title: Using self-organizing map (SOM) and support vector machine (SVM) for classification of selectivity of ACAT inhibitors.
abstract: Using a self-organizing map (SOM) and support vector machine, two classification models were built to predict whether a compound is a selective inhibitor toward the two Acyl-coenzyme A: cholesterol acyltransferase (ACAT) isozymes, ACAT-1 and ACAT-2. A dataset of 97 ACAT inhibitors was collected. For each molecule, the global descriptors, 2D and 3D property autocorrelation descriptors and autocorrelation of surface properties were calculated from the program ADRIANA.Code. The prediction accuracies of the models (based on the training/ test set splitting by SOM method) for the test sets are 88.9 % for SOM1, 92.6 % for SVM1 model. In addition, the extended connectivity fingerprints (ECFP_4) for all the molecules were calculated and the structure-activity relationship of selective ACAT inhibitors was summarized, which may help find important structural features of inhibitors relating to the selectivity of ACAT isozymes.
authors.affiliation: School of Chemistry and Chemical Engineering, Key Laboratory for Green Process of Chemical Engineering of Xinjiang Bingtuan, Shihezi University, Xinjiang, Shihezi 832003, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Wang
authors.forename: Maolin
authors.initials: M
authors.lastname: Wang
authors.forename: Aixia
authors.initials: A
authors.lastname: Yan
authors.forename: Bin
authors.initials: B
authors.lastname: Dai
mesh_terms: D050197:Atherosclerosis / Q000188:drug therapy; D003201:Computers; D006801:Humans; D012984:Software; D002785:Sterol O-Acyltransferase / Q000037:antagonists & inhibitors*; D013329:Structure-Activity Relationship; D060388:Support Vector Machine; D000097587:Sterol O-Acyltransferase 2
chemical_list: D002785:Sterol O-Acyltransferase; D000097587:Sterol O-Acyltransferase 2; C493492:sterol O-acyltransferase 1