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Abstract
Pharmaceutical and Personal Care Products (PPCPs) became a class of contaminants of emerging concern because are ubiquitously detected in surface water and soil, where they can affect wildlife. Ecotoxicological data are only available for a few PPCPs, thus modelling approaches are essential tools to maximize the information contained in the existing data. In silico methods may be helpful in filling data gaps for the toxicity of PPCPs towards various ecological indicator organisms. The good correlation between toxicity toward Daphnia magna and those on two fish species (Pimephales promelas and Oncorhynchus mykiss), improved by the addition of one theoretical molecular descriptor, allowed us to develop predictive models to investigate the relationship between toxicities in different species. The aim of this work is to propose quantitative activity–activity relationship (QAAR) models, developed in QSARINS and validated for their external predictivity. Such models can be used to predict the toxicity of PPCPs to a particular species using available experimental toxicity data from a different species, thus reducing the tests on organisms of higher trophic level. Similarly, good QAAR models, implemented by molecular descriptors to improve the quality, are proposed here for fish interspecies. We also comment on the relevance of autocorrelation descriptors in improving all studied interspecies correlations.
Acknowledgements
We thank the University of Insubria for giving a fellowship to Alessandro Sangion for his PhD research. This article was presented at the 17th International Conference on QSAR in Environmental and Health Sciences (QSAR 2016), 13–17 June 2016, Miami Beach, FL, USA.
Notes
$ Presented at the 17th International Conference on QSAR in Environmental and Health Sciences (QSAR 2016), 13–17 June 2016, Miami Beach, FL, USA.
