In silico identification of novel SARS-COV-2 2′-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches

The novel coronavirus disease COVID-19, caused by the virus SARS CoV-2, has exerted a significant unprecedented economic and medical crisis, in addition to its impact on the daily life and health care systems all over the world. Regrettably, no vaccines or drugs are currently available for this new...

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Main Authors: Mahmoud A. El Hassab, Tamer M. Ibrahim, Sara T. Al-Rashood, Amal Alharbi, Razan O. Eskandrani, Wagdy M. Eldehna
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Journal of Enzyme Inhibition and Medicinal Chemistry
Subjects:
Online Access:http://dx.doi.org/10.1080/14756366.2021.1885396
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spelling doaj-98234b16b4e14c1eaae68e930447cbd72021-03-18T15:12:46ZengTaylor & Francis GroupJournal of Enzyme Inhibition and Medicinal Chemistry1475-63661475-63742021-01-0136172773610.1080/14756366.2021.18853961885396In silico identification of novel SARS-COV-2 2′-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approachesMahmoud A. El Hassab0Tamer M. Ibrahim1Sara T. Al-Rashood2Amal Alharbi3Razan O. Eskandrani4Wagdy M. Eldehna5Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Badr University in Cairo (BUC)Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Kafrelsheikh UniversityDepartment of Pharmaceutical Chemistry, College of Pharmacy, King Saud UniversityDepartment of Pharmaceutical Chemistry, College of Pharmacy, King Saud UniversityDepartment of Pharmaceutical Chemistry, College of Pharmacy, King Saud UniversityDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Kafrelsheikh UniversityThe novel coronavirus disease COVID-19, caused by the virus SARS CoV-2, has exerted a significant unprecedented economic and medical crisis, in addition to its impact on the daily life and health care systems all over the world. Regrettably, no vaccines or drugs are currently available for this new critical emerging human disease. Joining the global fight against COVID-19, in this study we aim at identifying a potential novel inhibitor for SARS COV-2 2′-O-methyltransferase (nsp16) which is one of the most attractive targets in the virus life cycle, responsible for the viral RNA protection via a cap formation process. Firstly, nsp16 enzyme bound to Sinefungin was retrieved from the protein data bank (PDB ID: 6WKQ), then, a 3D pharmacophore model was constructed to be applied to screen 48 Million drug-like compounds of the Zinc database. This resulted in only 24 compounds which were subsequently docked into the enzyme. The best four score-ordered hits from the docking outcome exhibited better scores compared to Sinefungin. Finally, three molecular dynamics (MD) simulation experiments for 150 ns were carried out as a refinement step for our proposed approach. The MD and MM-PBSA outputs revealed compound 11 as the best potential nsp16 inhibitor herein identified, as it displayed a better stability and average binding free energy for the ligand-enzyme complex compared to Sinefungin.http://dx.doi.org/10.1080/14756366.2021.1885396sars cov-2 2′-o-methyltransferase (nsp16) inhibitor3d pharmacophoremolecular dynamicsmm-pbsa calculationscovid-19 therapies
collection DOAJ
language English
format Article
sources DOAJ
author Mahmoud A. El Hassab
Tamer M. Ibrahim
Sara T. Al-Rashood
Amal Alharbi
Razan O. Eskandrani
Wagdy M. Eldehna
spellingShingle Mahmoud A. El Hassab
Tamer M. Ibrahim
Sara T. Al-Rashood
Amal Alharbi
Razan O. Eskandrani
Wagdy M. Eldehna
In silico identification of novel SARS-COV-2 2′-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches
Journal of Enzyme Inhibition and Medicinal Chemistry
sars cov-2 2′-o-methyltransferase (nsp16) inhibitor
3d pharmacophore
molecular dynamics
mm-pbsa calculations
covid-19 therapies
author_facet Mahmoud A. El Hassab
Tamer M. Ibrahim
Sara T. Al-Rashood
Amal Alharbi
Razan O. Eskandrani
Wagdy M. Eldehna
author_sort Mahmoud A. El Hassab
title In silico identification of novel SARS-COV-2 2′-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches
title_short In silico identification of novel SARS-COV-2 2′-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches
title_full In silico identification of novel SARS-COV-2 2′-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches
title_fullStr In silico identification of novel SARS-COV-2 2′-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches
title_full_unstemmed In silico identification of novel SARS-COV-2 2′-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches
title_sort in silico identification of novel sars-cov-2 2′-o-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and mm-pbsa approaches
publisher Taylor & Francis Group
series Journal of Enzyme Inhibition and Medicinal Chemistry
issn 1475-6366
1475-6374
publishDate 2021-01-01
description The novel coronavirus disease COVID-19, caused by the virus SARS CoV-2, has exerted a significant unprecedented economic and medical crisis, in addition to its impact on the daily life and health care systems all over the world. Regrettably, no vaccines or drugs are currently available for this new critical emerging human disease. Joining the global fight against COVID-19, in this study we aim at identifying a potential novel inhibitor for SARS COV-2 2′-O-methyltransferase (nsp16) which is one of the most attractive targets in the virus life cycle, responsible for the viral RNA protection via a cap formation process. Firstly, nsp16 enzyme bound to Sinefungin was retrieved from the protein data bank (PDB ID: 6WKQ), then, a 3D pharmacophore model was constructed to be applied to screen 48 Million drug-like compounds of the Zinc database. This resulted in only 24 compounds which were subsequently docked into the enzyme. The best four score-ordered hits from the docking outcome exhibited better scores compared to Sinefungin. Finally, three molecular dynamics (MD) simulation experiments for 150 ns were carried out as a refinement step for our proposed approach. The MD and MM-PBSA outputs revealed compound 11 as the best potential nsp16 inhibitor herein identified, as it displayed a better stability and average binding free energy for the ligand-enzyme complex compared to Sinefungin.
topic sars cov-2 2′-o-methyltransferase (nsp16) inhibitor
3d pharmacophore
molecular dynamics
mm-pbsa calculations
covid-19 therapies
url http://dx.doi.org/10.1080/14756366.2021.1885396
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