Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants
- Publication type:
- Journal article
- Metadata:
-
- Autoren
- Ijaz Muhammad
- Noor Rahman
- Gul-E-Nayab
- Sadaf Niaz
- Zarrin Basharat
- Luca Rastrelli
- Sivaraman Jayanthi
- Thomas Efferth
- Haroon Khan
- Autoren-URL
- https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000656574900007&DestLinkType=FullRecord&DestApp=WOS_CPL
- DOI
- 10.1016/j.compbiomed.2021.104362
- eISSN
- 1879-0534
- Externe Identifier
- Clarivate Analytics Document Solution ID: SK9YV
- PubMed Identifier: 33894500
- ISSN
- 0010-4825
- Zeitschrift
- COMPUTERS IN BIOLOGY AND MEDICINE
- Schlüsselwörter
- Coronavirus
- Protease
- Mpro
- Natural products
- Docking
- Artikelnummer
- ARTN 104362
- Datum der Veröffentlichung
- 2021
- Status
- Published
- Titel
- Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants
- Sub types
- Article
- Ausgabe der Zeitschrift
- 133
Data source: Web of Science (Lite)
- Other metadata sources:
-
- Autoren
- Ijaz Muhammad
- Noor Rahman
- Gul-E-Nayab
- Sadaf Niaz
- Zarrin Basharat
- Luca Rastrelli
- Sivaraman Jayanthi
- Thomas Efferth
- Haroon Khan
- DOI
- 10.1016/j.compbiomed.2021.104362
- ISSN
- 0010-4825
- Zeitschrift
- Computers in Biology and Medicine
- Sprache
- en
- Artikelnummer
- 104362
- Paginierung
- 104362 - 104362
- Datum der Veröffentlichung
- 2021
- Status
- Published
- Herausgeber
- Elsevier BV
- Herausgeber URL
- http://dx.doi.org/10.1016/j.compbiomed.2021.104362
- Datum der Datenerfassung
- 2024
- Titel
- Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants
- Ausgabe der Zeitschrift
- 133
Data source: Crossref
- Abstract
- <h4>Background</h4>COVID-19, declared a pandemic in March 2020 by the World Health Organization is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The virus has already killed more than 2.3 million people worldwide.<h4>Object</h4>The principal intent of this work was to investigate lead compounds by screening natural product library (NPASS) for possible treatment of COVID-19.<h4>Methods</h4>Pharmacophore features were used to screen a large database to get a small dataset for structure-based virtual screening of natural product compounds. In the structure-based screening, molecular docking was performed to find a potent inhibitor molecule against the main protease (M<sup>pro</sup>) of SARS-CoV-2 (PDB ID: 6Y7M). The predicted lead compound was further subjected to Molecular Dynamics (MD) simulation to check the stability of the leads compound with the evolution of time.<h4>Results</h4>In pharmacophore-based virtual screening, 2,361 compounds were retained out of 30,927. In the structure-based screening, the lead compounds were filtered based on their docking scores. Among the 2,360 compounds, 12 lead compounds were selected based on their docking score. Kazinol T with NPASS ID: NPC474104 showed the highest docking score of -14.355 and passed criteria of Lipinski's drug-like parameters. Monitoring ADMET properties, Kazinol T showed its safety for consumption. Docking of Kazinol T with two Asian mutants (R60C and I152V) showed variations in binding and energy parameters. Normal mode analysis for ligand-bound and unbound form of protease along with its mutants, revealed displacement and correlation parameters for C-alpha atoms. MD simulation results showed that all ligand-protein complexes remained intact and stable in a dynamic environment with negative Gibbs free energy.<h4>Conclusions</h4>The natural product Kazinol T was a predicted lead compound against the main protease of SARS-CoV-2 and will be the possible treatment for COVID-19.
- Addresses
- Department of Zoology, Abdul Wali Khan University Mardan, 23200, Pakistan.
- Autoren
- Ijaz Muhammad
- Noor Rahman
- Gul-E-Nayab
- Sadaf Niaz
- Zarrin Basharat
- Luca Rastrelli
- Sivaraman Jayanthi
- Thomas Efferth
- Haroon Khan
- DOI
- 10.1016/j.compbiomed.2021.104362
- eISSN
- 1879-0534
- Externe Identifier
- PubMed Identifier: 33894500
- PubMed Central ID: PMC8051016
- Open access
- true
- ISSN
- 0010-4825
- Zeitschrift
- Computers in biology and medicine
- Schlüsselwörter
- Humans
- Peptide Hydrolases
- Protease Inhibitors
- Antiviral Agents
- Molecular Docking Simulation
- Phytochemicals
- COVID-19
- SARS-CoV-2
- Sprache
- eng
- Medium
- Print-Electronic
- Online publication date
- 2021
- Open access status
- Open Access
- Paginierung
- 104362
- Datum der Veröffentlichung
- 2021
- Status
- Published
- Datum der Datenerfassung
- 2021
- Titel
- Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants.
- Sub types
- research-article
- Journal Article
- Ausgabe der Zeitschrift
- 133
Files
https://europepmc.org/articles/PMC8051016?pdf=render
Data source: Europe PubMed Central
- Abstract
- BACKGROUND: COVID-19, declared a pandemic in March 2020 by the World Health Organization is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The virus has already killed more than 2.3 million people worldwide. OBJECT: The principal intent of this work was to investigate lead compounds by screening natural product library (NPASS) for possible treatment of COVID-19. METHODS: Pharmacophore features were used to screen a large database to get a small dataset for structure-based virtual screening of natural product compounds. In the structure-based screening, molecular docking was performed to find a potent inhibitor molecule against the main protease (Mpro) of SARS-CoV-2 (PDB ID: 6Y7M). The predicted lead compound was further subjected to Molecular Dynamics (MD) simulation to check the stability of the leads compound with the evolution of time. RESULTS: In pharmacophore-based virtual screening, 2,361 compounds were retained out of 30,927. In the structure-based screening, the lead compounds were filtered based on their docking scores. Among the 2,360 compounds, 12 lead compounds were selected based on their docking score. Kazinol T with NPASS ID: NPC474104 showed the highest docking score of -14.355 and passed criteria of Lipinski's drug-like parameters. Monitoring ADMET properties, Kazinol T showed its safety for consumption. Docking of Kazinol T with two Asian mutants (R60C and I152V) showed variations in binding and energy parameters. Normal mode analysis for ligand-bound and unbound form of protease along with its mutants, revealed displacement and correlation parameters for C-alpha atoms. MD simulation results showed that all ligand-protein complexes remained intact and stable in a dynamic environment with negative Gibbs free energy. CONCLUSIONS: The natural product Kazinol T was a predicted lead compound against the main protease of SARS-CoV-2 and will be the possible treatment for COVID-19.
- Date of acceptance
- 2021
- Autoren
- Ijaz Muhammad
- Noor Rahman
- Gul-E-Nayab
- Sadaf Niaz
- Zarrin Basharat
- Luca Rastrelli
- Sivaraman Jayanthi
- Thomas Efferth
- Haroon Khan
- Autoren-URL
- https://www.ncbi.nlm.nih.gov/pubmed/33894500
- DOI
- 10.1016/j.compbiomed.2021.104362
- eISSN
- 1879-0534
- Externe Identifier
- PubMed Central ID: PMC8051016
- Zeitschrift
- Comput Biol Med
- Schlüsselwörter
- Coronavirus
- Docking
- M(pro)
- Natural products
- Protease
- Antiviral Agents
- COVID-19
- Humans
- Molecular Docking Simulation
- Peptide Hydrolases
- Phytochemicals
- Protease Inhibitors
- SARS-CoV-2
- Sprache
- eng
- Country
- United States
- Paginierung
- 104362
- PII
- S0010-4825(21)00156-6
- Datum der Veröffentlichung
- 2021
- Status
- Published
- Datum, an dem der Datensatz öffentlich gemacht wurde
- 2021
- Titel
- Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants.
- Sub types
- Journal Article
- Ausgabe der Zeitschrift
- 133
Data source: PubMed
- Autoren
- Muhammad Ijaz
- Noor Rahman
- Gul-E-Nayab
- Sadaf Niaz
- Zarrin Basharat
- Luca Rastrelli
- Sivaraman Jayanthi
- Thomas Efferth
- Haroon Khan
- Zeitschrift
- Comput. Biol. Medicine
- Paginierung
- 104362 - 104362
- Datum der Veröffentlichung
- 2021
- Titel
- Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants.
- Ausgabe der Zeitschrift
- 133
Data source: DBLP
- Beziehungen:
- Property of