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Modeling and prediction of octanol/water partition coefficient of pesticides using QSPR methods

Amel Bouakkadia (Department of Chemistry, Badji Mokhtar Annaba University, Annaba, Algeria)
Leila Lourici (Department of Chemistry, Chadli Bendjedid University, El Tarf, Algeria)
Djelloul Messadi (Department of Chemistry, Badji Mokhtar Annaba University, Annaba, Algeria)

Management of Environmental Quality

ISSN: 1477-7835

Article publication date: 12 June 2017

Abstract

Purpose

The purpose of this paper is to predict the octanol/water partition coefficient (Kow) of 43 organophosphorous compounds.

Design/methodology/approach

A quantitative structure-property relationship analysis was performed on a series of 43 pesticides using multiple linear regression and support vector machines methods, which correlate the octanol-water partition coefficient (Kow) values of these chemicals to their structural descriptors. At first, the data set was randomly separated into a training set (34 chemicals) and a test set (nine chemicals) for statistical external validation.

Findings

Models with three descriptors were developed using theoretical descriptors as independent variables derived from Dragon software while applying genetic algorithm-variable subset selection procedure.

Originality/value

The robustness and the predictive performance of the proposed linear model were verified using both internal and external statistical validation. One influential point which reinforces the model and an outlier were highlighted.

Keywords

Citation

Bouakkadia, A., Lourici, L. and Messadi, D. (2017), "Modeling and prediction of octanol/water partition coefficient of pesticides using QSPR methods", Management of Environmental Quality, Vol. 28 No. 4, pp. 579-592. https://doi.org/10.1108/MEQ-08-2015-0162

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited