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

Joint Authors

Iheagwam, Franklyn Nonso
Rotimi, Solomon Oladapo

Source

Scientifica

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-25, 25 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-09-14

Country of Publication

Egypt

No. of Pages

25

Main Subjects

Diseases

Abstract EN

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 (Terminalia catappa), grape (Vitis vinifera), and common verbena (Verbena officinalis), 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.

American Psychological Association (APA)

Iheagwam, Franklyn Nonso& Rotimi, Solomon Oladapo. 2020. Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants. Scientifica،Vol. 2020, no. 2020, pp.1-25.
https://search.emarefa.net/detail/BIM-1208127

Modern Language Association (MLA)

Iheagwam, Franklyn Nonso& Rotimi, Solomon Oladapo. Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants. Scientifica No. 2020 (2020), pp.1-25.
https://search.emarefa.net/detail/BIM-1208127

American Medical Association (AMA)

Iheagwam, Franklyn Nonso& Rotimi, Solomon Oladapo. Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants. Scientifica. 2020. Vol. 2020, no. 2020, pp.1-25.
https://search.emarefa.net/detail/BIM-1208127

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1208127