A multi-epitope vaccine design targeting emerging influenza A(H3N2) subclade K (J.2.4.1) variant

Résumé fourni par la source

Influenza A(H3N2) continues to pose a significant global public health challenge owing to its rapid antigenic evolution, particularly within the hemagglutinin (HA) glycoprotein, which frequently compromises vaccine effectiveness. The emergence of the H3N2 subclade K (J.2.4.1), characterized by multiple antigenically relevant mutations, necessitates the development of updated vaccine strategies capable of eliciting strain-specific immune responses. In this study, an immunoinformatics driven approach was employed to design a multi-epitope vaccine (MEV) targeting the HA protein of the J.2.4.1 variant. The HA sequence was modified to incorporate lineage-specific mutations, and cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B-cell epitopes were predicted using the machine learning-based NetMHCpan/NetMHCIIpan algorithms and the IEDB platform. High-confidence epitopes were selected based on antigenicity, non-allergenicity, non-toxicity, and immunogenic potential, and assembled using appropriate linkers with the 50S ribosomal protein L7/L12 as an adjuvant. The final MEV construct demonstrated favorable physicochemical characteristics, structural stability, and satisfactory model validation. Molecular docking and molecular dynamics simulations revealed stable interactions between the vaccine construct and TLR4, while immune simulation predicted effective humoral and cellular immune responses with the generation of immunological memory. Population coverage analysis further indicated broad global applicability of the selected T-cell epitopes. Together, these findings suggest that the incorporation of J.2.4.1 specific antigenic mutations into the MEV may enhance strain-specific immune recognition and provide a promising computational framework for the rapid development of next-generation influenza vaccines. Nevertheless, experimental validation is required to confirm the immunogenicity, safety, and protective efficacy of the proposed vaccine candidate.

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