Structure-based identification of potential SARS-CoV-2 main protease inhibitors

Abstract

To address coronavirus disease (COVID-19), currently, no effective drug or vaccine is available. In this regard, molecular modeling approaches are highly useful to discover potential inhibitors of the main protease (M^pro) enzyme of SARS-CoV-2. Since, the M^pro enzyme plays key roles in mediating viral replication and transcription; therefore, it is considered as an attractive drug target to control SARS-CoV-2 infection. By using structure-based drug design, pharmacophore modeling, and virtual high throughput drug screening combined with docking and all-atom molecular dynamics simulation approach, we have identified five potential inhibitors of SARS-CoV-2 M^pro. MD simulation studies revealed that compound 54035018 binds to the M^pro with high affinity (ΔG_bind −37.40 kcal/mol), and the complex is more stable in comparison with other protein-ligand complexes. We have identified promising leads to fight COVID-19 infection as these compounds fulfill all drug-likeness properties. However, experimental and clinical validations are required for COVID-19 therapy.

Communicated by Ramaswamy H. Sarma

Keywords:

• COVID19
• SARS-CoV-2
• Main protease inhibitor
• Pharmacophore modeling
• Molecular docking
• ADMET
• Molecular dynamics simulations

Acknowledgements

SK and ZF would like to acknowledge the CHPC server based in Cape Town, South Africa, and SK would also like to thank the University of the Witwatersrand URC postdoctoral fellowship for conducting this research. MFA and AH acknowledge the generous support from Research Supporting Project (No. RSP-2020-122) by King Saud University, Riyadh, Kingdom of Saudi Arabia.

Disclosure statement

The authors declare that they have no conflict of interest.

Additional information

Funding

This work is supported by the Council of Scientific and Industrial Research, India (Grant No. 27(0368)/20/EMRII).