Abstract Background The lack of effective treatment and a protective vaccine against the highly infectious SARS-CoV-2 has aggravated the already catastrophic global health issue. Here, in an attempt to design an efficient vaccine, a vigorous immunoinformatics approach was followed to predict the most suitable viral proteins epitopes for building that vaccine. Methods The amino acid sequences of four structural proteins (S, M, N, E) along with one potentially antigenic accessory protein (ORF1a) of SARS-CoV-2 were inspected for the most appropriate epitopes to be used for building the vaccine construct. Several immunoinformatics tools were used to assess the antigenicity, immunogenicity, allergenicity, toxigenicity, interferon-gamma inducing capacity, and the physicochemical properties of the product. Results The final candidate vaccine construct consisted of 468 amino acids, encompassing 30 epitopes. All the vaccine properties and its ability to trigger the humoral and cell-mediated immune response were validated computationally. Molecular modeling, docking to TLR3, simulation, and molecular dynamics were also carried out. Finally, a molecular clone using pET28: :mAID expression plasmid vector was prepared. Conclusion The overall results of the study suggest that the final multi-epitope chimeric construct is a potential candidate for an efficient protective vaccine against SARS-CoV-2.