Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to pose a serious global health threat. In this study, we employed an immunoinformatics approach to design a multi-epitope vaccine targeting the four structural proteins of SARS-CoV-2 (spike, membrane, envelope, and nucleocapsid). Epitope-rich fragments containing overlapping MHC class I, MHC class II, and B-cell epitopes were identified and assembled into different vaccine constructs. Molecular docking confirmed strong binding affinities of these fragments to common HLA alleles, and molecular dynamics simulations validated the stability of the selected construct. To enhance immunogenicity, human β-defensin 2 (hBD-2) and hBD-3 adjuvants were incorporated, and the construct was codon-optimized for expression in E. coli K-12. Among the four candidates, Construct 2 demonstrated superior structural stability and favorable interactions with toll-like receptors 3 and 4 (TLR3, TLR4) in molecular dynamics (MD). In silico immune simulations also predicted robust activation of B and T lymphocytes, cytokine release, and memory cell formation, indicating the potential of the construct to elicit broad and long-lasting antiviral immunity. This study establishes an effective immunoinformatics framework for rational multi-epitope vaccine design and identifies Construct 2 as a promising next-generation candidate against SARS-CoV-2. The findings highlight the potential of computational approaches to accelerate precise and targeted vaccine development pending experimental validation.
Amirabadi et al. (Thu,) studied this question.