Design and bioinformatic characterization of multi-epitope candidate vaccine derived from structural protein of SARS-CoV-2 Alpha, Delta, and Omicron variants

This present study was conducted to design a multi-epitope vaccine candidate that integrates conserved B-cell and T-cell epitopes derived from structural proteins across major variants, using advanced immunoinformatic tools. In silico analyses assessed antigenicity, toxicity, allergenicity, solubility, and physicochemical parameters, followed by modeling, refinement, and validation using various bioinformatics tools. Molecular docking and immune simulation confirmed stable interactions with immune receptors and strong immune responses, while codon optimization ensured efficient expression in Escherichia coli, highlighting the vaccine's potential as a safe and broadly protective immunogen. This study reports a computationally designed multi-epitope vaccine targeting conserved CTL, HTL, and LBL epitopes from SARS-CoV-2 structural proteins to confer broad variant coverage. The vaccine construct demonstrated favorable antigenicity, safety, structural stability, and strong binding to immune receptors (TLR-2, MHC-I, MHC-II), indicating its potential to activate both innate and adaptive immunity. Immune simulations showed robust humoral and cellular responses, especially Th1 polarization and long-term memory formation, supporting the vaccine's promise for further experimental development. In order to create a multi-epitope vaccine candidate for SARS-CoV-2 that would trigger both innate and adaptive immune responses across several viral types, this study used computational techniques to incorporate conserved epitopes from the Spike, Membrane, and Nucleocapsid proteins.