In silico T-cell and B-cell Epitope Based Vaccine Design Against Alphavirus Strain of Chikungunya

Page: [523 - 530] Pages: 8

  • * (Excluding Mailing and Handling)

Abstract

Background: Chikungunya an arbovirus, is transmitted to humans by the bite of Aedes mosquito. The virus occurrences have been reported in Southeast Asian countries including Pakistan. Its symptoms include typical febrile illness and arthralgic syndrome. The virus has not decisively proved to be life-threatening.

Methods: The attempt was to design T-cell and B-cell epitope-based vaccine for Chikungunya. The proteome of chikungunya was retrieved, antigenic proteins were identified and T-cell epitopes and B-cell epitopes were predicted. Interacting HLA alleles were also identified. The final analysis was done to confirm that predicted T-cell epitopes and B-cell epitopes can be used as a vaccine.

Results: About 32 T-cell epitopes and a 10mer B-cell epitope were identified. Both T-cell and Bcell epitopes demonstrated strong interactions with HLA alleles. The predicted T-cell and B-cell epitopes were docked with respective HLA alleles. The docking analysis showed that the predicted respective epitopes best fit into the binding pockets of the alleles.

Conclusion: On the basis of this computational analysis, it is suggested that these predicted epitopes can be used as a remedy against Alphavirus strain of chikungunya. Further laboratory experiments can be conducted to determine the efficacy and stability of this work.

Keywords: T-cell epitope, B-cell epitope, Chikungunya, HLA allele, arthralgic syndrome, Alphavirus strain.

[1]
Powers, A.M.; Logue, C.H. Changing patterns of chikungunya virus: re-emergence of a zoonotic arbovirus. J. Gen. Virol., 2007, 88(Pt 9), 2363-2377.
[http://dx.doi.org/10.1099/vir.0.82858-0] [PMID: 17698645]
[2]
Khan, A.H.; Morita, K. Parquet Md, Mdel.C.; Hasebe, F.; Mathenge, E.G.; Igarashi, A. Complete nucleotide sequence of chikungunya virus and evidence for an internal polyadenyla-tion site. J. Gen. Virol., 2002, 83(Pt 12), 3075-3084.
[http://dx.doi.org/10.1099/0022-1317-83-12-3075] [PMID: 12466484]
[3]
Simizu, B.; Yamamoto, K.; Hashimoto, K.; Ogata, T. Structural proteins of Chikungunya virus. J. Virol., 1984, 51(1), 254-258.
[http://dx.doi.org/10.1128/JVI.51.1.254-258.1984] [PMID: 6726893]
[4]
Renault, P.; Solet, J.L.; Sissoko, D.; Balleydier, E.; Larrieu, S.; Filleul, L.; Lassalle, C.; Thiria, J.; Rachou, E.; de Valk, H.; Ilef, D.; Ledrans, M.; Quatresous, I.; Quenel, P.; Pierre, V. A major epidemic of chikungunya virus infection on Reunion Island, France, 2005-2006. Am. J. Trop. Med. Hyg., 2007, 77(4), 727-731.
[http://dx.doi.org/10.4269/ajtmh.2007.77.727] [PMID: 17978079]
[5]
Lokireddy, S.; Vemula, S.; Vadde, R. Connective tissue metabolism in chikungunya patients. Virol. J., 2008, 5(1), 31.
[http://dx.doi.org/10.1186/1743-422X-5-31] [PMID: 18302795]
[6]
Patronov, A.; Doytchinova, I. T-cell epitope vaccine design by immunoinformatics. Open Biol., 2013, 3(1), 120139-120139.
[http://dx.doi.org/10.1098/rsob.120139] [PMID: 23303307]
[7]
Anushe, S. In silico B-cell and T-cell epitope-based vaccine designing against Chikungunya virus., 2018.
[8]
Tambunan, Usman Sumo Friend; Feimmy, Ruth Pratiwi Sipahutar; Parikesit, Arli Aditya Kerami, Djati Vaccine design for H5N1 based on B-and T-cell epitope predictions Bioinformatics and Biology insights, 2016, 10, BBI-S38378..
[http://dx.doi.org/10.4137/BBI.S38378]
[9]
Zobayer, N.; Hossain, A.B.B. Journal of Medical Sciences., 2018, 18(1), 34-47.
[http://dx.doi.org/10.3923/jms.2018.34.47]
[10]
Xu, K; Acharya, P; Kong, R; Cheng, C; Chuang, GY; Liu, K; Louder, MK; O’Dell, S; Rawi, R; Sastry, M; Shen, CH Epitopebased vaccine design yields fusion peptide-directed antibodies that neutralize diverse strains of HIV-1. Nature medicine, 2018, 24(6), 857.
[11]
Alonso-Padilla, J; Lafuente, EM; Reche, PA Computer-aided design of an epitope-based vaccine against epstein-barr virus Journal of immunology research, 2017 2017.
[12]
Mallhi, T.H.; Khan, Y.H.; Khan, A.H.; Tanveer, N.; Qadir, M.I. First chikungunya outbreak in Pakistan: a trail of viral attacks. New Microbes New Infect., 2017, 19, 13-14.
[http://dx.doi.org/10.1016/j.nmni.2017.05.008] [PMID: 28663798]
[13]
Rauf, M., Fatima-Tuz-Zahra,; Manzoor, S.; Mehmood, A.; Bhatti, S. Outbreak of chikungunya in Pakistan. Lancet Infect. Dis., 2017, 17(3), 258.
[http://dx.doi.org/10.1016/S1473-3099(17)30074-9] [PMID: 28244384]
[14]
Apweiler, R.; Bairoch, A.; Wu, C.H.; Barker, W.C.; Boeckmann, B.; Ferro, S.; Gasteiger, E.; Huang, H.; Lopez, R.; Magrane, M.; Martin, M.J.; Natale, D.A.; O Donovan, C. Redaschi, N.; Yeh, L.S. UniProt: the Universal Protein knowledgebase. Nucleic Acids Res., 2004, 32(Database issue), D115-D119.
[http://dx.doi.org/10.1093/nar/gkh131] [PMID: 14681372]
[15]
Doytchinova, I.A.; Flower, D.R. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics, 2007, 8(1), 4.
[http://dx.doi.org/10.1186/1471-2105-8-4] [PMID: 17207271]
[16]
Larsen, M.V.; Lundegaard, C.; Lamberth, K.; Buus, S.; Lund, O.; Nielsen, M. Large-scale validation of methods for cytotoxic Tlymphocyte epitope prediction. BMC Bioinformatics, 2007, 8(1), 424.
[http://dx.doi.org/10.1186/1471-2105-8-424] [PMID: 17973982]
[17]
Fieser, T.M.; Tainer, J.A.; Geysen, H.M.; Houghten, R.A.; Lerner, R.A. Influence of protein flexibility and peptide conformation on reactivity of monoclonal anti-peptide antibodies with a protein alpha-helix. Proc. Natl. Acad. Sci. USA, 1987, 84(23), 8568-8572.
[http://dx.doi.org/10.1073/pnas.84.23.8568] [PMID: 2446325]
[18]
Larsen, J.E.P.; Lund, O.; Nielsen, M. Improved method for predicting linear B-cell epitopes. Immunome Res., 2006, 2, 2.
[http://dx.doi.org/10.1186/1745-7580-2-2] [PMID: 16635264]
[19]
Emini, E.A.; Hughes, J.V.; Perlow, D.S.; Boger, J. Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide. J. Virol., 1985, 55(3), 836-839.
[http://dx.doi.org/10.1128/JVI.55.3.836-839.1985] [PMID: 2991600]
[20]
Karplus, P.A.; Schulz, G.E. Prediction of chain flexibility in proteins. Naturwissenschaften, 1985, 72, 212-213.
[http://dx.doi.org/10.1007/BF01195768]
[21]
Kolaskar, A.S.; Tongaonkar, P.C. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett., 1990, 276(1-2), 172-174.
[http://dx.doi.org/10.1016/0014-5793(90)80535-Q] [PMID: 1702393]
[22]
Parker, J.M.R.; Guo, D.; Hodges, R.S. 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, 25(19), 5425-5432.
[http://dx.doi.org/10.1021/bi00367a013] [PMID: 2430611]
[23]
Oseroff, C.; Sidney, J.; Tripple, V.; Grey, H.; Wood, R.; Broide, D.H.; Greenbaum, J.; Kolla, R.; Peters, B. Pom??s, A.; Sette, A. Analysis of T cell responses to the major allergens from German cockroach: epitope specificity and relationship to IgE production. J. Immunol., 2012, 189(2), 679-688.
[http://dx.doi.org/10.4049/jimmunol.1200694] [PMID: 22706084]
[24]
Dimitrov, I.; Flower, D.R.; Doytchinova, I. AllerTOP--a server for in silico prediction of allergens. BMC Bioinformatics, 2013, 14(6)(Suppl. 6), S4.
[http://dx.doi.org/10.1186/1471-2105-14-S6-S4] [PMID: 23735058]
[25]
Guan, P.; Doytchinova, I.A.; Zygouri, C.; Flower, D.R. MHCPred: A server for quantitative prediction of peptide-MHC binding. Nucleic Acids Res., 2003, 31(13), 3621-3624.
[http://dx.doi.org/10.1093/nar/gkg510] [PMID: 12824380]
[26]
Berman, H.M.; Kleywegt, G.J.; Nakamura, H.; Markley, J.L. The future of the protein data bank. Biopolymers, 2013, 99(3), 218-222.
[http://dx.doi.org/10.1002/bip.22132] [PMID: 23023942]
[27]
Meraj, K.; Mahto, M.K.; Christina, N.B.; Desai, N.; Shahbazi, S.; Bhaskar, M. Molecular modeling, docking and ADMET studies towards development of novel Disopyramide analogs for potential inhibition of human voltage gated sodium channel proteins. Bioinformation, 2012, 8(23), 1139-1146.
[http://dx.doi.org/10.6026/97320630081139] [PMID: 23275710]
[28]
Lee, H.; Heo, L.; Lee, M.S.; Seok, C. GalaxyPepDock: a protein peptide docking tool based on interaction similarity and energy optimization. Nucleic Acids Res., 2015, 43(W1)W431-5
[http://dx.doi.org/10.1093/nar/gkv495] [PMID: 25969449]
[29]
Zheng, J.; Lin, X.; Wang, X.; Zheng, L.; Lan, S.; Jin, S.; Ou, Z.; Wu, J. In Silico Analysis of Epitope-Based Vaccine Can-didates against Hepatitis B Virus Polymerase Protein. Viruses, 2017, 9(5), 112.
[http://dx.doi.org/10.3390/v9050112]