期刊
BIOORGANIC & MEDICINAL CHEMISTRY
卷 21, 期 11, 页码 3127-3137出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.bmc.2013.03.032
关键词
NS5B; RdRp; HCV; SAR; HCV-796; RDKit; Random Forest; k Nearest Neighbor Simulated Annealing; Candesartan cilexetil; Computational drug repositioning
资金
- National Cancer Institute, National Institutes of Health [N01-CO-12400]
- NIH, National Cancer Institute, Center for Cancer Research
- Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health, Department of Health and Human Services [HHSN272201100012I]
- National Institute of Health [CA153147]
- US National Science Foundation through the MRI program [CNS-0821258, CNS-1228778]
- SCREMS program [DMS-0821311]
- Direct For Computer & Info Scie & Enginr
- Division Of Computer and Network Systems [1228778] Funding Source: National Science Foundation
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 mu M. 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. (C) 2013 Elsevier Ltd. All rights reserved.
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