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

页码：659 / 664

页数：6

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