基于拓扑指数和人工神经网络的不对称催化反应对映体过量的定量构效关系研究

QSAR study of the enantiomeric excess in asymmetric catalytic reactions with topological indices and an artificial neural network.

作者信息

Jiang Chen, Li Daliang, Wen Jiwu, You Tianpa

机构信息

Department of Chemistry, University of Science and Technology of China, Hefei, 230026, People's Republic of China.

出版信息

J Mol Model. 2007 Jan;13(1):91-7. doi: 10.1007/s00894-006-0126-y. Epub 2006 Jun 15.

DOI:10.1007/s00894-006-0126-y

PMID:16775734

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.

摘要

利用具有拓扑指数及其手性扩展的反向传播（BP）神经网络，研究了催化不对称反应中产物对映体过量与几种不对称反应中催化剂或试剂结构之间的关系。训练后的网络可用于筛选新型不对称催化剂、评估催化效果、设计反应环境以及证明或改进所提出的反应机理。