A general QSAR model for predicting the acute toxicity of pesticides to Oncorhynchus mykiss

被引：27

作者：

Devillers, J

Flatin, J

机构：

[1] CTIS, F-69140 Rillieux La Pape, France

[2] Fac Catholique Lyon, Lab Biol Gen & Histol, F-69288 Lyon 02, France

来源：

SAR AND QSAR IN ENVIRONMENTAL RESEARCH | 2000年 / 11卷 / 01期

关键词：

QSAR; Oncorhynchus mykiss; acute toxicity; pesticides; neural network; autocorrelation method;

D O I：

10.1080/10629360008033227

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

A Quantitative Structure-Activity Relationship (QSAR) model was derived for estimating the acute toxicity of pesticides against Oncorhynchus mykiss under varying experimental conditions. Chemicals were described by means of autocorrelation descriptors encoding lipophilicity (H-0 to H-5) and the H-bonding acceptor ability (HBA(0)) and H-bonding donor ability (HBD0) of the pesticides. A three-layer feedforward neural network trained by the back-propagation algorithm was used as statistical engine for deriving a powerful QSAR model accounting for the weight of the fish, time of exposure, temperature, pH, and hardness.

引用

页码：25 / 43

页数：19

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