In-silico design of an Epitope-based peptide vaccine: A Computational Biology Approach

Tammanna Ravee Sahrawat

Abstract


Lymphocytic choriomeningitis, is a rodent-borne viral infectious disease caused by Lymphocytic choriomeningitis virus (LCMV), a member of the family Arenaviridae, that was initially isolated in 1933. Acquired postnatal infection ranges from asymptomatic to a brief, nonspecific flu-like illness to critical self-resolving neurological disease, predominantly consisting of aseptic meningitis or meningoencephalitis. This study was undertaken to design an epitope-based peptide vaccine against Lymphocytic choriomeningitis virus using a computational biology approach. Twenty four sequences of LCMV were retrieved from UniProt database and analyzed with various in silico tools. VaxiJen was used to identify immunogenic peptides and T-cell epitopes were analysed using NetCTL server to identify T-cell epitopes. Out of 15 immunogenic peptides analysed using NetCTL server, a conservancy of 64.28% amongst all epitopes was observed. The peptide sequence VVQNLDQLY, a non-allergen, was found to be a potent T-cell epitope that interacted with 28 human leukocyte antigens (HLAs) and its interaction with HLA-A*02:06 was studied using protein-protein docking analysis. The HLA allele and the epitope VVQNLDQLY were found to effectively interact with each other and this epitope may be used as a vaccine against LCMV. Thus immunoinformatics based approaches can be used to predict vaccine candidates against pathogens in a timely manner and usher us into an era of T-cell based novel vaccinomics approach.


Keywords


Vaccinomics, In-silico, T-cell epitope, protein-protein docking, allergenecity

Full Text:

PDF

References


Poland GA, Ovsyannikova IG, Jacobson RM. Application of pharmacogenomics to vaccine, Pharmacogenomics. 2009; 10(5): 837–852.

Flower DR. Bioinformatics for Vaccinology. Chichester: John Wiley & Sons, Ltd.

Bourdette DN, Edmonds E, Smith C, et al. A highly immunogenic trivalent T-cell receptor peptide vaccine for multiple sclerosis. Mult Scler. 2005; 11(5): 552–561.

López JA, Weilenman C, Audran R, et al. A synthetic malaria vaccine elicits a potent CD8(+) and CD4(+) T lymphocyte immune response in humans. Eur J Immunolgy. 2001; 31(7): 1989–1998.

Knutson KL, Schiffman K, Disis ML. Immunization with a HER-2/neu helper peptide vaccine generates HER-2/neu CD8 T-cell immunity in cancer patients. J Clin Invest. 2001; 107(4): 477–484.

Petrovsky N, Brusic V. Computational immunology: The coming of age. Immunol Cell Biology. 2002; 80(3): 248–254.

Brusic V, Bajic VB, Petrovsky N. Computational methods for prediction of T-cell epitopes – a framework for modelling, testing, and applications. Methods. 2002; 34(4): 436–443.

Peters B, Bulik S, Tampe R, Van Ender PM, Holzhütter HG. Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors. J Immunology. 2002; 171(4): 1741–1749.

Bhasin M, Raghava GP. Analysis and prediction of affinity of TAP binding peptides using cascade SVM. Protein Science. 2004; 13(3): 596–607.

Nielsen M, Lundegaard C, Lund O, Keşmir C. The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage. Immunogenetics. 2005; 57(1–2): 33–41.

Ovsyannikova IG, Poland GA. Vaccinomics: current findings, challenges and novel approaches for vaccine development. Expub. 2011; 13(3): 438-44.

Daniel J, Bonthius. Lymphocytic choriomeningitis virus: An under-recognized cause of neurologic disease in the fetus, child, and adult. Semin Pediat Neurology. 2012; 19(3): 89–95.

Shrestha B, Diamond MS. Role of CD8+ T-cells in control of West Nile virus infection. J Virol. 2004; 78(15):8312–8321.

UniProt: a hub for protein information. Nucl. Acids Res. 2015; 43 (D1): D204-D212.

Sievers F, Higgins DG. Clustal Omega, accurate alignment of very large numbers of sequences. Methods Mol Biology. 2014; 10(7): 105-16.

Irini A, Doytchinova, Darren R Flower. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics. 2007; 8(4).

Larsen MV, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M. Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinformatics. 2007; 8:424.

Buus S, Lauemøller SL, Worning P, et al. Sensitive quantitative predictions of peptide-MHC binding by a ‘Query by Committee’ artificial neural network approach. Tissue Antigens. 2003; 62(5): 378–384.

Peters B, Sette A. Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics. 2005; 6:132.

Bui HH, Sidney J, Li W, Fusseder N, Sette A. Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines, BMC Bioinformatics. 2007; 8(1): 361.

Dimitrov I, Bangov I, Flower DR, Doytchinov I. AllerTOP v.2--a server for in silico prediction of allergens. J Mol Model. 2014; 20(6): 2278.

Sudipto Saha and G. P. S. Raghava. AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Research. 2006; Vol. 34.

Ambrish Roy, Alper Kucukural, Yang Zhang. I-TASSER: a unified platform for automated protein structure and function prediction. 2010; 5(4): 725–738.

Eisenberg D, Lüthy R, Bowie JU. VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymology. 1997; 277: 396-404.

Dina Schneidman, Duhovny Yuval, Inbar Ruth, Nussinov Haim, J. Wolfson . PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Research. 2005; 33: W363–W367.

Pierce BG, Wiehe K, Hwang H, Kim BH, Vreven T, Weng Z. ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers. Bioinformatics. 2014; 30(12): 1771-3.

Rajarshi Maiti, Gary H, Van Domselaar, Haiyan Zhang, David S, Wishart. SuperPose: a simple server for sophisticated structural superposition. Nucleic Acids Research, 2014; W590–W594.