Cargando…

Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach

The sudden outbreak of novel coronavirus has caused a global concern due to its infection rate and mortality. Despite extensive research, there are still no specific drugs or vaccines to combat SARS-CoV-2 infection. Hence, this study was designed to evaluate some plant-based active compounds for dru...

Descripción completa

Detalles Bibliográficos
Autores principales: Azim, Kazi Faizul, Ahmed, Sheikh Rashel, Banik, Anik, Khan, Md Mostafigur Rahman, Deb, Anamika, Somana, Saneya Risa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7280834/
https://www.ncbi.nlm.nih.gov/pubmed/32537482
http://dx.doi.org/10.1016/j.imu.2020.100367
_version_ 1783543796252803072
author Azim, Kazi Faizul
Ahmed, Sheikh Rashel
Banik, Anik
Khan, Md Mostafigur Rahman
Deb, Anamika
Somana, Saneya Risa
author_facet Azim, Kazi Faizul
Ahmed, Sheikh Rashel
Banik, Anik
Khan, Md Mostafigur Rahman
Deb, Anamika
Somana, Saneya Risa
author_sort Azim, Kazi Faizul
collection PubMed
description The sudden outbreak of novel coronavirus has caused a global concern due to its infection rate and mortality. Despite extensive research, there are still no specific drugs or vaccines to combat SARS-CoV-2 infection. Hence, this study was designed to evaluate some plant-based active compounds for drug candidacy against SARS-CoV-2 by using virtual screening methods and various computational analyses. A total of 27 plant metabolites were screened against SARS-CoV-2 main protease proteins (MPP), Nsp9 RNA binding protein, spike receptor binding domain, spike ecto-domain and HR2 domain using a molecular docking approach. Four metabolites, i.e., asiatic acid, avicularin, guajaverin, and withaferin showed maximum binding affinity with all key proteins in terms of lowest global binding energy. The crucial binding sites and drug surface hotspots were unravelled for each viral protein. The top candidates were further employed for ADME (absorption, distribution, metabolism, and excretion) analysis to investigate their drug profiles. Results suggest that none of the compounds render any undesirable consequences that could reduce their drug likeness properties. The analysis of toxicity pattern revealed no significant tumorigenic, mutagenic, irritating, or reproductive effects by the compounds. However, withaferin was comparatively toxic among the top four candidates with considerable cytotoxicity and immunotoxicity. Most of the target class by top drug candidates belonged to enzyme groups (e.g. oxidoreductases hydrolases, phosphatases). Moreover, results of drug similarity prediction revealed two approved structural analogs of Asiatic acid i.e. Hydrocortisone (DB00741) (previously used for SARS-CoV-1 and MERS) and Dinoprost-tromethamine (DB01160) from DrugBank. In addition, two other biologically active compounds, Mupirocin (DB00410) and Simvastatin (DB00641) could be an option for the treatment of viral infections. The study may pave the way to develop effective medications and preventive measure against SARS-CoV-2. Due to the encouraging results, we highly recommend further in vivo trials for the experimental validation of our findings.
format Online
Article
Text
id pubmed-7280834
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher The Authors. Published by Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-72808342020-06-09 Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach Azim, Kazi Faizul Ahmed, Sheikh Rashel Banik, Anik Khan, Md Mostafigur Rahman Deb, Anamika Somana, Saneya Risa Inform Med Unlocked Article The sudden outbreak of novel coronavirus has caused a global concern due to its infection rate and mortality. Despite extensive research, there are still no specific drugs or vaccines to combat SARS-CoV-2 infection. Hence, this study was designed to evaluate some plant-based active compounds for drug candidacy against SARS-CoV-2 by using virtual screening methods and various computational analyses. A total of 27 plant metabolites were screened against SARS-CoV-2 main protease proteins (MPP), Nsp9 RNA binding protein, spike receptor binding domain, spike ecto-domain and HR2 domain using a molecular docking approach. Four metabolites, i.e., asiatic acid, avicularin, guajaverin, and withaferin showed maximum binding affinity with all key proteins in terms of lowest global binding energy. The crucial binding sites and drug surface hotspots were unravelled for each viral protein. The top candidates were further employed for ADME (absorption, distribution, metabolism, and excretion) analysis to investigate their drug profiles. Results suggest that none of the compounds render any undesirable consequences that could reduce their drug likeness properties. The analysis of toxicity pattern revealed no significant tumorigenic, mutagenic, irritating, or reproductive effects by the compounds. However, withaferin was comparatively toxic among the top four candidates with considerable cytotoxicity and immunotoxicity. Most of the target class by top drug candidates belonged to enzyme groups (e.g. oxidoreductases hydrolases, phosphatases). Moreover, results of drug similarity prediction revealed two approved structural analogs of Asiatic acid i.e. Hydrocortisone (DB00741) (previously used for SARS-CoV-1 and MERS) and Dinoprost-tromethamine (DB01160) from DrugBank. In addition, two other biologically active compounds, Mupirocin (DB00410) and Simvastatin (DB00641) could be an option for the treatment of viral infections. The study may pave the way to develop effective medications and preventive measure against SARS-CoV-2. Due to the encouraging results, we highly recommend further in vivo trials for the experimental validation of our findings. The Authors. Published by Elsevier Ltd. 2020 2020-06-09 /pmc/articles/PMC7280834/ /pubmed/32537482 http://dx.doi.org/10.1016/j.imu.2020.100367 Text en © 2020 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
Azim, Kazi Faizul
Ahmed, Sheikh Rashel
Banik, Anik
Khan, Md Mostafigur Rahman
Deb, Anamika
Somana, Saneya Risa
Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach
title Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach
title_full Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach
title_fullStr Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach
title_full_unstemmed Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach
title_short Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach
title_sort screening and druggability analysis of some plant metabolites against sars-cov-2: an integrative computational approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7280834/
https://www.ncbi.nlm.nih.gov/pubmed/32537482
http://dx.doi.org/10.1016/j.imu.2020.100367
work_keys_str_mv AT azimkazifaizul screeninganddruggabilityanalysisofsomeplantmetabolitesagainstsarscov2anintegrativecomputationalapproach
AT ahmedsheikhrashel screeninganddruggabilityanalysisofsomeplantmetabolitesagainstsarscov2anintegrativecomputationalapproach
AT banikanik screeninganddruggabilityanalysisofsomeplantmetabolitesagainstsarscov2anintegrativecomputationalapproach
AT khanmdmostafigurrahman screeninganddruggabilityanalysisofsomeplantmetabolitesagainstsarscov2anintegrativecomputationalapproach
AT debanamika screeninganddruggabilityanalysisofsomeplantmetabolitesagainstsarscov2anintegrativecomputationalapproach
AT somanasaneyarisa screeninganddruggabilityanalysisofsomeplantmetabolitesagainstsarscov2anintegrativecomputationalapproach