ArticleBioorganic & medicinal chemistry2013
Inhibitors for the hepatitis C virus RNA polymerase explored by SAR with advanced machine learning methods.
Article in Bioorganic & medicinal chemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 25 citations in OpenAlex.
- 1-Sulfonyl-3-amino-1ACS omega · 2023Article
- Development of Machine Learning Models and the Discovery of a New Antiviral Compound against Yellow Fever Virus.Journal of chemical information and modeling · 2021Article
- Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents.Molecular diversity · 2021Article
- Use of big data in drug development for precision medicine: an update.Expert review of precision medicine and drug development · 2019Article
- Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique.Analytica chimica acta · 2016Article
- Article
- Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.Journal of computational chemistry · 2015Article
- Finding candidate drugs for hepatitis C based on chemical-chemical and chemical-protein interactions.PloS one · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 1 country.
Funding
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.