Computational identification and design of multi-peptide vaccine candidates, particularly targeting viral proteins, has gained momentum in the recent past. Using bioinformatics and immunoinformatics tools, the work identifies B-cell and T-cell epitopes—peptide sequences capable of triggering immune responses—that are preferably conserved across multiple virus genotypes. This approach aims to develop broad-spectrum vaccines effective against diverse viral strains. Epitope prediction algorithms analyze viral protein sequences to pinpoint regions with high antigenic potential. The binding affinity between predicted peptides and major histocompatibility complex (MHC) molecules is further evaluated using molecular docking and dynamics simulations, helping to select candidates with optimal immune recognition. This computational workflow streamlines vaccine design by prioritizing multi-epitope constructs, enhancing immune response breadth and durability.

Integral to this process is the protein structural and functional analysis, allowing researchers to visualize epitope locations, assess structural stability, and understand the spatial arrangement of amino acids critical for protein function. This insight guides the refinement of vaccine candidates by ensuring that selected peptides are accessible and structurally viable for immune targeting.