Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins

ABSTRACT:

The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies in silico. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body.

Communicated by Ramaswamy H. Sarma

Keywords:

• Multi epitope
• chimeric
• molecular docking
• molecular dynamics simulation
• immune simulation

Acknowledgement

The authors of this article extend their gratitude to Krupanidhi College of Physiotherapy for its constant support and assistance, which helped the authors in the successful completion of this research work.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.