title: QSAR study of the enantiomeric excess in asymmetric catalytic reactions with topological indices and an artificial neural network.
abstract: The relationships between the enantiomer excess of product in catalytic asymmetric reactions and the structures of the catalysts or reagents in several asymmetric reactions were studied using a backpropagation (BP) neural network with topological indices and their chiral expansions. The trained network can be used to screen new asymmetric catalysts, estimate catalytic effects, design reaction environments, and prove or improve the proposed reaction mechanism.
authors.affiliation: Department of Chemistry, University of Science and Technology of China, Hefei, 230026, People's Republic of China.
authors.forename: Chen
authors.initials: C
authors.lastname: Jiang
authors.forename: Daliang
authors.initials: D
authors.lastname: Li
authors.forename: Jiwu
authors.initials: J
authors.lastname: Wen
authors.forename: Tianpa
authors.initials: T
authors.lastname: You
mesh_terms: D002384:Catalysis; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D015394:Molecular Structure; D016571:Neural Networks, Computer; D009930:Organic Chemicals; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D013237:Stereoisomerism
chemical_list: D009930:Organic Chemicals