Skip to content
Open access

H5N1 influenza multi-epitope vaccine design through immunoinformatics approaches

Aug 2026 · Frontiers in Applied Mathematics and Statistics · 0 citations · 60 references

Abstract

The H5N1 avian influenza virus poses a significant threat to both animal and human health, with a high potential for triggering a global pandemic. This study outlines a step-by-step immunoinformatics-driven approach to design a multi-epitope vaccine against H5N1. Potential vaccine candidates were identified by analyzing the sequences of conserved H5N1 proteins, including Hemagglutinin, Neuraminidase, and Matrix protein 1 and 2. B-cell epitopes and T-cell peptides were predicted and then screened for toxicity and allergenicity. The final vaccine construct has been verified for structural stability and computer simulation has been used to evaluate its theoretical potential for eliciting a long-lasting immune response. This In silico approach leverages a suite of computational tools to accelerate vaccine design by prioritizing promising candidates for experimental validation.

Read PDF

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.