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An Integrative in silico Drug Repurposing Approach for Identification of Potential Inhibitors of SARS-CoV-2 Main Protease.
- Source :
-
Molecular informatics [Mol Inform] 2021 May; Vol. 40 (5), pp. e2000187. Date of Electronic Publication: 2021 Mar 30. - Publication Year :
- 2021
-
Abstract
- Considering the urgent need for novel therapeutics in ongoing COVID-19 pandemic, drug repurposing approach might offer rapid solutions comparing to de novo drug design. In this study, we designed an integrative in silico drug repurposing approach for rapid selection of potential candidates against SARS-CoV-2 Main Protease (M <superscript>pro</superscript> ). To screen FDA-approved drugs, we implemented structure-based molecular modelling techniques, physiologically-based pharmacokinetic (PBPK) modelling of drugs disposition and data mining analysis of drug-gene-COVID-19 association. Through presented approach, we selected the most promising FDA approved drugs for further COVID-19 drug development campaigns and analysed them in context of available experimental data. To the best of our knowledge, this is unique in silico study which integrates structure-based molecular modeling of M <superscript>pro</superscript> inhibitors with predictions of their tissue disposition, drug-gene-COVID-19 associations and prediction of pleiotropic effects of selected candidates.<br /> (© 2021 Wiley-VCH GmbH.)
- Subjects :
- Antiviral Agents chemistry
Computer Simulation
Drug Design
Humans
Molecular Docking Simulation
Protease Inhibitors chemistry
SARS-CoV-2 drug effects
Viral Matrix Proteins metabolism
Antiviral Agents pharmacology
Drug Repositioning methods
Protease Inhibitors pharmacology
SARS-CoV-2 enzymology
Viral Matrix Proteins antagonists & inhibitors
COVID-19 Drug Treatment
Subjects
Details
- Language :
- English
- ISSN :
- 1868-1751
- Volume :
- 40
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Molecular informatics
- Publication Type :
- Academic Journal
- Accession number :
- 33787066
- Full Text :
- https://doi.org/10.1002/minf.202000187