Autocorrelation modeling of lipophilicity with a back-propagation neural network

被引：18
|
作者：
Devillers, J [1 ]
Domine, D [1 ]
Guillon, C [1 ]
机构：
[1] CTIS, F-69140 Rillieux La Pape, France
来源：
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY | 1998年 / 33卷 / 7-8期
关键词：
n-octanol; water partition coefficient; autocorrelation method; back-propagation neural network AUTOLOGP (TM) (version 4.0);
D O I：
10.1016/S0223-5234(98)80024-X
中图分类号：
R914 [药物化学];
学科分类号：
100701 ;
摘要：
From a training set of 7200 chemicals a back-propagation neural network (BNN) model was developed for estimating the n-octanol/water partition coefficient of organic molecules. Chemicals were described by means of a modified autocorrelation method. The advantages of the autocorrelation method were emphasized through the analysis of the simulation performances of the model and from a comparative study involving another BNN model [Quant. Struct. Act. Relat. 16 (1997) 224-230] using a large number of variables (atoms and bonds) derived from connection matrices. (C) Elsevier, Paris.
引用
收藏
页码：659 / 664
页数：6
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