title: A classification study of human β₃-adrenergic receptor agonists using BCUT descriptors.
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.
authors.affiliation: Department of Materials Science and Chemical Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China.
authors.forename: Ming
authors.initials: M
authors.lastname: Hao
authors.forename: Yan
authors.initials: Y
authors.lastname: Li
authors.forename: Yonghua
authors.initials: Y
authors.lastname: Wang
authors.forename: Shuwei
authors.initials: S
authors.lastname: Zhang
mesh_terms: D058667:Adrenergic beta-3 Receptor Agonists / Q000737:chemistry / Q000494:pharmacology*; D000465:Algorithms; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D006801:Humans; D025341:Principal Component Analysis; D021281:Quantitative Structure-Activity Relationship; D022702:Receptors, Adrenergic, beta-3 / Q000378:metabolism*; D015203:Reproducibility of Results; D054852:Small Molecule Libraries / Q000737:chemistry / Q000494:pharmacology; D060388:Support Vector Machine
chemical_list: D058667:Adrenergic beta-3 Receptor Agonists; D022702:Receptors, Adrenergic, beta-3; D054852:Small Molecule Libraries