Cargando…

Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus

The high pathogenic nature of the Middle East Respiratory coronavirus (MER) and the associated high fatality rate demands an urgent attention from researchers. Because there is currently no approved drug for the management of the disease, research efforts have been intensified towards the discovery...

Descripción completa

Detalles Bibliográficos
Autores principales: Adegbola, Aanuoluwa Eunice, Fadahunsi, Olumide Samuel, Alausa, Abdulahi, Abijo, Ayodeji Zabdiel, Balogun, Toheeb Adewale, Aderibigbe, Taiwo Sarah, Semire, Banjo, Adegbola, Peter Ifeoluwa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161736/
https://www.ncbi.nlm.nih.gov/pubmed/34075339
http://dx.doi.org/10.1016/j.imu.2021.100617
_version_ 1783700563822641152
author Adegbola, Aanuoluwa Eunice
Fadahunsi, Olumide Samuel
Alausa, Abdulahi
Abijo, Ayodeji Zabdiel
Balogun, Toheeb Adewale
Aderibigbe, Taiwo Sarah
Semire, Banjo
Adegbola, Peter Ifeoluwa
author_facet Adegbola, Aanuoluwa Eunice
Fadahunsi, Olumide Samuel
Alausa, Abdulahi
Abijo, Ayodeji Zabdiel
Balogun, Toheeb Adewale
Aderibigbe, Taiwo Sarah
Semire, Banjo
Adegbola, Peter Ifeoluwa
author_sort Adegbola, Aanuoluwa Eunice
collection PubMed
description The high pathogenic nature of the Middle East Respiratory coronavirus (MER) and the associated high fatality rate demands an urgent attention from researchers. Because there is currently no approved drug for the management of the disease, research efforts have been intensified towards the discovery of a potent drug for the treatment of the disease. Papain Like protease (PLpro) is one of the key proteins involved in the viral replication. We therefore docked forty-six compounds already characterized from Azadirachta indica, Xylopia aethipica and Allium cepa against MERS-CoV-PLpro. The molecular docking analysis was performed with AutoDock 1.5.6 and compounds which exhibit more negative free energy of binding, and low inhibition constant (Ki) with the protein (MERS-CoV-PLpro) were considered potent. The physicochemical and pharmacokinetic properties of the compounds were predicted using the Swissadme web server. Twenty-two of the compounds showed inhibition potential similar to dexamethasone and remdesvir, which had binding affinity of −6.8 and −6.3 kcal/mol respectively. The binding affinity of the compounds ranged between −3.4 kcal/mol and −7.7 kcal/mol whereas; hydroxychloroquine had a binding affinity of −4.5 kcal/mol. Among all the compounds, nimbanal and verbenone showed drug likeliness, they did not violate the Lipinski rule neither were they inhibitors of drug-metabolizing enzymes. Both nimbanal and verbenone were further post-scored with MM/GBSA and the binding free energy of nimbanal (−25.51 kcal/mol) was comparable to that of dexamethasone (−25.46 kcal/mol). The RMSD, RMSF, torsional angle, and other analysis following simulation further substantiate the efficacy of nimbanal as an effective drug candidate. In conclusion, our study showed that nimbanal is a more promising therapeutic agent and could be a lead for the discovery of a new drug that may be useful in the management of severe respiratory coronavirus syndrome.
format Online
Article
Text
id pubmed-8161736
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher The Authors. Published by Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-81617362021-05-28 Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus Adegbola, Aanuoluwa Eunice Fadahunsi, Olumide Samuel Alausa, Abdulahi Abijo, Ayodeji Zabdiel Balogun, Toheeb Adewale Aderibigbe, Taiwo Sarah Semire, Banjo Adegbola, Peter Ifeoluwa Inform Med Unlocked Article The high pathogenic nature of the Middle East Respiratory coronavirus (MER) and the associated high fatality rate demands an urgent attention from researchers. Because there is currently no approved drug for the management of the disease, research efforts have been intensified towards the discovery of a potent drug for the treatment of the disease. Papain Like protease (PLpro) is one of the key proteins involved in the viral replication. We therefore docked forty-six compounds already characterized from Azadirachta indica, Xylopia aethipica and Allium cepa against MERS-CoV-PLpro. The molecular docking analysis was performed with AutoDock 1.5.6 and compounds which exhibit more negative free energy of binding, and low inhibition constant (Ki) with the protein (MERS-CoV-PLpro) were considered potent. The physicochemical and pharmacokinetic properties of the compounds were predicted using the Swissadme web server. Twenty-two of the compounds showed inhibition potential similar to dexamethasone and remdesvir, which had binding affinity of −6.8 and −6.3 kcal/mol respectively. The binding affinity of the compounds ranged between −3.4 kcal/mol and −7.7 kcal/mol whereas; hydroxychloroquine had a binding affinity of −4.5 kcal/mol. Among all the compounds, nimbanal and verbenone showed drug likeliness, they did not violate the Lipinski rule neither were they inhibitors of drug-metabolizing enzymes. Both nimbanal and verbenone were further post-scored with MM/GBSA and the binding free energy of nimbanal (−25.51 kcal/mol) was comparable to that of dexamethasone (−25.46 kcal/mol). The RMSD, RMSF, torsional angle, and other analysis following simulation further substantiate the efficacy of nimbanal as an effective drug candidate. In conclusion, our study showed that nimbanal is a more promising therapeutic agent and could be a lead for the discovery of a new drug that may be useful in the management of severe respiratory coronavirus syndrome. The Authors. Published by Elsevier Ltd. 2021 2021-05-28 /pmc/articles/PMC8161736/ /pubmed/34075339 http://dx.doi.org/10.1016/j.imu.2021.100617 Text en © 2021 The Authors 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
Adegbola, Aanuoluwa Eunice
Fadahunsi, Olumide Samuel
Alausa, Abdulahi
Abijo, Ayodeji Zabdiel
Balogun, Toheeb Adewale
Aderibigbe, Taiwo Sarah
Semire, Banjo
Adegbola, Peter Ifeoluwa
Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus
title Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus
title_full Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus
title_fullStr Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus
title_full_unstemmed Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus
title_short Computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus
title_sort computational prediction of nimbanal as potential antagonist of respiratory syndrome coronavirus
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161736/
https://www.ncbi.nlm.nih.gov/pubmed/34075339
http://dx.doi.org/10.1016/j.imu.2021.100617
work_keys_str_mv AT adegbolaaanuoluwaeunice computationalpredictionofnimbanalaspotentialantagonistofrespiratorysyndromecoronavirus
AT fadahunsiolumidesamuel computationalpredictionofnimbanalaspotentialantagonistofrespiratorysyndromecoronavirus
AT alausaabdulahi computationalpredictionofnimbanalaspotentialantagonistofrespiratorysyndromecoronavirus
AT abijoayodejizabdiel computationalpredictionofnimbanalaspotentialantagonistofrespiratorysyndromecoronavirus
AT baloguntoheebadewale computationalpredictionofnimbanalaspotentialantagonistofrespiratorysyndromecoronavirus
AT aderibigbetaiwosarah computationalpredictionofnimbanalaspotentialantagonistofrespiratorysyndromecoronavirus
AT semirebanjo computationalpredictionofnimbanalaspotentialantagonistofrespiratorysyndromecoronavirus
AT adegbolapeterifeoluwa computationalpredictionofnimbanalaspotentialantagonistofrespiratorysyndromecoronavirus