4.7 Article

Quantitative structure-activity relationship modeling of the toxicity of organothiophosphate pesticides to Daphnia magna and Cyprinus carpio

Journal

CHEMOSPHERE
Volume 75, Issue 11, Pages 1531-1538

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2009.01.081

Keywords

EINECS; REACH; QSAR; Organothiophosphate; Daphnia magna; Interspecies correlation

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Within the REACH regulatory framework in the EU, quantitative structure-activity relationships (QSAR) models are expected to help reduce the number of animals used for experimental testing. The objective of this study was to develop QSAR models to describe the acute toxicity of organothiophosphate pesticides to aquatic organisms. Literature data sets for acute toxicity data of organothiophosphates to fish and one data set from experiments with 15 organothiophosphates on Daphnia magna performed in the present study were used to establish QSARs based on quantum mechanically derived molecular descriptors. The logarithm of the octanol/water partition coefficient, log K-ow. the energy of the lowest unoccupied molecular orbital, E-lumo, and the energy of the highest occupied molecular orbital, E-homo were used as descriptors. Additionally, it was investigated if toxicity data for the invertebrate D. magna could be used to build a QSAR model to predict toxicity to fish. Suitable QSAR models (0.80 < r(2) < 0.82) were derived to predict acute toxicity of organothiophosphates to fish (Cyprinus carpio) and the invertebrate (D. magna). Toxicity data for D. magna correlated well (r(2) = 0.94) with toxicity data for C. carpio. This implies that by performing toxicity tests with D. magna, one can use our interspecies QSAR model to predict the acute toxicity of organothiophosphates to fish. The three QSAR models were validated either both internally and externally (D. magna) or internally only (carp and D. magna to carp). For each QSAR model, an applicability domain was defined based on the chemical structures and the ranges of the descriptor values of the training set compounds. From the 100196 European Inventory of Existing Commercial Chemical Substances (EINECS), 83 compounds were identified that fit the selection criteria for the QSAR models. For these compounds, using our QSAR models, one can obtain an indication of their toxicity without the need for additional experimental testing. (C) 2009 Published by Elsevier Ltd.

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