All approved coronavirus disease 2019 (COVID-19) vaccines in current use are safe, effective, and reduce the risk of severe illness. Although data on the immunological presentation of patients with COVID-19 is limited, increasing experimental evidence supports the significant contribution of B and T cells towards the resolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Despite the availability of several COVID-19 vaccines with high efficacy, more effective vaccines are still needed to protect against the new variants of SARS-CoV-2. Employing a comprehensive immunoinformatic prediction algorithm and leveraging the genetic closeness with SARS-CoV, we have predicted potential immune epitopes in the structural proteins of SARS-CoV-2. The S and N proteins of SARS-CoV-2 and SARS-CoVs are main targets of antibody detection and have motivated us to design four multi-epitope vaccines which were based on our predicted B- and T-cell epitopes of SARS-CoV-2 structural proteins. The cardinal epitopes selected for the vaccine constructs are predicted to possess antigenic, non-allergenic, and cytokine-inducing properties. Additionally, some of the predicted epitopes have been experimentally validated in published papers. Furthermore, we used the C-ImmSim server to predict effective immune responses induced by the epitope-based vaccines. Taken together, the immune epitopes predicted in this study provide a platform for future experimental validations which may facilitate the development of effective vaccine candidates and epitope-based serological diagnostic assays.

Researchers around the world are developing more than 145 vaccines (DNA/mRNA/whole-virus/viral-vector/protein-based/repurposed vaccine) against the SARS-CoV-2 and 21 vaccines are in human trials. However, a limited information is available about which SARS-CoV-2 proteins are recognized by human B- and T-cell immune responses. Using a comprehensive computational prediction algorithm and stringent selection criteria, we have predicted and identified potent B- and T-cell epitopes in the structural proteins of SARS-CoV and SARS-CoV-2. The amino acid residues spanning the predicted linear B-cell epitope in the RBD of S protein (370-NSASFSTFKCYGVSPTKLNDLCFTNV-395) have recently been identified for interaction with the CR3022, a previously described neutralizing antibody known to neutralize SARS-CoV-2 through binding to the RBD of the S protein. Intriguingly, most of the amino acid residues spanning the predicted B-cell epitope (aa 331-NITNLCPFGEVFNATRFASVYAWNRK-356, 403-RGDEVRQIAPGQTGKIADYNYKLPD-427 and aa 437- NSNNLDSKVGGNYNYLYRLFRKSNL-461) of the S protein have been experimentally verified to interact with the cross-neutralizing mAbs (S309 and CB6) in an ACE2 receptor-S protein interaction independent-manner. In addition, we found that computationally predicted epitope of S protein (370-395) is likely to function as both linear B-cell and MHC class II epitope. Similarly, 403-27 and 437-461 peptides of S protein were predicted as linear B cell and MHC class I epitope while, 177-196 and 1253-1273 peptides of S protein were predicted as linear and conformational B cell epitope. We found MHC class I epitope 316-GMSRIGMEV-324 predicted as high affinity epitope (HLA-A*02:03, HLA-A*02:01, HLA-A*02:06) common to N protein of both SARS-CoV-2 and SARS-CoV (N317-325) was previously shown to induce interferon-gamma (IFN-γ) in PBMCs of SARS-recovered patients. Interestingly, two MHC class I epitopes, 1041-GVVFLHVTY-1049 (HLA-A*11:01, HLA-A*68:01, HLA-A*03:01) and 1202-FIAGLIAIV-1210 (HLA-A*02:06, HLA-A*68:02) derived from SARS-CoV S protein with epitope conservancy between 85 to 100% with S protein of SARS-CoV-2 was experimentally verified using PBMCs derived from SARS-CoV patients. We observed that HLA-A*02:01, HLA-A*02:03, HLA-A*02:06, HLA-A*11:01, HLA-A*30:01, HLA-A*68:01, HLA-A*68:02, HLA-B*15:01 and HLA-B*35:01 have been predicted to bind to the maximum number of MHC class I epitope (based on the criterion of allele predicted to bind more than 30 epitopes) of S protein of SARS-CoV-2. Similarly, we observed that HLA-A*02:06, HLA-A*30:01, HLA-A*30:02, HLA-A*31:01, HLA-A*32:01, HLA-A*68:01, HLA-A*68:02, HLA-B*15:01 and HLA-B*35:01 are predicted to bind to the maximum number of MHC class I epitope of N protein of SARS-CoV-2. We found that HLA-DRB1*04:01, HLA-DRB1*04:05, HLA-DRB1*13:02, HLA-DRB1*15:01, HLA-DRB3*01:01, HLA-DRB3*02:02, HLA-DRB4*01:01, HLA-DRB5*01:01, HLA-DQA1*04:01, DQB1*04:02, HLA-DPA1*02:01, DPB1*01:01, HLA-DPA1*01:03, DPB1*02:01, HLA-DPA1*01:03, DPB1*04:01, HLA-DPA1*03:01, DPB1*04:02, HLA-DPA1*02:01, DPB1*05:01, HLA-DPA1*02:01, and DPB1*14:01 are predicted to bind to the maximum number of MHC class II epitope of S protein of SARS-CoV-2. Alleles such as HLA-DRB1*04:01, HLA-DRB1*07:01, HLA-DRB1*08:02, HLA-DRB1*09:01, HLA-DRB1*11:01, HLA-DRB1*13:02, HLA-DRB3*02:02, HLA-DRB5*01:01, HLA-DQA1*01:02, DQB1*06:02, DPB1*05:01 and HLA-DPA1*02:01 are found to interact with the maximum number of MHC class II epitope of N protein of SARS-CoV-2. Using the IEDB tool we found the occurrence of HLA alleles with population coverage of around 99% throughout the world. The findings of computational predictions of mega-pool of B- and T-cell epitopes identified in the four main structural proteins of SARS-CoV-2 provides a platform for future experimental validations and the results of present works support the use of RBD or the full-length S and N proteins in an effort towards designing of recombinant protein-based vaccine and a serological diagnostic assay for SARS-CoV-2.