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
【저자키워드】 docking, molecular dynamics simulations, SARS CoV-2 NSP13 helicase, protein-ligand interaction fingerprint, structure-based pharmacophore, 【초록키워드】 Drug discovery, molecular docking, binding free energy, ZINC database, Molecular dynamics simulation, Helicase, inhibitor, Combination, Interaction, Analysis, Virus life cycle, approaches, enzyme, Compound, collected data, protein-ligand interaction, selected, identify, conducted, screened, exceeded, retrieved, 【제목키워드】 Virtual screening, Helicase, inhibitor, approach, SARS-CoV-2 nsp13,