Journal ArticleDOI
Quantitative structure–activity relationship analysis of acute toxicity of diverse chemicals to Daphnia magna with whole molecule descriptors
Maikki Moosus,Uko Maran +1 more
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The ECOTOX database was queried and analysed for available data and a homogenous subset of 253 compounds for the endpoint LC50 48 h was established, and the applicability domain was subsequently analysed and discussed.Abstract:
Quantitative structure–activity relationship analysis and estimation of toxicological effects at lower-mid trophic levels provide first aid means to understand the toxicity of chemicals. Daphnia magna serves as a good starting point for such toxicity studies and is also recognized for regulatory use in estimating the risk of chemicals. The ECOTOX database was queried and analysed for available data and a homogenous subset of 253 compounds for the endpoint LC50 48 h was established. A four-parameter quantitative structure–activity relationship was derived (coefficient of determination, r 2 = 0.740) for half of the compounds and internally validated (leave-one-out cross-validated coefficient of determination, = 0.714; leave-many-out coefficient of determination, = 0.738). External validation was carried out with the remaining half of the compounds (coefficient of determination for external validation, = 0.634). Two of the descriptors in the model (log P, average bonding information content) capture the s...read more
Citations
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Prediction of acute toxicity of emerging contaminants on the water flea Daphnia magna by Ant Colony Optimization–Support Vector Machine QSTR models
TL;DR: A novel quantitative structure-toxicity relationship (QSTR) model was developed, using Ant Colony Optimization to select the most relevant set of molecular descriptors, and Support Vector Machine to correlate the selected descriptors with the toxicity data, and prediction results were found to be very accurate for those compounds that fall inside the defined applicability domain.
Journal ArticleDOI
Measurement of baseline toxicity and QSAR analysis of 50 non-polar and 58 polar narcotic chemicals for the alga Pseudokirchneriella subcapitata
TL;DR: A set of homogenous experimental algal toxicity data was measured for 50 non-polar narcotic chemicals using the alga Pseudokirchneriella subcapitata in a closed test with a growth rate endpoint providing further guidelines for the in silico prediction purposes in decision support while performing risk assessment.
Journal ArticleDOI
Comparison of in silico models for prediction of Daphnia magna acute toxicity
TL;DR: Eight in silico modelling packages were evaluated and compared for the prediction of Daphnia magna acute toxicity from the viewpoint of the European legislation on chemicals, REACH and showed that four models had similar reliability.
Journal ArticleDOI
Exploring the role of quantum chemical descriptors in modeling acute toxicity of diverse chemicals to Daphnia magna.
TL;DR: A comparison of the robust models based on the quantum-chemical descriptors computed with various quantum-mechanical methods suggests that the advanced semi-empirical methods such as PM7 can be more reliable than the ab-initio methods which are computationally more expensive.
Journal ArticleDOI
Acute aquatic toxicity of organic solvents modeled by QSARs
Amélie Levet,Claire Bordes,Yohann Clément,Pierre Mignon,Christophe Morell,Henry Chermette,Pedro Marote,Pierre Lanteri +7 more
TL;DR: The aim of this work was to develop reliable QSARs in order to model both invertebrate and algae EC50 for organic solvents, regardless of the mechanism of toxic action involved.
References
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