Construction of Multi-Epitopes Vaccine Candidate against SARS-CoV-2 D614G Variant

Abstract

COVID-19 caused by the SARS-CoV-2 virus has become a real threat due to the emergence of new variants which are more deadly with higher infectivity. Vaccine constructs that target specific SARS-CoV-2 variants are needed for stemming COVID-19 fatality. The spike (S) glycoprotein is the major antigenic component that triggers the host immune response. Reverse vaccinology strategy was applied to the S protein of COVID-19 variant D614G to identify highly ranked antigenic proteins. In this study, a multi-epitope synthetic gene was designed using computational strategies for the COVID-19 D614G variant. The SARS-CoV-2 D614G variant protein sequence was retrieved from the NCBI database. The prediction of linear B-cell epitopes was carried out using Artificial Neural Network (ANN)-based ABCpred and BepiPred 2.0 software. The top 15 highly antigenic epitopes sequences were then selected. Propred 1 and Propred servers were used to identify major histocompatibility complex (MHC) class I and class II binding epitopes within pre-determined B-cell epitopes to predict T-cell epitopes. The top 5 MHC class I and class II were selected. Further in-silico testing for its solubility, allergenicity, antigenicity, and other physiochemical properties was analyzed using Bpred. The constructed gene was subjected to assembly PCR and the gene product was confirmed by Sanger sequencing. The findings from this study suggested that a highly antigenic specific region of the SARS-CoV-2 D614G variant can be predicted in-silico and amplified using the assembly PCR method. The designed synthetic gene was shown to elicit specific humoral and cell-mediated immune responses towards the SARS-CoV-2 variants.