QSAR models for biocides: The example of the prediction of Daphnia magna acute toxicity
| Autor: | Alla P. Toropova, Marco Marzo, Andrey A. Toropov, F Como, Claudia Ileana Cappelli, Maria Blazquez, Cosimo Toma, Giovanna J. Lavado, Emilio Benfenati, Anna Lombardo, Diego Baderna |
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| Rok vydání: | 2020 |
| Předmět: |
Biocide
Quantitative structure–activity relationship biology 010405 organic chemistry Aquatic ecosystem Daphnia magna Bioengineering General Medicine biology.organism_classification 01 natural sciences Acute toxicity 0104 chemical sciences Aquatic toxicology 010404 medicinal & biomolecular chemistry Environmental chemistry Drug Discovery Linear regression Molecular Medicine Environmental science Terrestrial ecosystem |
| DOI: | 10.6084/m9.figshare.11627265 |
| Popis: | Biocides are multi-component products used to control undesired and harmful organisms able to affect human or animal health or to damage natural and manufactured products. Because of their widespread use, aquatic and terrestrial ecosystems could be contaminated by biocides. The environmental impact of biocides is evaluated through eco-toxicological studies with model organisms of terrestrial and aquatic ecosystems. We focused on the development of in silico models for the evaluation of the acute toxicity (EC50) of a set of biocides collected from different sources on the freshwater crustacean Daphnia magna, one of the most widely used model organisms in aquatic toxicology. Toxicological data specific for biocides are limited, so we developed three models for daphnid toxicity using different strategies (linear regression, random forest, Monte Carlo (CORAL)) to overcome this limitation. All models gave satisfactory results in our datasets: the random forest model showed the best results with a determination coefficient r2 = 0.97 and 0.89, respectively, for the training (TS) and the validation sets (VS) while linear regression model and the CORAL model had similar but lower performance (r2 = 0.83 and 0.75, respectively, for TS and VS in the linear regression model and r2 = 0.74 and 0.75 for the CORAL model). |
| Databáze: | OpenAIRE |
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