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

• Main Authors: Mahmoud A. El Hassab (Author), Wagdy M. Eldehna (Author), Sara T. Al-Rashood (Author), Amal Alharbi (Author), Razan O. Eskandrani (Author), Hamad M. Alkahtani (Author), Eslam B. Elkaeed (Author), Sahar M. Abou-Seri (Author)
• Format: Book
• Published: Taylor & Francis Group, 2022-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1475-6366; 1475-6374; 10.1080/14756366.2021.2022659
• Keywords: sars cov-2 nsp13 helicase; protein-ligand interaction fingerprint; structure-based pharmacophore; docking; molecular dynamics simulations; Therapeutics. Pharmacology; RM1-950
• Source: Journal of Enzyme Inhibition and Medicinal Chemistry, Vol 37, Iss 1, Pp 563-572 (2022)

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.