Implementation of in silico methods to predict common epitopes for vaccine development against Chikungunya and Mayaro viruses

Abstract Being a Positive sense RNA virus the recent reemergence of Chikungunya and Mayaro virus has taken the concern of the leading scientific communities of the world. Though the outbreak of Mayaro virus is limited to Neotropical region only, Chikungunya is already identified in over 60 countries around the world. Besides, the lack of a strong protective treatment, misdiagnosis issue and co-circulation of both the viruses calls for a new strategy which could potentially prevent these infections from spreading. In this study, we therefore, identified the peptide based vaccine candidates e.g. epitopes for B cell and T cell from Chikungunya virus which also showed to be homologous to the Mayaro virus through immuno-informatics and computational approaches. Final epitopes identified from the most antigenic structural polyprotein of both the viruses were 5 for CD8+ T cell Epitopes (209KPGDSGRPI217, 219TGTMGHFIL227, 239ALSVVTWNK247, 98KPGRRERMC106 and 100GRRERMCMK108), 2 epitopes for CD4+ T cell (105MCMKIENDCIFEVKH119 and 502DRTLLSQQSGNVKIT516) and a single epitope for B cell (504GGRFTIPTGAGKPGDSGRPI518). Analysis of our predicted epitopes for population coverage showed prominent population coverage (92.43%) around the world. Finally, molecular docking simulation of the foreseen T cell epitopes with respondent HLA alleles secured good HLA-epitope interaction. This study was directed towards the discovery of potential antigenic epitopes which can open up a new skyline to design novel vaccines for combating both of the diseases at the same time.