Rational design of multi-epitope vaccine for Chandipura virus using an immunoinformatics approach

Abstract

Chandipura virus (CHPV) is endemic in India, with frequent outbreaks reported. No approved medicines or vaccines exist for CHPV. We aimed to develop a multi-epitope vaccine for CHPV using immunoinformatics approaches. In this study, a multi-epitope vaccine construct was developed by combining 11 CTL epitopes, 2 HTL epitopes, and 1 linear B-cell epitope from glycoprotein (G) with 1 EAAAK linker, 10 AAY linkers, 2 GPGPG linkers, 1 KK linker, and adjuvant (RS-09 peptide). We predicted and optimized the vaccine’s protein structure. Furthermore, the vaccine 3D structure was docked with Toll-like receptor 4 (TLR4) using the Cluspro 2.0 server, and the docked complex was analyzed using molecular dynamics (MD) simulation by the assisted model building with energy refinement (AMBER) v.20 package. The vaccine’s immune simulation profile was determined, and the vaccine sequence was reverse translated and in silico cloned into the pET28a (+). The vaccine’s population coverage was 99.79% across the worldwide. The vaccine was soluble, non-allergenic and non-toxic, with high levels of antigenicity. The quality of the vaccine’s 3D structure improved following refining, and the number of residues in the most favoured regions of the Ramachandran plot increased by 94.2%. The molecular docking, with a docking score of −1157 kcal/mol, and MD simulation results revealed a robust interaction and remarkable stability between the vaccine and TLR4. The immune response simulation indicated a decrease in antigen levels and an increase in interferon‐gamma (IFN‐γ) and interleukin-2 (IL-2) concentrations after each injection. In silico results indicate that this vaccine possesses significant promise against CHPV; however, laboratory and animal studies are necessary to validate our findings.