Computational Design and In Silico Evaluation of a Multi-Epitope Vaccine Targeting Conserved Structural Polyproteins of Chikungunya Virus

Chikungunya virus (CHIKV) is an emerging arbovirus for which no licensed vaccine is currently available. In this study, we employed an immunoinformatics-based reverse vaccinology approach to design a novel multi-epitope vaccine (MEV) targeting conserved regions of CHIKV structural polyproteins. Conserved sequences were identified through multiple sequence alignment and used to predict cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes with high antigenicity, non-allergenicity, and broad HLA coverage. The final MEV construct comprised ten CTL, ten HTL, and three B-cell epitopes linked with suitable linkers and an immunogenic adjuvant. Structural modeling and validation confirmed the stability and quality of the vaccine construct. Molecular docking and 200-ns molecular dynamics simulations demonstrated stable and favorable interactions with immune receptors TLR7 and CCR5. In silico immune simulations predicted robust humoral and cellular immune responses with long-term immunological memory. Collectively, these results highlight the novelty and potential of the proposed MEV as a promising CHIKV vaccine candidate, warranting further experimental validation through in vitro and in vivo studies.