Computational design and validation of a multi-epitope vaccine candidate against structural proteins of langya virus

The Langya virus (LayV), an emerging zoonotic henipavirus with pandemic potential and high fatality risks akin to Nipah and Hendra viruses. It underscores an urgent public health need for preventive solutions, given its lack of approved vaccines or therapies. Current RNA virus vaccine strategies, reliant on traditional live/inactivated approaches, face safety and scalability limitations, while multi-epitope designs for LayV’s structural proteins (N, P, M, F, G, and L) remain unexplored. This study aimed to computationally design a safe, specific, and scalable multi-epitope vaccine targeting LayV’s glycoproteins and fusion protein. We Used immunoinformatics tools (VaxiJen, NetCTL, IEDB) five antigenic proteins were prioritized, and 12 CTL, 7 HTL, and 4 B-cell epitopes were selected after screening. Three constructs (VCa, VCb, VCc) were engineered with adjuvants (L7/L12) and linkers (GPGPG/AAY), followed by a stability check using molecular docking and dynamics simulations (GROMACS). The constructs VCb emerged as the lead candidate, which was further suggested for experimental validation, exhibiting superior solubility (0.846), structural stability (instability index: 28.8), strong TLR4 binding (-336.5 kcal/mol), elevated β-strand content (20.8 %), and robust simulated immunity (IgG1: ∼24,000; IFN-γ: ∼5,000 ng/ml). Codon optimization (CAI >0.95, GC 52–55 %) confirmed the feasibility of an efficient E. coli expression system. This computational framework offers a quick and reliable approach for designing a LayV vaccine and highlights VCb as a promising multi-epitope vaccine candidate that deserves further experimental validation.