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H1N1 Influenza virus, otherwise known as swine flu is one of the subtypes of influenza A virus. The H1N1 flu spreads rapidly from human to human while sneezing and coughing. It was announced as a global pandemic by the World Health Organization (WHO) in 2009. Although the influenza virus has some effective vaccines, the H1N1 subtype of the virus does not have a low-cost and safest vaccine. The peptide-based vaccine design does not involve the in vitro culturing of the pathogenic virus and also, it is a cost and time-saving technology. This study aims at identifying the potential epitope through the available immunoinformatics tools. Among the 11 proteins of H1N1, approximately 22 epitopes are predicted. Two of these epitopes showed good interactions with various MHC alleles. Hence the 3D structure of the epitopes and HLA protein were built. The best two epitopes LSTASSWSY and VSFNQNLEY are from the structural proteins of the H1N1 virus namely Haemagglutinin and Neuraminidase. The surface proteins are the best targets for vaccine design. The molecular docking result and pose view of the interaction of HLA and the epitopes suggests LSTASSWSY as the more stable and potential epitope for vaccine designing since it has a good binding affinity -7.71 kcal/mol and also has both hydrogen and hydrophobic interactions with the HLA protein. This study can hopefully be a lead for the vaccine design for the H1N1 virus.
Akila Kannaiyan, In silico docking studies of selective natural inhibitor against PB1 protein of Influenza A (H1N1) virus, International Journal of Pharmacy and Biological Sciences 8 (4), 214-219.
Akila K. Insilico analysis of PB1 Protein of Influenza A Virus. Int J Pharma Bio Sci. 2017 Jul;8(3):140-4
Ezaj MMA, Junaid M, Akter Y, Nahrin A, Siddika A, Afrose SS, Nayeem SMA, Haque MS, Moni MA, Hosen SMZ. Whole proteome screening and identification of potential epitopes of SARS-CoV-2 for vaccine design-an immunoinformatic, molecular docking and molecular dynamics simulation accelerated robust strategy. J Biomol Struct Dyn. 2021 Feb 15:1-26.
Sanchez-Trincado JL, Gomez-Perosanz M, Reche PA. Fundamentals and Methods for T- and B-Cell Epitope Prediction. J Immunol Res. 2017;2017:2680160.
Bahrami AA, Payandeh Z, Khalili S, Zakeri A, Bandehpour M. Immunoinformatics: In Silico Approaches and Computational Design of a Multi-epitope, Immunogenic Protein. Int Rev Immunol. 2019;38(6):307-322.
Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJ. The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc. 2015 Jun;10(6):845-58.
Khalili S, Jahangiri A, Borna H, Ahmadi Zanoos K, Amani J. Computational vaccinology and epitope vaccine design by immunoinformatics. Acta Microbiol Immunol Hung. 2014 Sep;61(3):285-307.
Purcell AW, McCluskey J, Rossjohn J. More than one reason to rethink the use of peptides in vaccine design. Nat Rev Drug Discov. 2007 May;6(5):404-14. doi: 10.1038/nrd2224.
Singh S, Singh H, Tuknait A, Chaudhary K, Singh B, Kumaran S, Raghava GP. PEPstrMOD: structure prediction of peptides containing natural, non-natural and modified residues. Biol Direct. 2015 Dec 21;10:73.
Tenzer S, Peters B, Bulik S, Schoor O, Lemmel C, Schatz MM, Kloetzel PM, Rammensee HG, Schild H, Holzhütter 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 May;62(9):1025-37.
Dudek NL, Perlmutter P, Aguilar MI, Croft NP, Purcell AW. Epitope discovery and their use in peptide based vaccines. Curr Pharm Des. 2010;16(28):3149-57.
Hegde NR, Gauthami S, Sampath Kumar HM, Bayry J. The use of databases, data mining and immunoinformatics in vaccinology: where are we? Expert Opin Drug Discov. 2018 Feb;13(2):117-130.
.Trifonov V, Khiabanian H, Greenbaum B, Rabadan R. The origin of the recent swine influenza A(H1N1) virus infecting humans. Euro Surveill 2009;14:19193.