Prediction of B and T cell epitope-based peptide vaccines from highly conserved regions in Enterovirus D68 capsid protein VP1: a computational approach

Authors

  • Tahirah Yasmin Tahirah Yasmin*1 Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka-1000, Bangladesh

DOI:

https://doi.org/10.56511/JIPBS.2015.v2.i04.pp426-438

Abstract

Objective: Human Enterovirus D-68 (EV-D68) is a historically rarely reported virus linked with respiratory disease. However, in the recent years, a large increase in respiratory disease associated with EV-D68 has been reported, with documented outbreaks in North America, Europe and Asia. This study therefore aims to design specific peptide vaccine(s) against the virus by targeting capsid protein VP1 which plays crucial role in host-pathogen interaction.Material and Methods: Different web-based tools were applied to predict B and T cell epitopes with high accuracy and precision from sequence based analyses of the conserved regions of the capsid protein. Initially MEGA and SWISS-MODEL were used for the sequence and 3D structure analysis respectively. Later, the Immune Epitope Database and Analysis Resource (IEDB-AR), BepiPred and ABCPred servers were used for the identification of T-cell and B-cell epitopes.Results: “INPADT” peptide was found to be the most potential linear B cell epitope which fulfilled all the criteria of accessibility, hydrophilicity, flexibility and beta turn region for becoming an ideal B cell epitope. On the other hand, “YMSIANANY”, “LVSKRSFEY”, “ENFLSRAAL” and “AMFVPTGAL” were found to be most suitable T cell epitopes interacting with a large number of MHC class I and class II alleles. Among them “LVSKRSFEY” and “ENFLSRAAL” had the highest population coverage. All of these epitopes were found non allergen and with 100% conservancy among different strains of EVD-68 worldwide.Conclusion: Based on the present study, it could be concluded that these predicted epitopes may be used to design a vaccine against Enterovirus and thus, can be validated in model hosts to verify their efficacy as vaccine.

           

Keywords:

Epitope, Enterovirus D68, Vaccine, MHC Class I, MHC Class II, T-cell epitopes, B-cell epitopes

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References

Yue Liu, Ju Sheng, Andrei Fokine, Geng Meng, Woong-Hee Shin, Feng Long, Richard J. Kuhn, Daisuke Kihara, and Michael G. Rossmann. Structure and inhibition of EV-D68, a virus that causes respiratory illness in children. Science. 2015 Jan 2; 347(6217): 71 – 74.

Rafal Tokarz , Cadhla Firth , Shabir A. Madhi , Stephen R. C. Howie , Winfred Wu , Amadou Alpha Sall , Saddef Haq , Thomas Briese , and W. Ian Lipkin . Worldwide emergence of multiple clades of enterovirus 68. J Gen Virol. 2012 Sep; 93(Pt 9): 1952 – 1958.

Schieble J. H., Fox V. L., Lennette E. H. A probable new human picornavirus associated with respiratory diseases. Am J Epidemiol ( 1967 ) 85, 297 – 310

Tokarz R, Firth C, Madhi SA, Howie SR, Wu W, Sall AA, Haq S, Briese T, Lipkin WI Worldwide emergence of multiple clades of enterovirus 68. J Gen Virol. 2012;93: 1952 – 1958.

Kreuter JD, et al. A fatal central nervous system enterovirus 68 infection. Arch Pathol Lab Med.2011;135: 793 – 796.

Rueckert RR. In: Virology. Fields BN, Knipe DM, editor. Lippincott-Raven, New York; Picornaviruses and their replication; 1990. pp. 507 – 548.

Helenius A. 2007. Virus entry and uncoating, p P100 – P118 In Knipe DM, Howley PM, Griffin DE, Lamb RA, Martin MA, Roizman B, Straus SE, editors. (ed), Fields virology, 5th ed, vol

Lippincott Williams & Wilkins, Philadelphia, PA

Chen H. F., Chang M. H., Chiang B. L., Jeng S. T. 2006. Oral immunization of mice using transgenic tomato fruit expressing VP1 protein from enterovirus 71. Vaccine 24: 2944 – 2951

E. M. Lafuente and P. A. Reche, “Prediction of MHC-peptide binding: a systematic and comprehensive overview,” Current Pharmaceutical Design, vol. 15, no. 28, pp. 3209 – 3220, 2009.

Hasan MA, Hossain M, and Alam MJ: A Computational Assay to Design an epitopeBased Peptide Vaccine Against Saint Louis Encephalitis Virus. Bioinform Biol Insights 2013, 7: 347 – 355.

Holland J, Domingo E .Origin and evolution of viruses. Virus Genes (1998) 16(1):13 –

Nair DT, Singh K, Siddiqui Z, Nayak BP, Rao KV, Salunke DM. Epitope recognition by diverse antibodies suggests conformational convergence in an antibody response. J Immunol. 2002; 168(5):2371 – 2382

Krogh A, Larsson B, Heijne GV and Sonnhammer ELL: Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. Journal of Molecular Biology2001, vol. 305, no. 3, pp. 567 – 580.

Jens Erik Pontoppidan Larsen, Ole Lund and Morten Nielsen. Improved method for predicting linear B-cell epitopes. Immunome Res. 2006; 2: 2.

Saha, S and Raghava G.P.S. Prediction of Continuous B-cell Epitopes in an Antigen Using Recurrent Neural Network. Proteins, (2006) 65(1),40-48

Fieser TM, John A, Tainer H, et al. Influence of protein flexibility and peptide conformation on reactivity of monoclonal anti-peptide antibodies with a protein ahelix. Proc Natl Acad Sci. 1987; 84(23):8568 – 72.

Emini EA, Hughes JV, Perlow DS, Boger J: Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide. J Virol 1985, 55(3):836-839.

Parker JM, Guo D, Hodges RS: New hydrophilicity scale derived from high performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites. Biochemistry 1986, 23:25.

Karplus PA, Schulz GE: Prediction of Chain Flexibility in Proteins - A tool for the Selection of Peptide Antigens. Naturwissenschafren 1985, 72:212-3.

Chou PY, Fasman GD. Prediction of the secondary structure of proteins from their amino acid sequence. Adv Enzymol Relat Areas Mol Biol. 1978; 47:45 – 148.

Torsten Schwede, Jürgen Kopp, Nicolas Guex, and Manuel C. Peitsch. SWISSMODEL: an automated protein homologymodeling server. Nucleic Acids Res. 2003 Jul 1; 31(13): 3381 – 3385.

Laskowski R A, MacArthur M W, Moss D S, Thornton J M (1993). PROCHECK - a program to check the stereochemical quality of protein structures. J. App. Cryst., 26, 283-291.

Benkert P, Biasini M, Schwede T .Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics(2011) 27(3):343 – 350

Larsen MV, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M. Large-scale validation of methods for cytotoxic Tlymphocyte epitope prediction. BMC Bioinformatics. Oct 31; 8: 424. 2007

Tenzer S, Peters B, Bulik S, Schoor O, Lemmel C, Schatz MM, Kloetzel PM, Rammensee HG, Schild H, and Holzhutter HG. Modeling the MHC class I pathway by combining predictions of proteasomal cleavage, TAP transport and MHC class I binding. Cell Mol Life Sci. 2005 62:10251037.

Bui HH, Sidney J, Dinh K et al .Predicting population coverage of T-cell epitopebased diagnostics and vaccines. BMC Bioinformatics (2006) 17(7):153

Dang, H. X., & Lawrence, C. B.. Allerdictor: Fast allergen prediction using text classification techniques. Bioinformatics, (2014) btu004.

Ward JJ, McGuffin LJ, Bryson K et al. The DISOPRED server for the prediction of protein disorder. Bioinformatics 20 (2004) (13):2138 – 2139

Tadatsugu Imamura and Hitoshi Oshitani. Global reemergence of enterovirus D68 as an important pathogen for acute respiratory infections. Rev Med Virol. 2015 Mar; 25(2): 102 – 114.

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

Oany AR, Emran AA and Jyoti TP: Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach. Drug Des Devel Ther 2014, 8: 1139 – 1149.

Chee Wah Tan, Yoke Fun Chan, Kooi Mow Sim, Eng Lee Tan, and Chit Laa Poh. Inhibition of Enterovirus 71 (EV-71) Infections by a Novel Antiviral Peptide Derived from EV-71 Capsid Protein VP1. PLoS One. 2012; 7(5): e34589.

Shih SR, Tsai MC, Tseng SN, Won KF, Shia KS, et al. Mutation in Enterovirus 71 capsid protein VP1 confers resistance to the inhibitory effects of pyridyl imidazolidinone. Antimicrob Agents Chemother. 2004; 48: 3523 – 3529.

Trost B, Bickis M, Kusalik A: Strength in numbers: achieving greater accuracy in MHCI binding prediction by combining the results from multiple prediction tools. Immunome Res 2007, 3: 5 – 15.

McKeever TM, Lewis SA, Smith C, Hubbard R. Vaccination and allergic disease: a birth cohort study. Am J Public Health. 2004; 94(6):985 – 989.

Published

05-10-2015
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How to Cite

Tahirah Yasmin*1 , T. Y. “Prediction of B and T Cell Epitope-Based Peptide Vaccines from Highly Conserved Regions in Enterovirus D68 Capsid Protein VP1: a Computational Approach”. Journal of Innovations in Pharmaceutical and Biological Sciences, vol. 2, no. 4, Oct. 2015, pp. 426-38, doi:10.56511/JIPBS.2015.v2.i04.pp426-438.

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Research Article