Abstract
Background: The lack of effective treatment 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 thorough 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 (VaxiJen server), immunogenicity (IEDB immunogenicity tool), allergenicity (AlgPred), toxigenicity (ToxinPred server), interferongamma inducing capacity (IFNepitope server), and the physicochemical properties of the construct (ProtParam tool).
Results: The final candidate vaccine construct consisted of 468 amino acids, encompassing 29 epitopes. The CTL epitopes that passed the antigenicity, allergenicity, toxigenicity and immunogenicity assessment were four epitopes from S protein, one from M protein, two from N protein, 12 from the ORF1a polyprotein and none from E protein. While the HTL epitopes that passed the antigenicity, allergenicity, toxigenicity and INF-gamma were one from S protein, three from M protein, six from the ORF1a polyprotein and none from N and E proteins.
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.