Computational screening of potential MHC class I restricted cytotoxic T lymphocytes-based common multi-epitopes of major arboviral diseases

Abstract

Aim: Arboviral diseases are a health hazard and Flavivirus and Alphavirus infections are the most common in humans. This study focuses on immunoinformatic approaches to identify potential MHC class I restricted epitopes common for some selected arboviral diseases. Materials & methods: T-cell epitope prediction tool of Immune Epitope Database was employed to identify putative epitopes from the polyproteins of the selected viruses. Further, population coverage, conservancy, antigenic properties and docking analyses were performed to identify potential common epitopes for the selected viruses. Results: Eight common epitopes were screened for the selected viruses based on their population coverage, conservancy, antigenic properties and binding affinity. Conclusion: Considering the in silico potency, identified epitopes may further be subjected for candidate vaccine development against these arboviruses.