Designing next-generation mRNA vaccines against nipah virus using predictive immunoinformatics frameworks

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s The Nipah virus (NiV) is a zoonotic pathogen designated as a priority disease by the World Health Organization. Currently, there are no approved vaccines specifically available for NiV infection in either humans or animals. In this study, we employed immunoinformatics approaches to design an mRNA vaccine candidate targeting five proteins from the Nipah virus. Viral protein sequences were retrieved and analyzed, and antigenic sequences were selected for further evaluation. The vaccine construct was developed using linear B-cell epitopes, cytotoxic T lymphocyte (CTL) epitopes, and helper T lymphocyte (HTL) epitopes capable of inducing interleukin-4 (IL-4), interleukin-10 (IL-10), and interferon-gamma (IFN-γ) responses, as predicted using various bioinformatics tools. The final construct comprised fifteen epitopes, an adjuvant, an MHC class I-targeting domain (MITD), a Kozak sequence, 5′ and 3′ untranslated regions (UTRs), and a 5′ cap, all linked using appropriate peptide linkers. The vaccine was predicted to be antigenic, non-toxic, and non-allergenic, with favorable physicochemical properties, including a molecular weight of 129.23 kDa, an aliphatic index of 74.42, a GRAVY score of −0.483, and an isoelectric point (pI) of 8.61. Molecular docking simulations demonstrated strong binding affinities with Toll-like receptors 3 and 4 (TLR3 and TLR4). These findings suggest that the designed vaccine construct has the potential to elicit a protective immune response against the Nipah virus. However, further experimental validation is required to assess its efficacy and safety.

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