Potential protease inhibitors and their combinations to block SARS-CoV-2

Abstract

COVID-19, which has emerged recently as a pandemic viral infection caused by SARS-coronavirus 2 has spread rapidly around the world, creating a public health emergency. The current situation demands an effective therapeutic strategy to control the disease using drugs that are approved, or by inventing new ones. The present study examines the possible repurposing of existing anti-viral protease inhibitor drugs. For this, the structural features of the viral spike protein, the substrate for host cell protease and main protease of the available SARS CoV-2 isolates were established by comparing with related viruses for which antiviral drugs are effective. The results showed 97% sequence similarity among SARS and SARS-CoV-2 main protease and has same cleavage site positions and ACE2 receptor binding region as in the SARS–CoV spike protein. Though both are N-glycosylated, unlike SARS-CoV, human SARS-CoV-2 S-protein was O-glycosylated as well. Molecular docking studies were done to explore the role of FDA approved protease inhibitors to control SARS-CoV-2 replication. The results indicated that, Ritonavir has the highest potency to block SARS-CoV-2 main protease and human TMPRSS2, a host cell factor that aids viral infection. Other drugs such as Indinavir and Atazanavir also showed favourable binding with Cathepsin B/L that helped viral fusion with the host cell membrane. Further molecular dynamics simulation and MM-PBSA binding free energy calculations confirmed the stability of protein-drug complexes. These results suggest that protease inhibitors particularly Ritonavir, either alone or in combination with other drugs such as Atazanavir, have the potential to treat COVID 19.

Communicated by Ramaswamy H. Sarma

Keywords:

• COVID-19
• spike protein
• main protease
• TMPRSS2
• molecular docking

Acknowledgements

The authors acknowledge the AICADD and DBT-BIF support at the Department of Computational Biology and Bioinformatics, University of Kerala, India for providing the necessary facilities to carry out this study.

Disclosure statement

The authors declare no conflict of interest.

Author contributions

CSA and PRS conceived and designed the study. CSA and AK performed the experiments. CSA, ASN, AK, OVO and PRS analyzed the data. Manuscript written by CSA and PRS, edited by OVO and ASN. All authors read and approved the final manuscript.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This study was supported by the SIUCEB at the Department of Computational Biology and Bioinformatics, University of Kerala, India. P.R.S. was supported by ISCA, Kolkata by Asutosh Mookerjee Fellowship.