Chikungunya virus (CHIKV), responsible for a mosquito-borne viral illness, has rapidly spread worldwide, posing a significant global health threat. In this study, we explored the immunogenic variability of CHIKV envelope 2 (E2), a pivotal component in the anti-CHIKV immune response, using an in silico approach. After extracting the representative sequence types of the CHIKV E2 antigen, we predicted the structure-based B-cell epitopes and MHC I and II binding T-cell epitopes. Variations in key T-cell epitopes were further analyzed using molecular docking simulations. We extracted 258 E2 gene sequences from a pool of 1660 blast hits, displaying homology levels ranging from 93.6% to 100%. This revealed 44 sequence types, each representing a unique genetic variant. Phylogenetic analysis revealed distinct geographically distributed clonal lineages (clades I-IV). The B-cell linear and discontinuous epitopes demonstrated a similar distribution across the E2 protein of different strains, spanning domains A, B, and C, with some slight variations. Moreover, T-cell epitope prediction revealed eight conserved MHC class I hot spots and three MHC II hot spots, displaying variations among lineages. Among clade II strains, there were significant variations (N5H, S118G, G194S, L248F/S, and I255V/T) observed in epitopes, distinct from strains belonging to other lineages. Additionally, molecular docking showed that variations in MHC I epitopes across clonal lineages induced changes in the structure of the peptide-MHC complexes, potentially resulting in immunogenic disparities. We expect that this in silico approach will serve as a complementary tool to experimental platforms for exploring immunogenic variation or developing biomarkers for vaccine design and other related studies.
Keywords: Alphavirus; Chikungunya virus; MHC binding epitopes; chikungunya fever; envelope 2; in silico approach; molecular docking.