Estimating environmentally important properties of chemicals from the chemical structure

The development of models to predict important environmental properties is easily recognised in the light of the great number of existing chemicals that still need to be characterised. To meet the needs for testing new chemicals such models may also be useful. Here new quantitative structure-activity relationship (QSAR) models are presented to predict acute and subacute aquatic toxicity to a green alga (Pseudokirschneriella subcapitata), a crustacea (Daphnia magna), two fish species (Lepomis macrochirus, Leuciscus idus) and a bacterial bioluminescence inhibition test (Microtox3). The toxicity is predicted from more than 1400 molecular descriptors using the multivariate statistical method partial least squares (PLS) regression. The models are based on descriptors calculated from the chemical structure only and can be applied to substances that have not yet been isolated or synthesised. QSAR models were obtained for which the standard prediction errors in logarithmic units correspond to the following concentration factors: Microtox 15 min bioluminescence inhibition EC50 - a factor 3.4; green alga 96 h growth rate inhibition EC50 - a factor 2.8; Daphnia magna 48 h immobilisation EC50 - a factor 2.3; Lepomis macrochirus 96 h toxicity LC50 - a factor 2.4; Leuciscus idus 96 h toxicity LC50 - a factor 3.5 In addition to development of prognosis models, the aim of this project was to develop methodology to obtain more reliable QSAR model predictions of toxicity

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