Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants.

Iheagwam, Franklyn Nonso and Rotimi, Solomon Oladapo (2020) Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants. Scientifica, 2020. p. 1878410. ISSN 2090-908X

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Abstract

The COVID-19 pandemic, which started in Wuhan, China, has spread rapidly over the world with no known antiviral therapy or vaccine. Interestingly, traditional Chinese medicine helped in flattening the pandemic curve in China. In this study, molecules from African medicinal plants were analysed as potential candidates against multiple SARS-CoV-2 therapeutic targets. Sixty-five molecules from the ZINC database subset (AfroDb Natural Products) were virtually screened with some reported repurposed therapeutics against six SARS-CoV-2 and two human targets. Molecular docking, druglikeness, absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the best hits were further simulated. Of the 65 compounds, only three, namely, 3-galloylcatechin, proanthocyanidin B1, and luteolin 7-galactoside found in almond (), grape (), and common verbena (), were able to bind to all eight targets better than the reported repurposed drugs. The findings suggest these molecules may play a role as therapeutic leads in tackling this pandemic due to their multitarget activity.

Item Type:	Article
Subjects:	Q Science > Q Science (General)
Divisions:	UNSPECIFIED
Depositing User:	Franklyn N IHEAGWAM
Date Deposited:	20 Jun 2021 21:49
Last Modified:	20 Jun 2021 21:49
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/14759

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