title: Chemometrics-based approach to modeling quantitative composition-activity relationships for Radix Tinosporae.
abstract: Quantitative composition-activity relationship (QCAR) study makes it possible to discover active components in traditional Chinese medicine (TCM) and to predict the integral bioactivity by its chemical composition. In the study, 28 samples of Radix Tinosporae were quantitatively analyzed by high performance liquid chromatography, and their analgesic activities were investigated via abdominal writhing tests on mice. Three genetic algorithms (GA) based approaches including partial least square regression, radial basis function neural network, and support vector regression (SVR) were established to construct QCAR models of R. Tinosporae. The result shows that GA-SVR has the best model performance in the bioactivity prediction of R. Tinosporae; seven major components thereof were discovered to have analgesic activities, and the analgesic activities of these components were partly confirmed by subsequent abdominal writhing test. The proposed approach allows discovering active components in TCM and predicting bioactivity by its chemical composition, and is expected to be utilized as a supplementary tool for the quality control and drug discovery of TCM.
authors.affiliation: School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Shi-Kai
authors.initials: SK
authors.lastname: Yan
authors.forename: Zhong-Ying
authors.initials: ZY
authors.lastname: Lin
authors.forename: Wei-Xing
authors.initials: WX
authors.lastname: Dai
authors.forename: Qi-Rong
authors.initials: QR
authors.lastname: Shi
authors.forename: Xiao-Hua
authors.initials: XH
authors.lastname: Liu
authors.forename: Hui-Zi
authors.initials: HZ
authors.lastname: Jin
authors.forename: Wei-Dong
authors.initials: WD
authors.lastname: Zhang
mesh_terms: D015746:Abdominal Pain; D000465:Algorithms; D000700:Analgesics / Q000032:analysis* / Q000737:chemistry / Q000494:pharmacology; D000818:Animals; D001522:Behavior, Animal / Q000187:drug effects; D002851:Chromatography, High Pressure Liquid; D055808:Drug Discovery; D004365:Drugs, Chinese Herbal / Q000737:chemistry* / Q000494:pharmacology; D016018:Least-Squares Analysis; D008297:Male; D008516:Medicine, Chinese Traditional; D051379:Mice; D008813:Mice, Inbred ICR; D008954:Models, Biological; D018517:Plant Roots; D011786:Quality Control; D012044:Regression Analysis; D013329:Structure-Activity Relationship; D060388:Support Vector Machine; D031610:Tinospora / Q000737:chemistry*
chemical_list: D000700:Analgesics; D004365:Drugs, Chinese Herbal