In silico peptide based vaccine against hepatitis C virus

Abstract

Hepatitis C is a severe disease caused by Hepatitis C virus which leads to human fatality and affected 180 million people across the globe. Its chronic infection leads to liver damage and malignant hepatoma. Till now there is no vaccine in the market for this virus. The objective of the study was to predict the best epitope using Bioinformatics tools for designing a vaccine against HCV. Here T-cell epitope was considered since it can recognize only antigen that processes to generate peptide by antigen presenting cell. For selecting the best T cell epitope, the binding energy with the MHC molecule must be high, must have a protease cleavage site, conserved site, motif, good binder with hydrophobic binding pocket and half-life of dissociation must be high. By considering above criteria suitable bioinformatics tools were used to predict the epitopes from NS3, NS5A and NS5B of 3a and 3b genotype. A total of 600 epitopes from different tools for each protein were predicted and from there only 11 efficient epitopes was virtually screened out using protein-protein interaction between MHC-I and MHC-II molecules and their energy. IMYAPTIWV peptide of NS5A protein was found to be the best epitope. The selected epitope for T-cell can further be used for future work in a wet laboratory for the development of vaccine against HCV.