Multi-stage structure-based virtual screening approach towards identification of potential SARS-CoV-2 NSP13 helicase inhibitors 

Abstract

On account of its crucial role in the virus life cycle, SARS-COV-2 NSP13 helicase enzyme was exploited as a promising target to identify a novel potential inhibitor using multi-stage structure-based drug discovery approaches. Firstly, a 3D pharmacophore was generated based on the collected data from a protein-ligand interaction fingerprint (PLIF) study using key interactions between co-crystallised fragments and the NSP13 helicase active site. The ZINC database was screened through the generated 3D-pharmacophore retrieving 13 potential hits. All the retrieved hits exceeded the benchmark score of the co-crystallised fragments at the molecular docking step and the best five-hit compounds were selected for further analysis. Finally, a combination between molecular dynamics simulations and MM-PBSA based binding free energy calculations was conducted on the best hit (compound FWM-1) bound to NSP13 helicase enzyme, which identified FWM-1 as a potential potent NSP13 helicase inhibitor with binding free energy equals −328.6 ± 9.2 kcal/mol.

Graphical Abstract

Keywords:

• SARS CoV-2 NSP13 helicase
• protein-ligand interaction fingerprint
• structure-based pharmacophore
• docking
• molecular dynamics simulations

Author contributions

All the authors contributed equally to this work.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

The present work was financially supported from the Researchers Supporting Project number (RSP-2021/103), King Saud University, Riyadh, Saudi Arabia.