Molecular docking, simulation and MM-PBSA studies of nigella sativa compounds: a computational quest to identify potential natural antiviral for COVID-19 treatment

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Abstract

Nigella sativa or black seed is used as a medicinal plant around the globe. Oil and seeds have a long tradition of folklore use in various medicinal and food systems. The conventional therapeutic use of Nigella sativa, in different ways, has been reported in several studies to treat different diseases including influenza, headache, hypertension, diabetes, inflammation, eczema, fever, cough, asthma, bronchitis, and fever. Based on previously reported potential therapeutic uses of N. sativa compounds, and keeping in mind the dire need of time for the development of potent antiviral, a combined docking, ADMET properties calculation, molecular dynamics, and MM-PBSA approaches were applied in the current study to check the therapeutic potentials of N. sativa chief constituents against COVID-19. Among the studied compounds, we found that dithymoquinone (DTQ), with binding affinity of −8.6 kcal/mol compared to a positive control (chloroquine, −7.2 kcal/mol), has the high potential of binding at SARS-CoV-2:ACE2 interface and thus could be predicted as a plausible inhibitor to disrupt viral-host interactions. Molecular dynamics simulation of 100 ns well complemented binding affinity of the compound and revealed strong stability of DTQ at the docked site. Additionally, MM-PBSA also affirms the docking results. Compound DTQ of the present study, if validated in wet lab experiments, could be used to treat COVID-19 and could serve as a lead in the future for development of more effective natural antivirals against COVID-19. Communicated by Ramaswamy H. Sarma.

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Ahmad, S., Abbasi, H. W., Shahid, S., Gul, S., & Abbasi, S. W. (2021). Molecular docking, simulation and MM-PBSA studies of nigella sativa compounds: a computational quest to identify potential natural antiviral for COVID-19 treatment. Journal of Biomolecular Structure and Dynamics, 39(12), 4225–4233. https://doi.org/10.1080/07391102.2020.1775129

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