Prediction of B-cell and T-cell epitopes in the spike glycoprotein of SARS-CoV-2 in Bangladesh: An in-silico approach

To combat highly infectious Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), scientists and researchers are toiling hard globally to develop effective drugs and vaccines. By exploring the structural proteins of SARS-CoV-2 can be a feasible way to find an effective vaccine. In this study by using in-silico tools, we recommended B-cell and T-cell epitopes of spike protein from a Bangladeshi isolate which can be considered for incorporation into a vaccine against the SARS-CoV-2. Homology modelling, energy minimization process, and finally Ramachandran model was used for the prediction of a more stable conformation of the spike protein. The most important peptides were screened through the VaxiJen server followed by the IEDB server and CTLPred Score predicted and analysed the desired epitopes. In the final analysis, the peptide EVRQIAPGQTGKIADY (starting from 91) showed the highest antigenicity score (1.3837) as a B-cell epitope although GSTPCNGVEGFNCYFP, starting at 161, showed highest score (0.91) in an initial analysis. On the contrary, as a T-cell epitope, 71 KLNDLCFTNV- 80 was found with the highest antigenicity score (2.6927) which was also found as an epitope in further analysis. A combination of B-cell and T-cell epitopes may evoke a humoral and cell-mediated immune response which will possibly lead to an effective vaccine. Further, the various computational analyses will provide valuable information that will pave the way for modelling a novel vaccine against SARS-CoV-2.