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Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants
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 po...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492903/ https://www.ncbi.nlm.nih.gov/pubmed/32963884 http://dx.doi.org/10.1155/2020/1878410 |
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author | Iheagwam, Franklyn Nonso Rotimi, Solomon Oladapo |
author_facet | Iheagwam, Franklyn Nonso Rotimi, Solomon Oladapo |
author_sort | Iheagwam, Franklyn Nonso |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7492903 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-74929032020-09-21 Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants Iheagwam, Franklyn Nonso Rotimi, Solomon Oladapo Scientifica (Cairo) Research Article 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. Hindawi 2020-09-12 /pmc/articles/PMC7492903/ /pubmed/32963884 http://dx.doi.org/10.1155/2020/1878410 Text en Copyright © 2020 Franklyn Nonso Iheagwam and Solomon Oladapo Rotimi. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Iheagwam, Franklyn Nonso Rotimi, Solomon Oladapo Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants |
title | Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants |
title_full | Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants |
title_fullStr | Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants |
title_full_unstemmed | Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants |
title_short | Computer-Aided Analysis of Multiple SARS-CoV-2 Therapeutic Targets: Identification of Potent Molecules from African Medicinal Plants |
title_sort | computer-aided analysis of multiple sars-cov-2 therapeutic targets: identification of potent molecules from african medicinal plants |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492903/ https://www.ncbi.nlm.nih.gov/pubmed/32963884 http://dx.doi.org/10.1155/2020/1878410 |
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