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Immunoinformatics mapping of potential epitopes in SARS-CoV-2 structural proteins

ABSTRACT: 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.

SUBMITTER: Devi Y

PROVIDER: S-EPMC8592446 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe pandemic situation of SARS-CoV-2 infection has sparked global concern due to the disease COVID-19 caused by it. Since the first cluster of confirmed cases in China in December 2019, the infection has been reported across the continents and inflicted upon a substantial number of populations.MethodThis study is focused on immunoinformatics analyses of the SARS-CoV-2 spike glycoprotein (S protein) which is key for the viral attachment to human host cells. Computational analyses were carried out for the prediction of B-cell and T-cell (MHC class I and II) epitopes of S protein and the analyses were extended further for the prediction of their immunogenic properties. The interaction and binding affinity of T-cell epitopes with HLA-B7 were also investigated by molecular docking.ResultThree distinct epitopes for vaccine design were predicted from the sequence of S protein. The potential B-cell epitope was KNHTSPDVDLG possessing the highest antigenicity score of 1.4039 among other B-cell epitopes. T-cell epitope for human MHC class I was VVVLSFELL with an antigenicity score of 1.0909 and binding ability to 29 MHC-I alleles. The predicted T-cell epitope for human MHC class II molecule was VVIGIVNNT with a corresponding 1.3063 antigenicity score, less digesting enzymes, and 7 MHC-II alleles binding ability. All these three peptides were predicted to be highly antigenic, non-allergenic, and non-toxic. Analyses of the physiochemical properties of these predicted epitopes indicate their stable nature for plausible vaccine design. Furthermore, molecular docking investigation between the MHC class-I epitopes and human HLA-B7 reflects the stable interaction with high affinity among them.ConclusionThe present study posits three potential epitopes of S protein of SARS-CoV-2 predicted by immunoinformatic methods based on their immunogenic properties and interactions with the host counterpart that can facilitate the development of vaccine against SARS-CoV-2. This study can act as the springboard for the future development of the COVID-19 vaccine.

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Immunoinformatics mapping of potential epitopes in SARS-CoV-2 structural proteins

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