In-silico design of an Epitope-based peptide vaccine: A Computational Biology Approach

Abstract

Lymphocytic choriomeningitis, is a rodent-borne viral infectious disease caused by Lymphocytic choriomeningitis virus (LCMV), a member of the family Arenaviridae, that was initially isolated in 1933. Acquired postnatal infection ranges from asymptomatic to a brief, nonspecific flu-like illness to critical self-resolving neurological disease, predominantly consisting of aseptic meningitis or meningoencephalitis. This study was undertaken to design an epitope-based peptide vaccine against Lymphocytic choriomeningitis virus using a computational biology approach. Twenty four sequences of LCMV were retrieved from UniProt database and analyzed with various in silico tools. VaxiJen was used to identify immunogenic peptides and T-cell epitopes were analysed using NetCTL server to identify T-cell epitopes. Out of 15 immunogenic peptides analysed using NetCTL server, a conservancy of 64.28% amongst all epitopes was observed. The peptide sequence VVQNLDQLY, a non-allergen, was found to be a potent T-cell epitope that interacted with 28 human leukocyte antigens (HLAs) and its interaction with HLA-A*02:06 was studied using protein-protein docking analysis. The HLA allele and the epitope VVQNLDQLY were found to effectively interact with each other and this epitope may be used as a vaccine against LCMV. Thus immunoinformatics based approaches can be used to predict vaccine candidates against pathogens in a timely manner and usher us into an era of T-cell based novel vaccinomics approach