QSAR study of the enantiomeric excess in asymmetric catalytic reactions with topological indices and an artificial neural network.
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.
Jiang
Chen
C
Department of Chemistry, University of Science and Technology of China, Hefei, 230026, People's Republic of China.
Li
Daliang
D
Wen
Jiwu
J
You
Tianpa
T
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
D009930:Organic Chemicals