Immunoinformatics-guided design of a conserved multi-epitope vaccine candidate against pathogenic human coronaviruses

Despite the global decline in COVID-19 incidence, the continued emergence of immune-evasive SARS-CoV-2 variants underscores the urgent need for next-generation vaccines capable of providing broad protection. To characterise and design a broad-spectrum recombinant multiepitope vaccine candidate against pathogenic human coronaviruses using an immunoinformatics approach. Conserved antigenic regions within the spike (S), nucleocapsid (N) and membrane (M) proteins were identified from multiple SARS-CoV-2 variants through multiple sequence alignment. High-affinity T-cell and B-cell epitopes were screened and assembled into recombinant vaccine construct (RVC). The RVC was evaluated for antigenicity, allergenicity, toxicity and physicochemical properties, followed by tertiary structure prediction and validation. Molecular docking with Toll-like receptor 3 (TLR-3) and molecular dynamics (MD) simulations with MM-GBSA binding free energy calculations were performed, alongside in silico immune simulation. The RVC comprised four HLA class I-restricted epitopes, 27 HLA class II-restricted epitopes and five linear B-cell epitopes, with predicted global population coverage of 99.99%. The construct demonstrated high antigenicity, non-allergenicity and favourable physicochemical stability. Molecular docking showed stable interaction with TLR-3, supported by MD simulations and a favourable MM-GBSA binding free energy of - 5.19 kcal/mol. In silico immune simulation predicted robust humoral and cellular immune responses, including sustained memory cell populations following three-dose immunisation. These computational findings support the RVC as a promising broad-spectrum human coronavirus vaccine candidate. However, experimental validation, including immunogenicity, safety and protective efficacy studies in relevant in vitro and in vivo models, is warranted to substantiate its translational applicability.