title: Quantitative structure and bioactivity relationship study on human acetylcholinesterase inhibitors.
abstract: Several QSAR (Quantitative Structure-Activity Relationships) models for predicting the inhibitory activity of 404 Acetylcholinesterase inhibitors were developed. The whole dataset was split into a training set and a test set randomly or using a Kohonen's self-organizing map. Then the inhibitory activity of 404 Acetylcholinesterase inhibitors was predicted using Multilinear Regression (MLR) analysis and Support Vector Machine (SVM) methods, respectively. For the test sets, correlation coefficients of all our models over 0.90 were achieved. Y-randomization test was employed to ensure the robustness of our models and a docking simulation was used to confirm the descriptors we used.
authors.affiliation: State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, PO Box 53, Beijing University of Chemical Technology, 15 BeiSanHuan East Road, Beijing 100029, People's Republic of China. yanax@mail.buct.edu.cn
authors.forename: Aixia
authors.initials: A
authors.lastname: Yan
authors.forename: Kai
authors.initials: K
authors.lastname: Wang
mesh_terms: D002800:Cholinesterase Inhibitors / Q000378:metabolism / Q000494:pharmacology*; D003198:Computer Simulation; D006801:Humans; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D060388:Support Vector Machine
chemical_list: D002800:Cholinesterase Inhibitors