An Integrated Computational Approach to Predict and Characterize Emerging Mutations in the Japanese Encephalitis Virus Envelope Protein

Japanese encephalitis virus (JEV) causes significant encephalitis across the Asia-Pacific region. Current vaccines target historical genotype III strains, but emerging genotypes,potentially driven by vaccine-mediated selective pressure, threaten vaccine effectiveness through altered envelope protein sequences that may reduce antibody cross-neutralisation. This study employed integrated sequence and structural analyses to identify E protein mutations affecting neutralising antibody binding and protein stability. The study curated JEV polyprotein sequences from NCBI, performed multiple sequence alignment, and used Shannon entropy to pinpoint highly variable positions. Mutations occurring at [≥]1% frequency within high-entropy regions were selected for analysis. From 34 initially identified mutations, four candidates were prioritized based on structural stabilization potential. Mutations were evaluated through FoldX stability predictions, molecular docking with antibody 2H4 using HADDOCK3, and molecular dynamics simulations. Binding energies were calculated using MM-GBSA analysis. Results demonstrated that all mutant E-2H4 complexes remained stable during simulations, with root-mean-square deviation plateauing after equilibration and minimal localized changes in root-mean-square fluctuation. These findings suggest that EDIII substitutions represent important candidates for further investigation to understand genotype-specific variations and inform next-generation vaccine development strategies against emerging JEV strains.