"In Silico Strategies and Comparative Genomics in Arboviruses: A Comprehensive Review of Therapeutic and Vaccine Target Discovery"

Arboviruses, including Dengue (DENV), Chikungunya (CHIKV), and Zika (ZIKV), are a concern as significant global health crises due to their rapid spread, complex vector-host interactions, and lack of targeted therapeutics or licensed vaccines. This RNA virus is spread by Aedes mosquitoes and shows high genetic variability with a range of clinical complications. Conventional laboratory approaches for drug and vaccine discovery are time-consuming and very expensive, thus leading to a move towards computational (in silico) strategies. This review explains the genomic architecture and biological insights of DENV, CHIKV, and ZIKV which highlighting their evolutionary relationships, transmission dynamics, and clinical relevance. We discuss the power of comparative genomics in identifying conserved, essential, and non-host homologous genes that serve as potential therapeutic and vaccine targets. A systematic in silico pipeline—encompassing genome annotation, essential gene identification, host non-homology analysis, subcellular localization prediction, druggability and immunogenicity assessment, epitope modeling, and network analysis—is presented. To identify promising candidates for downstream validation and clinical development, we can use integrated computational methods. Our review emphasizes the need for an integrated, comparative genomic approach to overcome the challenges posed by viral diversity and co-circulation, ultimately guiding effective therapeutic and vaccine design against these high-burden arboviral diseases. Keywords: Arbovirus; Dengue (DENV); Chikungunya (CHIKV); Zika (ZIKV); In Silico Analysis, Vaccine Target; Epitope Prediction, Immunoinformatics.