In silico identification and validation of immunogenic epitopes for mRNA vaccine development against babanki virus using bioinformatics approach

Abstract

The Babanki virus, classified within the Alphavirus genus of the family Togaviridae , poses notable health challenges due to its association with febrile illnesses and possible arthritic symptoms. In this investigation, a comprehensive immunoinformatics and bioinformatics framework was applied to develop mRNA vaccine candidates targeting this virus. The Babanki protein sequences sourced from the NCBI repository were screened for antigenicity, allergenic risk, and toxicity to identify suitable vaccine components. Two separate mRNA constructs were then designed, each integrating predicted epitopes for B-cells, cytotoxic T lymphocytes (CTLs), and helper T lymphocytes (HTLs), alongside elements enhancing co-translational efficiency to boost immune activation. Both vaccine candidates demonstrated antigenicity above the required threshold and were predicted to be safe, with no allergenic or toxic properties. Physicochemical evaluations confirmed their favorable stability and solubility characteristics. Furthermore, molecular docking analyses revealed strong interactions with the immune receptors TLR3 and TLR7. Immune response simulations supported the constructs’ capacity to induce durable and potent immunogenicity. The results of this study indicate that the designed mRNA vaccines are promising candidates against Babanki virus; however, further in vitro and in vivo screening is required to validate the efficacy of the vaccine constructs.