Computational Modelling of Hemagglutinin Protein Mutational Landscapes: A Network Theory Approach to Influenza Vaccine Target Selection
DOI:
https://doi.org/10.70411/MJHAS.3.1.2026281Keywords:
Influenza, Hemagglutinin (HA), Network Theory, Mutational Landscape, Vaccine DesignAbstract
Influenza vaccine design remains challenging because rapid mutations in the hemagglutinin (HA) protein can reduce vaccine effectiveness.
Findings suggest that residues with high centrality, particularly those near the receptor-binding and fusion regions, are essential for maintaining HA functionality and structural stability, even as mutations occur. Tests against the evolution of historical strains and neutralization assays confirmed that these sites have lower mutation tolerance and preserved antigenicity.
Our network-based method acts as a strong and adaptable tool to design appropriate antigens, not only for the flu, but also for other rapid viral pathogens. It is regrettable that the current vaccine strategies often find it difficult to keep up with quick growth trunks. In this paper, we present an advanced computational framework that merges structural bioinformatics, sequence analysis, and network theory to chart the mutational landscape of HA and identify potential vaccine targets that could endure these shifts.
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