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Molecular modeling identification of potential drug candidates from selected African plants against SARS-CoV-2 key druggable proteins

Coronavirus disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the major health threats the world has experienced. In order to stem the tide of the virus and its associated disease, rapid efforts have been dedicated to identifying c...

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Autores principales: Uhomoibhi, J.O., Idowu, K.A., Shode, F.O., Sabiu, S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279166/
https://www.ncbi.nlm.nih.gov/pubmed/35856008
http://dx.doi.org/10.1016/j.sciaf.2022.e01279
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author Uhomoibhi, J.O.
Idowu, K.A.
Shode, F.O.
Sabiu, S
author_facet Uhomoibhi, J.O.
Idowu, K.A.
Shode, F.O.
Sabiu, S
author_sort Uhomoibhi, J.O.
collection PubMed
description Coronavirus disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the major health threats the world has experienced. In order to stem the tide of the virus and its associated disease, rapid efforts have been dedicated to identifying credible anti-SARS-CoV-2 drugs. This study forms part of the continuing efforts to develop anti-SARS-CoV-2 molecules and employed a computational structure-activity relationship approach with emphasis on 99 plant secondary metabolites from eight selected African medicinal plants with proven therapeutic benefits against respiratory diseases focusing on the viral protein targets [Spike protein (Sgp), Main protease (Mpro), and RNA-dependent RNA polymerase (RdRp)]. The results of the molecular dynamics simulation of the best docked compounds presented as binding free energy revealed that three compounds each against the Sgp (VBS, COG and ABA), and Mpro (COR, QOR and ABG) had higher and better affinity for the proteins than the respective reference drugs, cefoperazone (CSP) and Nelfinavir (NEF), while four compounds (HDG, VBS, COR and KOR) had higher and favorable binding affinity towards RdRp than the reference standard, ramdesivir (RDS). Analysis of interaction with the receptor binding domain amino acid residues of Sgp showed that VBS had the highest number of interactions (17) relative to 14 and 13 for COG and ABA, respectively. For Mpro, COR showed interactions with catalytic dyad residues (His172 and Cys145). Compared to RDS, COR, HDG, VBS and KOR formed 19, 18, 17 and 12 H-bond and Van der Waal bonds, respectively, with RdRp. Furthermore, structural examination of the three proteins after binding to the lead compounds revealed that the compounds formed stable complexes. These observations suggest that the identified compounds might be beneficial in the fight against COVID-19 and are suggested for further in vitro and in vivo experimental validation.
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spelling pubmed-92791662022-07-14 Molecular modeling identification of potential drug candidates from selected African plants against SARS-CoV-2 key druggable proteins Uhomoibhi, J.O. Idowu, K.A. Shode, F.O. Sabiu, S Sci Afr Article Coronavirus disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the major health threats the world has experienced. In order to stem the tide of the virus and its associated disease, rapid efforts have been dedicated to identifying credible anti-SARS-CoV-2 drugs. This study forms part of the continuing efforts to develop anti-SARS-CoV-2 molecules and employed a computational structure-activity relationship approach with emphasis on 99 plant secondary metabolites from eight selected African medicinal plants with proven therapeutic benefits against respiratory diseases focusing on the viral protein targets [Spike protein (Sgp), Main protease (Mpro), and RNA-dependent RNA polymerase (RdRp)]. The results of the molecular dynamics simulation of the best docked compounds presented as binding free energy revealed that three compounds each against the Sgp (VBS, COG and ABA), and Mpro (COR, QOR and ABG) had higher and better affinity for the proteins than the respective reference drugs, cefoperazone (CSP) and Nelfinavir (NEF), while four compounds (HDG, VBS, COR and KOR) had higher and favorable binding affinity towards RdRp than the reference standard, ramdesivir (RDS). Analysis of interaction with the receptor binding domain amino acid residues of Sgp showed that VBS had the highest number of interactions (17) relative to 14 and 13 for COG and ABA, respectively. For Mpro, COR showed interactions with catalytic dyad residues (His172 and Cys145). Compared to RDS, COR, HDG, VBS and KOR formed 19, 18, 17 and 12 H-bond and Van der Waal bonds, respectively, with RdRp. Furthermore, structural examination of the three proteins after binding to the lead compounds revealed that the compounds formed stable complexes. These observations suggest that the identified compounds might be beneficial in the fight against COVID-19 and are suggested for further in vitro and in vivo experimental validation. The Authors. Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative. 2022-09 2022-07-14 /pmc/articles/PMC9279166/ /pubmed/35856008 http://dx.doi.org/10.1016/j.sciaf.2022.e01279 Text en © 2022 The Authors. Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Uhomoibhi, J.O.
Idowu, K.A.
Shode, F.O.
Sabiu, S
Molecular modeling identification of potential drug candidates from selected African plants against SARS-CoV-2 key druggable proteins
title Molecular modeling identification of potential drug candidates from selected African plants against SARS-CoV-2 key druggable proteins
title_full Molecular modeling identification of potential drug candidates from selected African plants against SARS-CoV-2 key druggable proteins
title_fullStr Molecular modeling identification of potential drug candidates from selected African plants against SARS-CoV-2 key druggable proteins
title_full_unstemmed Molecular modeling identification of potential drug candidates from selected African plants against SARS-CoV-2 key druggable proteins
title_short Molecular modeling identification of potential drug candidates from selected African plants against SARS-CoV-2 key druggable proteins
title_sort molecular modeling identification of potential drug candidates from selected african plants against sars-cov-2 key druggable proteins
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279166/
https://www.ncbi.nlm.nih.gov/pubmed/35856008
http://dx.doi.org/10.1016/j.sciaf.2022.e01279
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