Identification of structural scaffold from interbioscreen (IBS) database to inhibit 3CLpro, PLpro, and RdRp of SARS-CoV-2 using molecular docking and dynamic simulation studies

Abstract

A novel coronavirus SARS-CoV-2 has caused a worldwide pandemic and remained a severe threat to the entire human population. Researchers worldwide are struggling to find an effective drug treatment to combat this deadly disease. Many FDA-approved drugs from varying inhibitory classes and plant-derived compounds are screened to combat this virus. Still, due to the lack of structural information and several mutations of this virus, initial drug discovery efforts have limited success. A high-resolution crystal structure of important proteins like the main protease (3CLpro) that are required for SARS-CoV-2 viral replication and polymerase (RdRp) and papain-like protease (PLpro) as a vital target in other coronaviruses still presents important targets for the drug discovery. With this knowledge, scaffold library of Interbioscreen (IBS) database was explored through molecular docking, MD simulation and postdynamic binding free energy studies. The 3D docking structures and simulation data for the IBS compounds was studied and articulated. The compounds were further evaluated for ADMET studies using QikProp and SwissADME tools. The results revealed that the natural compounds STOCK2N-00385, STOCK2N-00244, and STOCK2N-00331 interacted strongly with 3CLpro, PLpro, and RdRp, respectively, and ADMET data was also observed in the range of limits for almost all the compounds with few exceptions. Thus, it suggests that these compounds may be potential inhibitors of selected target proteins, or their structural scaffolds can be further optimized to obtain effective drug candidates for SARS-CoV-2. The findings of in-silico data need to be supported by in-vivo studies which could shed light on understanding the exact mode of inhibitory action.

Communicated by Ramaswamy H. Sarma

Keywords:

• Docking
• dynamics
• ADMET
• SARS-CoV-2

Acknowledgements

VRP, AMD, RP, DKL, VGU, SDF, PC and SCK thanks Dr. S. J. Surana, Principal, R.C.P.I.P.E.R, Shirpur for providing research facilities. NDA thank the management of Nagar Yuwak Shikshan Sanstha, Nagpur for the kind support. SKS thank Principal, PJLCP, Nagpur and CHM and UYN thank Principal, MCOPS, Manipal for their encouragement.

Author contribution

Saurabh C. Khadse: Conceptualization, Methodology, Investigation and Interpretation, Writing-original draft, Writing-review and editing. Nikhil D. Amnerkar: Methodology, Editing-original draft, Writing-review and editing, Validation. Vikas R. Patil: Docking studies, Data collection and analysis. Ashish M. Dhote: Methodology, Docking studies, Data collection and analysis. Rina Patil: Docking studies, Data collection and analysis. Deepak K. Lokwani: Methodology, Docking. Vinod G. Ugale: Visualization, Validation, Resources. Nitin B. Charbe: Visualization, Validation, Resources. Sandip Firke: Docking Interpretation. Prashant Chaudhari: Validation, Resources. Sapan Shah, Chetan Mehta and Usha Nayak: MD Simulation studies, Data collection.

Disclosure statement

The author declares that there is no competing interest in this work.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.