In Silico Identification of Epitope-Based Peptide Vaccine for Nipah Virus

Abstract

Nipah virus was first appeared in Malaysian 1998, which further found be outburst in neighbor countries i.e. Bangladesh, Singapore, and India. Currently there is no effective drug or vaccine available only supportive care and prevention are way to manage it. Epitope based vaccine could be the best way to cure Nipah virus infection. In this study, the proteome of Nipah virus was retrieve from UniProt database and were subjected to check for allergenicity using Allergen FP v.1.0 tool. NetMHCII 2.3 server screened epitopes from non-allergen proteins and Vaxijen tool was used to identify the most antigenic epitopes binds with MHC class II molecules. Two potent T cell epitopes LLFVFGPNL and KYKIKSNPL were found, which binds with HLA-DRB1*01:01 and HLA-DRB1*07:01 MHC class II alleles. PepstrMod and Swiss-Model server were used to build 3D structure model of epitopes and alleles, respectively. Further identified epitopes were docked with HLA alleles using AutoDock vina tool to confirm binding ability. The epitopes LLFVFGPNL and KYKIKSNPL had binding affinity of − 8.1 kcal/mol and − 5.7 kcal/mol with HLA-DRB1*01:01 and HLA-DRB1*07:01 alleles, respectively. Solidity of predicted epitope—allele docked complex were evaluating by molecular dynamics simulation.HLA distribution analysis was performed for predicted epitopes using the population coverage tool of Immune Epitope Database (IEDB). These predicted epitopes cover maximum number of populations in India as well as worldwide. Therefore, these epitopes could be potent vaccine candidates to counter Nipah virus by testing in wet lab.