Integrated study of Quercetin as a potent SARS-CoV-2 RdRp inhibitor: Binding interactions, MD simulations, and In vitro assays
Ahmed M Metwaly, Esmail M El-Fakharany, Aisha A Alsfouk, Ibrahim M Ibrahim, Eslam B Elkaeed, Ibrahim. H Eissa
PLOS ONE, doi:10.1371/journal.pone.0312866
To find an effective inhibitor for SARS-CoV-2, Quercetin's chemical structure was compared to nine ligands associated with nine key SARS-CoV-2 proteins. It was found that Quercetin closely resembles Remdesivir, the co-crystallized ligand of RNA-dependent RNA polymerase (RdRp). This similarity was confirmed through flexible alignment experiments and molecular docking studies, which showed that both Quercetin and Remdesivir bind similarly to the active site of RdRp. Molecular dynamics (MD) simulations over a 200 ns trajectory, analyzing various factors like RMSD, RG, RMSF, SASA, and hydrogen bonding were conducted. These simulations gave detailed insights into the binding interactions of Quercetin with RdRp compared to Remdesivir. Further analyses, including MM-GBSA, Protein-Ligand Interaction Fingerprints (ProLIF) and Profile PLIP studies, confirmed the stability of Quercetin's binding. Principal component analysis of trajectories (PCAT) provided insights into the coordinated movements within the systems studied. In vitro assays showed that Quercetin is highly effective in inhibiting RdRp, with an IC 50 of 122.1 ±5.46 nM, which is better than Remdesivir's IC 50 of 21.62 ±2.81 μM. Moreover, Quercetin showed greater efficacy against SARS-CoV-2 In vitro, with an IC 50 of 1.149 μg/ml compared to Remdesivir's 9.54 μg/ml. The selectivity index (SI) values highlighted Quercetin's safety margin (SI: 791) over Remdesivir (SI: 6). In conclusion, our comprehensive study suggests that Quercetin is a promising candidate for further research as an inhibitor of SARS-CoV-2 RdRp, providing valuable insights for developing an effective anti-COVID-19 treatment.
Supporting information S1 File. The detailed methodology for the molecular similarity, the molecular docking, the MD simulations, the ProLIF, the PLIP, the MM-GBSA, the PCAT, and the In vitro studies. (PDF)
Author Contributions Conceptualization: Ahmed M. Metwaly
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