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嘧啶硫代水杨酸衍生物的多元回归分析及神经网络法研究
引用本文:郭明,白红进,刘建平.嘧啶硫代水杨酸衍生物的多元回归分析及神经网络法研究[J].化学研究,2000,11(1):12-15.
作者姓名:郭明  白红进  刘建平
作者单位:塔里木农垦大学基础课部新疆阿拉尔843300
基金项目:国家自然科学基金,新疆生产建设兵团科委科研项目,29767001,NKB98TNDNR13NY,,
摘    要:通过量子化学方法计算了 1 4个新型嘧啶硫代水杨酸衍生物的量化参数 ,运用分子力学进行完全构象优化进而计算了分子几何形状等参数。对这些化合物抑制乙酰乳酸合成酶 (ALS)活性进行了QSAR分析 ,结果表明 ,空间因素及静电效应是影响构效关系的主要因素 ,神经网络法得到较优预测结果。

关 键 词:嘧啶硫代水杨酸  定量结构—活性相关性  神经网络
文章编号:1008-1011(2000)01-0012-04
修稿时间:1999年9月13日

Study on the Derivatives of Pyrimidinyl-thiobenzoic Acids Using multivariate regression analysis and Neural Network
Guo Ming,Bai Hongjin,Liu Jianping.Study on the Derivatives of Pyrimidinyl-thiobenzoic Acids Using multivariate regression analysis and Neural Network[J].Chemical Research,2000,11(1):12-15.
Authors:Guo Ming  Bai Hongjin  Liu Jianping
Abstract:In this paper,the semiempirical quantum chemistry calculations were undertaken for the fourteen derivatives of pyrimidinylthiobenzoic acids.The conformations were completely optimized to the title compounds and the molecular geometric shape and other parameters were also calculated.Quantitative structure_activity relationship between the title compounds and the inhibition to acetolactate synthetase(ALS) was investigated.The results of QSAR indicated that the steric and electrostatic effect were dominated mainly,the superior predictions were obtained, by neural network in this research.
Keywords:pyrimidinylthiobenzoic acids  quantitative structure_activity relationship  neural network
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