Venetoclax: a promising repurposed drug against SARS-CoV-2 main protease

Abstract

Global health care emergency caused by a new coronavirus (severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2) demands urgent need to repurpose the approved pharmaceutical drugs. Main protease, M^pro of SARS-CoV-2 draws significant attention as a drug target. Herein, we have screened FDA approved organosulfur drugs (till 2016) and our laboratory synthesized organosulfur and organoselenium compounds (L1-L306) against M^pro-apo using docking followed by classical MD simulations. Additionally, a series of compounds (L307-L364) were chosen from previous experimental studies, which were reported to exhibit inhibitory potentials towards M^pro. We found several organosulfur drugs, particularly Venetoclax (FDA approved organosulfur drug for Leukemia) to be a high-affinity binders to the M^pro of SARS-CoV-2. The results reveal that organosulfur compounds including Venetoclax preferentially bind (non-covalently) to the non-catalytic pocket of the protein located in the dimer interface. We found that the ligand binding is primarily favoured by ligand-protein van der Waals interaction and penalized by desolvation effect. Interestingly, Venetoclax binding alters the local flexibility of M^pro and exerts pronounced effect in the C-terminal as well as two loop regions (Loop-A and Loop-B) that play important roles in catalysis. These findings highlighted the importance of drug repurposing and explored the non-catalytic pockets of M^pro in combating COVID-19 infection in addition to the importance of catalytic binding pocket of the protein.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2 main protease
• docking and molecular dynamics simulation
• organosulfur drugs
• organochalcogen compounds
• Venetoclax

Acknowledgements

SG and DB thank IIT Guwahati for their fellowships. PARAM-ISHAN, Bimolecular Simulation Lab (BSL) of Department of Biosciences and Bioengineering and BIF facility (Supported by DBT, Project Code: BT/BI/12/064/2012 (NER-BIF) of IIT Guwahati is gratefully acknowledged for providing the computing facility. PS acknowledges SERB, Govt. of India (YSS/2015/000024) for funding. KPB acknowledges DST, India for INSPIRE Faculty Award (IFA12-CH-68).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by DST, New Delhi, India;SERB, India.