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Background: The outbreak of the coronavirus (SARS-CoV-2) has drastically affected the human population and caused enormous economic deprivation. It belongs to the β-coronavirus family and causes various problems such as acute respiratory distress syndrome and has resulted in a global pandemic. Though various medications have been under trial for combating COVID-19, specific medicine for treating COVID-19 is unavailable. Thus, the current situation urgently requires effective treatment modalities. Nigella sativa, a natural herb with reported antiviral activity and various pharmacological properties, has been selected in the present study to identify a therapeutic possibility for treating COVID-19. Methods: The present work aimed to virtually screen the bioactive compounds of N. sativa based on the physicochemical properties and docking approach against two SARS-CoV-2 enzymes responsible for crucial functions: 3CLpro (Main protease) and NSP15 (Nonstructural protein 15 or exonuclease). However, simulation trajectory analyses for 100 ns were accomplished by using the YASARA STRUCTURE tool based on the AMBER14 force field with 400 snapshots every 250 ps. RMSD and RMSF plots were successfully obtained for each target. Results: The results of molecular docking have shown higher binding energy of dithymoquinone (DTQ), a compound of N. sativa against 3CLpro and Nsp15, i.e., −8.56 kcal/mol and −8.31 kcal/mol, respectively. Further, the dynamic simulation has shown good stability of DTQ against both the targeted enzymes. In addition, physicochemical evaluation and toxicity assessment also revealed that DTQ obeyed the Lipinski rule and did not have any toxic side effects. Importantly, DTQ was much better in every aspect among the 13 N. sativa compounds and 2 control compounds tested. Conclusions: The results predicted that DTQ is a potent therapeutic molecule that could dual-target both 3CLpro and NSP15 for anti-COVID therapy.

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Identifying the Most Potent Dual-Targeting Compound(s) against 3CLprotease and NSP15exonuclease of SARS-CoV-2 from Nigella sativa: Virtual Screening via Physicochemical Properties, Docking and Dynamic Simulation Analysis