ArticleMolecular diversity2011
A classification study of human β₃-adrenergic receptor agonists using BCUT descriptors.
Article in Molecular diversity, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Binding Constants of Substituted Benzoic Acids with Bovine Serum Albumin.Pharmaceuticals (Basel, Switzerland) · 2020Article
- Systems Pharmacology for Investigation of the Mechanisms of Action of Traditional Chinese Medicine in Drug Discovery.Frontiers in pharmacology · 2019Review
- A new chemoinformatics approach with improved strategies for effective predictions of potential drugs.Journal of cheminformatics · 2018Article
- Using self-organizing map (SOM) and support vector machine (SVM) for classification of selectivity of ACAT inhibitors.Molecular diversity · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Experimental EC(50)s for 202 human β(3)-AR agonists are used to develop classification models as a potential screening tool for a large library of target compounds before synthesis. A variable selection approach from random forests (VS-RF) is used to extract the structural information most relevant to the human β(3)-AR activation properties of the collected data set. The obtained results indicate that the VS-RF method can be used for variable selection with smallest sets of non-redundant descriptors with highly predictive accuracy (Q (ex)% = 96% for the external prediction set). Thus, the proposed VS-RF models should be helpful for screening of potential human β(3)-AR agonists before chemical synthesis in drug development.
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Registered trials
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