Evolutionary Bioinformatics

Foot-and-mouth disease (FMD), an endemic disease of cloven-hoofed animals, causes an annual economic loss of US$60–150 million in Bangladesh. There is no cross-protection among the foot-and-mouth disease virus (FMDV) serotypes and vaccination escape mutation may happen. Peptide vaccine is a safer alternative. The aim of this study is to predict and map the B and T cell epitopes of VP1 proteins of FMDV serotypes O and A that were circulating in Bangladesh from 2011 to 2013. Using evolutionary and computational approach (BCPred, BepiPred, DiscoTope, ElliPro, and ProPred-I, IEDB analysis for MHC-I prediction), a total of 11 B and T cell epitopes were predicted. Also, the three-dimensional (3D) structure of VP1 protein showed that the predicted five epitopes residing on N- and C-termini can be considered as good vaccine candidates, and epitopes on the G–H loop can serve as receptor recognition sites for vaccine design. The scores of predicted epitopes of one method were cross-checked with other one for potential epitope mining. Within the VP1 antigenic sites, significant evidence of positive selection was present indicating evolution of VP1 under high immune surveillance.