Finding potent inhibitors against SARS-CoV-2 main protease through virtual screening, ADMET, and molecular dynamics simulation studies

Abstract

Currently, no antiviral drug or vaccine is available to treat COVID-19 caused by SARS-CoV-2. This underscores an urgent need for developing a drug against SARS-CoV-2. The main protease (3CL^pro) of SARS-CoV-2 is considered an essential protein for maintaining the viral life cycle and, therefore, a potential target for drug development. In a recent study, 1000 potential ligands were identified for 3CL^pro by screening 1.3 billion compounds from the ZINC15 library. In the current study, we have further screened these 1000 compounds using structure-based virtual screening utilizing the Schrödinger suite and identified nine compounds having a docking score of ∼ −11.0 kcal/mol or less. The top 5 hits display good pharmacological profiles revealing better absorption, proper permeability across the membrane, uniform distribution, and non-toxic. The molecular docking study is further complemented by molecular dynamics simulations of the top 5 docked complexes. The binding free energy analyses via the molecular mechanics generalized Born surface area (MM/GBSA) scheme reveals that ZINC000452260308 is the most potent (ΔG_bind = −14.31 kcal/mol) inhibitor. The intermolecular van der Waals interactions mainly drive the 3CL^pro-ligand association. This new compound may have great potential as a lead molecule to develop a new antiviral drug to fight against COVID-19.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2 3CLpro
• virtual screening
• ADMET
• molecular dynamics
• MM/GBSA

Disclosure statement

The authors declare no potential conflict of interest.

Ethics statement

There is no human or animal experiment in this study.

Data availability statement

The data that support the findings of this study are available from the corresponding author (PK) upon reasonable request.

Additional information

Funding

This work was partially supported by the Department of Biotechnology, Govt. of India (grant number BT/RLF/Re-entry/40/2014), and Department of Science and Technology (DST), Govt. of India (grant number ECR/2017/000010). RJ thanks the Indian Institute of Technology Indore for financial assistance.