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In silico investigation and identification of bioactive compounds from medicinal plants as potential inhibitors against SARS-CoV-2 cellular entry
Coronavirus Drug Discovery: Druggable Targets and In Silico Update: Volume 3 ; : 355-376, 2022.
Article in English | Scopus | ID: covidwho-2149156
ABSTRACT
The present study conducted an in silico investigation and identifications of bioactive compounds from medicinal plants against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) cellular entry. Thirty nine (39) bioactive compounds with evidence of in vitro or in vivo antidiabetic activities from medicinal plants were utilized in order to provide insight about their possible inhibitory potentials against SARS-CoV-2 cellular entry. Results from this study showed that silymarin, sanguinarine, withanolides, boswellic acids, fisetin, celastrol, neferine, ursolic acid, rutin, gambogic acid, quercetin, and luteolin expressed multiple binding capacity against nucleocapsid dimerization domain (−10.7 to −8.4kcal/mol), spike's protein binding domain (−10.0 to −8.1kcal/mol), and spike receptor-binding domain (−10.8 to −9.0kcal/mol) compared to lopinavir and remdesivir which were used as reference compounds in the study. However, withanolides, fisetin, luteolin, sanguinarine, and silymarin are most druggable phytochemicals as they obey the Lipinski's rule of five analyses with no signs of in silico predictory toxicity. Thus, they are recommended for further studies for the development of phytotherapy formulation to combat SARS-CoV-2 disease. © 2022 Elsevier Inc. All rights reserved.
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Full text: Available Collection: Databases of international organizations Database: Scopus Topics: Traditional medicine Language: English Journal: Coronavirus Drug Discovery: Druggable Targets and In Silico Update: Volume 3 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Topics: Traditional medicine Language: English Journal: Coronavirus Drug Discovery: Druggable Targets and In Silico Update: Volume 3 Year: 2022 Document Type: Article