanese encephalitis.     

Selection of T-cell epitopes from foot-and-mouth disease virus reflects the binding affinity to different cattle MHC class II molecules

The major histocompatibility complex (MHC)-restricted selection of T-cell epitopes of foot-and-mouth disease virus (FMDV) by individual cattle MHC class II DR (BoLA-DR) molecules was studied in a direct MHC-peptide binding assay. By in vitro priming of T lymphocytes derived from animals homozygous for both MHC class I and II, five T-cell epitopes were analyzed in the context of three MHC class II haplotypes. We found that the presentation of these T-cell epitopes was mediated by DR molecules, since blocking this pathway of antigen presentation using monoclonal antibody TH14B completely abolished the proliferative responses against the peptides. To study the DR-restricted presentation of these T-cell epitopes, a direct MHC-peptide binding assay on isolated cattle DR molecules was developed. Purified cattle MHC class II DR molecules of the BoLA-DRB3*0201, BoLA-DRB3*1101, and BoLA-DRB3*1201 alleles were isolated from peripheral blood mononuclear cells. For each allele, one of the identified T-cell epitopes was biotinylated, and used as a marker peptide for the development of a competitive MHC-peptide binding assay. Subsequently, the T-cell epitopes of FMDV with functionally defined MHC class II specificity were analyzed in this binding assay. The affinity of the epitopes to bind to certain DR molecules was significantly correlated to the capacity to induce T-cell proliferation. This demonstrated at the molecular level that the selection of individual T-cell epitopes found at the functional level was indeed the result of MHC restriction.     

Monoclonal antibodies specific for the empty conformation of HLA-DR1 reveal aspects of the conformational change associated with peptide binding

Class II major histocompatibility complex (MHC) proteins bind peptides and present them at the cell surface for interaction with CD4+ T cells as part of the system by which the immune system surveys the body for signs of infection. Peptide binding is known to induce conformational changes in class II MHC proteins on the basis of a variety of hydrodynamic and spectroscopic approaches, but the changes have not been clearly localized within the overall class II MHC structure. To map the peptide-induced conformational change for HLA-DR1, a common human class II MHC variant, we generated a series of monoclonal antibodies recognizing the beta subunit that are specific for the empty conformation. Each antibody reacted with the empty but not the peptide-loaded form, for both soluble recombinant protein and native protein expressed at the cell surface. Antibody binding epitopes were characterized using overlapping peptides and alanine scanning substitutions and were localized to two distinct regions of the protein. The pattern of key residues within the epitopes suggested that the two epitope regions undergo substantial conformational alteration during peptide binding. These results illuminate aspects of the structure of the empty forms and the nature of the peptide-induced conformational change.     

MHC binding peptides for designing of vaccines against Japanese encephalitis virus: A computational approach

Japanese encephalitis (JE), a viral disease has seen a drastic and fatal enlargement in the northern states of India in the current decade. The better and exact cure for the disease is still in waiting. For the cause an in silico strategy in the development of the peptide vaccine has been taken here for the study. A computational approach to find out the Major Histocompatibility Complex (MHC) binding peptide has been implemented. The prediction analysis identified MHC class I (using propred I) and MHC class II (using propred) binding peptides at an expectable percent predicted IC (50) threshold values. These predicted Human leukocyte antigen [HLA] allele binding peptides were further analyzed for potential conserved region using an Immune Epitope Database and Analysis Resource (IEDB). This analysis shows that HLA-DRB1*0101, HLA-DRB3*0101, HLA-DRB1*0401, HLA-DRB1*0102 and HLA-DRB1*07:01% of class II (in genotype 2) and HLA-A*0101, HLA-A*02, HLA-A*0301, HLA-A*2402, HLA-B*0702 and HLA-B*4402% of HLA I (in genotype 3) bound peptides are conserved. The predicted peptides MHC class I are ILDSNGDIIGLY, FVMDEAHFTDPA, KTRKILPQIIK, RLMSPNRVPNYNLF, APTRVVAAEMAEAL, YENVFHTLW and MHC class II molecule are TTGVYRIMARGILGT, NYNLFVMDEAHFTDP, AAAIFMTATPPGTTD, GDTTTGVYRIMARGI and FGEVGAVSL found to be top ranking with potential super antigenic property by binding to all HLA. Out of these the predicted peptide FVMDEAHFTDPA for allele HLA-A*02:01 in MHC class I and NYNLFVMDEAHFTDP for allele HLA-DRB3*01:01 in MHC class II was observed to be most potent and can be further proposed as a significant vaccine in the process. The reported results revealed that the immune-informatics techniques implemented in the development of small size peptide is useful in the development of vaccines against the Japanese encephalitis virus (JEV).     

Towards universal structure-based prediction of class II MHC epitopes for diverse allotypes

The binding of peptide fragments of antigens to class II MHC proteins is a crucial step in initiating a helper T cell immune response. The discovery of these peptide epitopes is important for understanding the normal immune response and its misregulation in autoimmunity and allergies and also for vaccine design. In spite of their biomedical importance, the high diversity of class II MHC proteins combined with the large number of possible peptide sequences make comprehensive experimental determination of epitopes for all MHC allotypes infeasible. Computational methods can address this need by predicting epitopes for a particular MHC allotype. We present a structure-based method for predicting class II epitopes that combines molecular mechanics docking of a fully flexible peptide into the MHC binding cleft followed by binding affinity prediction using a machine learning classifier trained on interaction energy components calculated from the docking solution. Although the primary advantage of structure-based prediction methods over the commonly employed sequence-based methods is their applicability to essentially any MHC allotype, this has not yet been convincingly demonstrated. In order to test the transferability of the prediction method to different MHC proteins, we trained the scoring method on binding data for DRB1*0101 and used it to make predictions for multiple MHC allotypes with distinct peptide binding specificities including representatives from the other human class II MHC loci, HLA-DP and HLA-DQ, as well as for two murine allotypes. The results showed that the prediction method was able to achieve significant discrimination between epitope and non-epitope peptides for all MHC allotypes examined, based on AUC values in the range 0.632-0.821. We also discuss how accounting for peptide binding in multiple registers to class II MHC largely explains the systematically worse performance of prediction methods for class II MHC compared with those for class I MHC based on quantitative prediction performance estimates for peptide binding to class II MHC in a fixed register.     

Molecular detection and cloning of thermostable hemolysin gene from Aeromonas hydrophila

Aeromonas hydrophila is a major bacterial pathogen associated with hemorrhagic septicemia in aquatic and terrestrial animals including humans. There is an urgent need to develop molecular and immunological assays for rapid, specific and sensitive diagnosis. A new set of primers has been designed for detection of thermostable hemolysin (TH) gene (645 bp) from A. hydrophila, and sensitivity limit for detection of TH gene was 5 pg. The TH gene was cloned, sequenced and analyzed. The G+C content was 68.06%; and phylogeny was constructed using TH protein sequences which had significant homology with those for thermostable and other hemolysins present in several bacterial pathogens. In addition, we have predicted the four and eight T-cell epitopes for MHC class I and II alleles, respectively. These results provide new insight for TH protein containing antigenic epitopes that can be used in immunoassays and also designing of thermostable vaccines.     

Design of a predicted MHC restricted short peptide immunodiagnostic and vaccine candidate for Fowl adenovirus C in chicken infection

Fowl adenoviruses (FAdVs) are the ethiologic agents of multiple pathologies in chicken. There are five different species of FAdVs grouped as FAdV-A, FAdV-B, FAdV-C, FAdV-D, and FAdV-E. It is of interest to develop immunodiagnostics and vaccine candidate for Peruvian FAdV-C in chicken infection using MHC restricted short peptide candidates. We sequenced the complete genome of one FAdV strain isolated from a chicken of a local farm. A total of 44 protein coding genes were identified in each genome. We sequenced twelve Cobb chicken MHC alleles from animals of different farms in the central coast of Peru, and subsequently determined three optimal human MHC-I and four optimal human MHC-II substitute alleles for MHC-peptide prediction. The potential MHC restricted short peptide epitope-like candidates were predicted using human specific (with determined suitable chicken substitutes) NetMHC MHC-peptide prediction model with web server features from all the FAdV genomes available. FAdV specific peptides with calculated binding values to known substituted chicken MHC-I and MHC-II were further filtered for diagnostics and potential vaccine epitopes. Promiscuity to the 3/4 optimal human MHC-I/II alleles and conservation among the available FAdV genomes was considered in this analysis. The localization on the surface of the protein was considered for class II predicted peptides. Thus, a set of class I and class II specific peptides from FAdV were reported in this study. Hence, a multiepitopic protein was built with these peptides, and subsequently tested to confirm the production of specific antibodies in chicken.     

Structural and Dynamical Insights on HLA-DR2 Complexes That Confer Susceptibility to Multiple Sclerosis in Sardinia: A Molecular Dynamics Simulation Study

Sardinia is a major Island in the Mediterranean with a high incidence of multiple sclerosis, a chronic autoimmune inflammatory disease of the central nervous system. Disease susceptibility in Sardinian population has been associated with five alleles of major histocompatibility complex (MHC) class II DRB1 gene. We performed 120 ns of molecular dynamics simulation on one predisposing and one protective alleles, unbound and in complex with the two relevant peptides: Myelin Basic Protein and Epstein Barr Virus derived peptide. In particular we focused on the MHC peptide binding groove dynamics. The predisposing allele was found to form a stable complex with both the peptides, while the protective allele displayed stability only when bound with myelin peptide. The local flexibility of the MHC was probed dividing the binding groove into four compartments covering the well known peptide anchoring pockets. The predisposing allele in the first half cleft exhibits a narrower and more rigid groove conformation in the presence of myelin peptide. The protective allele shows a similar behavior, while in the second half cleft it displays a narrower and more flexible groove conformation in the presence of viral peptide. We further characterized these dynamical differences by evaluating H-bonds, hydrophobic and stacking interaction networks, finding striking similarities with super-type patterns emerging in other autoimmune diseases. The protective allele shows a defined preferential binding to myelin peptide, as confirmed by binding free energy calculations. All together, we believe the presented molecular analysis could help to design experimental assays, supports the molecular mimicry hypothesis and suggests that propensity to multiple sclerosis in Sardinia could be partly linked to distinct peptide-MHC interaction and binding characteristics of the antigen presentation mechanism.     

Structure-based identification of MHC binding peptides: Benchmarking of prediction accuracy

Identification of MHC binding peptides is essential for understanding the molecular mechanism of immune response. However, most of the prediction methods use motifs/profiles derived from experimental peptide binding data for specific MHC alleles, thus limiting their applicability only to those alleles for which such data is available. In this work we have developed a structure-based method which does not require experimental peptide binding data for training. Our method models MHC-peptide complexes using crystal structures of 170 MHC-peptide complexes and evaluates the binding energies using two well known residue based statistical pair potentials, namely Betancourt-Thirumalai (BT) and Miyazawa-Jernigan (MJ) matrices. Extensive benchmarking of prediction accuracy on a data set of 1654 epitopes from class I and class II alleles available in the SYFPEITHI database indicate that BT pair-potential can predict more than 60% of the known binders in case of 14 MHC alleles with AUC values for ROC curves ranging from 0.6 to 0.9. Similar benchmarking on 29,522 class I and class II MHC binding peptides with known IC(50) values in the IEDB database showed AUC values higher than 0.6 for 10 class I alleles and 9 class II alleles in predictions involving classification of a peptide to be binder or non-binder. Comparison with recently available benchmarking studies indicated that, the prediction accuracy of our method for many of the class I and class II MHC alleles was comparable to the sequence based methods, even if it does not use any experimental data for training. It is also encouraging to note that the ranks of true binding peptides could further be improved, when high scoring peptides obtained from pair potential were re-ranked using all atom forcefield and MM/PBSA method.