T-CELL AND B-CELL EPITOPE PREDICTION FOR MULTI-EPITOPE PEPTIDE VACCINE AGAINST KYASANUR FOREST DISEASE VIRUS

Abstract

Kyasanur Forest Disease Virus (KFDV) is a tick-borne flavivirus that is transmitted to humans through the bite of infected ticks, it endemics primarily in south-western regions of the Indian subcontinent, mainly Karnataka, Kerala, Tamil Nadu, Goa, and Maharashtra. The disease poses a significant public health challenge, with no licensed vaccines currently available for its prevention. KFDV is a seriously underreached virus, despite its high morbidity and mortality rates. This study aims to address this critical gap by employing an in-silico approach to design a peptide-based vaccine against KFDV. Through a systematic in-silico approach involving structural and antigenic analyses, B-cell and T-cell epitope prediction, as well as molecular docking studies, we identified four B-cell epitopes and 11 T-cell epitopes with desirable characteristics such as high affinity, low allergenicity, strong antigenicity, minimal toxicity, stability, and the ability to induce IFN-gamma. Furthermore, molecular docking analyses confirmed the robust binding of the epitopes with their respective MHC alleles. These findings provide valuable insights into potential targets for vaccine development against KFDV. However, further experimental validation and preclinical studies are warranted to evaluate the immunogenicity and protective efficacy of these epitopes. The development of an effective vaccine against KFDV would be crucial in controlling the spread of this disease and safeguarding vulnerable populations at risk of infection.