Bioinformatics-guided vaccine targeting the hemagglutinin protein of avian influenza virus.

Avian influenza viruses (AIV) represent a major zoonotic threat to global public health and agriculture due to their high mutation rates, antigenic drift, and potential for interspecies transmission. This study addresses the urgent need for innovative, broad-spectrum vaccines that can overcome the limitations of traditional approaches, such as slow production and strain-specific protection, by designing and evaluating a novel multi-epitope protein-based vaccine targeting conserved regions of the AIV hemagglutinin (HA) protein through advanced immunoinformatics tools. Using an in silico approach, conserved 4 MHC-I, 9 MHC-II, and 5 B-cell epitopes were identified, screened for antigenicity, non-toxicity, and non-allergenicity, and integrated into a rationally designed vaccine construct optimized with a tPA signal peptide, the RpfE adjuvant, and immunostimulatory elements. The AIV vaccine construct exhibited favorable physicochemical properties, including a molecular weight of 64.8 kDa, a basic pI, antigenicity (0.5871), non-toxicity, non-allergenicity, and high solubility (0.747). The tertiary structure, predicted using RoseTTAFold, refined with GalaxyRefine, and then validated by a Ramachandran plot (97.4% residues in favored regions), demonstrated high stereochemical reliability. Linear and conformational B-cell epitopes were mapped, indicating strong antibody elicitation potential. Molecular docking, normal mode analysis, and molecular dynamics simulation confirmed a stable interaction with human TLR3, characterized by a favorable binding energy (ΔGbind = − 16.96 ± 4 kcal/mol) and stable complex dynamics. Immunogenicity simulations revealed elevated levels of IgG and IgM, accompanied by increased immune cell responses. The gene was cloned into the PET28a(+) vector, producing a 5.2 kb plasmid suitable for expression. In conclusion, this in silico-designed vaccine candidate demonstrates promising potential as a broad-spectrum immunogen against AIV, leveraging computational vaccinology to mitigate antigenic drift and zoonotic risks; future perspectives include experimental validation via in vitro and in vivo studies to confirm safety, immunogenicity, and efficacy, enabling rapid deployment against emerging influenza threats.