Peptide vaccine prediction against Hepatitis-C virus causing hepatocellular cancer using immunoinformatics approach

Abstract

The prime objective of this study is to predict peptide vaccine against all genotypes of HCV that might be a part of combination therapy. We used bioinformatic approaches to identify the T cell and B cell epitopes having high antigenicity from the envelope glycoproteins E1 and E2 of HCV. For the analysis, HLA-A1, HLA-A*01:01, HLA-A3, HLA-B*2702, HLA-B*2705, HLA-B7, HLA-B8, HLA-Cw*0702, HLA-DRB1*1101, HLA-DRB1*03:01, DRB1*0401 and DRB1*0311 alleles were selected for the prediction of T cell epitopes. Consequently, potential B cell epitopes for each surface protein were predicted i.e., ALYVGMCGA, VNYRNVSGIY, GAAFCSALYV and CGVVSAKTVC. Likewise, T cell peptide epitopes having potential to bind with MHC class I molecule were also identified i.e., AWAKVVVIL, VRYVGATTA, VAPTLAVRY, WEYVVLAFL, WEYIMLVFL, AVKWEYVVL and WEYVVLLFL. Further, T cell epitope capable of binding to MHC class II molecule was identified i.e., VAIIMVMFS, LVLAQVMRI, VVIDIIAGG, LVGSATLCS, VVASATLCS, LLADARVCA, IQLINTNGS, LQLINTNGS and VVLLFLLLA. These peptides are potential candidates for design of vaccine.