Abstract
Hepatitis C virus (HCV) is a global health challenge, affecting approximately 200 million people worldwide. In this study we developed SAR models with advanced machine learning classifiers Random Forest and k Nearest Neighbor Simulated Annealing for 679 small molecules with measured inhibition activity for NS5B genotype 1b. The activity was expressed as a binary value (active/inactive), where actives were considered molecules with IC50 ≤0.95 μM. We applied our SAR models to various drug-like databases and identified novel chemical scaffolds for NS5B inhibitors. Subsequent in vitro antiviral assays suggested a new activity for an existing prodrug, Candesartan cilexetil, which is currently used to treat hypertension and heart failure but has not been previously tested for anti-HCV activity. We also identified NS5B inhibitors with two novel non-nucleoside chemical motifs.
Copyright © 2013 Elsevier Ltd. All rights reserved.
Publication types
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Research Support, N.I.H., Extramural
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Research Support, N.I.H., Intramural
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Research Support, Non-U.S. Gov't
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Research Support, U.S. Gov't, Non-P.H.S.
MeSH terms
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Antihypertensive Agents / chemistry*
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Antiviral Agents / chemistry*
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Artificial Intelligence
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Benzimidazoles / chemistry*
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Biphenyl Compounds / chemistry*
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Databases, Chemical
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Drug Discovery
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Drug Repositioning
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Hepacivirus / chemistry
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Hepacivirus / enzymology
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Molecular Docking Simulation
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RNA-Dependent RNA Polymerase / antagonists & inhibitors*
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RNA-Dependent RNA Polymerase / chemistry
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ROC Curve
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Structure-Activity Relationship
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Tetrazoles / chemistry*
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Viral Nonstructural Proteins / antagonists & inhibitors*
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Viral Nonstructural Proteins / chemistry
Substances
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Antihypertensive Agents
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Antiviral Agents
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Benzimidazoles
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Biphenyl Compounds
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Tetrazoles
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Viral Nonstructural Proteins
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NS-5 protein, hepatitis C virus
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RNA-Dependent RNA Polymerase
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candesartan cilexetil