Designing a multi-epitope vaccine against SARS-CoV-2: an immunoinformatics approach

Ongoing COVID-19 outbreak has raised a drastic challenge to global public health security. Most of the patients with COVID-19 suffer from mild flu-like illnesses such as cold and fever; however, few percentages of the patients progress from severe illness to death, mostly in an immunocompromised individual. The causative agent of COVID-19 is an RNA virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite these debilitating conditions, no medication to stop the disease progression or vaccination is available till now. Therefore, we aimed to formulate a multi-epitope vaccine against SARS-CoV-2 by utilizing an immunoinformatics approach. For this purpose, we used the SARS-CoV-2 spike glycoprotein to determine the immunodominant T- and B-cell epitopes. After rigorous assessment, we designed a vaccine construct using four potential epitopes from each of the three epitope classes such as cytotoxic T-lymphocytes, helper T-lymphocyte, and linear B-lymphocyte epitopes. The designed vaccine was antigenic, immunogenic, and non-allergenic with suitable physicochemical properties and has higher solubility. More importantly, the predicted vaccine structure was similar to the native protein. Further investigations indicated a strong and stable binding interaction between the vaccine and the toll-like receptor (TLR4). Strong binding stability and structural compactness were also evident in molecular dynamics simulation. Furthermore, the computer-generated immune simulation showed that the vaccine could trigger real-life-like immune responses upon administration into humans. Finally, codon optimization based onEscherichia coliK12 resulted in optimal GC content and higher CAI value followed by incorporating it into the cloning vector pET28+(a). Overall, these results suggest that the designed peptide vaccine can serve as an excellent prophylactic candidate against SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Automated summary

The ongoing COVID-19 outbreak poses a significant challenge to global public health security. In this study, a multi-epitope vaccine against SARS-CoV-2 was designed using an immunoinformatics approach. The vaccine showed antigenicity, immunogenicity, and non-allergenicity, with suitable physicochemical properties. Molecular dynamics simulation and immune simulation demonstrated the effectiveness of the vaccine, and codon optimization was performed. This designed peptide vaccine has the potential to be an excellent prophylactic candidate against SARS-CoV-2.