1. QSAR modeling of Daphnia magna and fish toxicities of biocides using 2D descriptors
- Author
-
Giovanna J. Lavado, Marco Marzo, Kunal Roy, Cecile Valsecchi, Diego Baderna, Kabiruddin Khan, Anna Lombardo, Julia Pasqualini, Emilio Benfenati, Pathan Mohsin Khan, Khan, K, Khan, P, Lavado, G, Valsecchi, C, Pasqualini, J, Baderna, D, Marzo, M, Lombardo, A, Roy, K, and Benfenati, E
- Subjects
Quantitative structure–activity relationship ,Biocide ,Environmental Engineering ,Health, Toxicology and Mutagenesis ,Daphnia magna ,0208 environmental biotechnology ,Quantitative Structure-Activity Relationship ,02 engineering and technology ,010501 environmental sciences ,Ecotoxicology ,01 natural sciences ,Daphnia ,Statistical quality ,Validation ,Animals ,Environmental Chemistry ,0105 earth and related environmental sciences ,biology ,QSAR ,Fishes ,Public Health, Environmental and Occupational Health ,Reproducibility of Results ,Hazard potential ,General Medicine ,General Chemistry ,biology.organism_classification ,Pollution ,020801 environmental engineering ,Fish ,Toxicity ,Environmental science ,Biochemical engineering ,Disinfectants ,Applicability domain - Abstract
In the recent years, ecotoxicological hazard potential of biocidal products has been receiving increasing attention in the industries and regulatory agencies. Biocides/pesticides are currently one of the most studied groups of compounds, and their registration cannot be done without the empirical toxicity information. In view of limited experimental data available for these compounds, we have developed Quantitative Structure-Activity Relationship (QSAR) models for the toxicity of biocides to fish and Daphnia magna following principles of QSAR modeling recommended by the OECD (Organization for Economic Cooperation and Development). The models were developed using simple and interpretable 2D descriptors and validated using stringent tests. Both models showed encouraging statistical quality in terms of determination coefficient R2 (0.800 and 0.648), cross-validated leave-one-out Q2 (0.760 and 0.602) and predictive R2pred or Q2ext (0.875 and 0.817) for fish (nTraining = 66, nTest = 22) and Daphnia magna (nTraining = 100, nTest = 33) toxicity datasets, respectively. These models should be applicable for data gap filling in case of new or untested biocidal compounds falling within the applicability domain of the models. In general, the models indicate that the toxicity increases with lipophilicity and decreases with polarity, branching and unsaturation. We have also developed interspecies toxicity models for biocides using the daphnia and fish toxicity data and used the models for data gap filling.
- Published
- 2019