Prediction of the endocrine disruption profile of pesticides

^$Presented at the 8th International Symposium on Computational Methods in Toxicology and Pharmacology Integrating Internet Resources, CMTPI-2015, 21–25 June 2015, Chios, Greece.

Abstract

Numerous manmade chemicals released into the environment can interfere with normal, hormonally regulated biological processes to adversely affect the development and reproductive functions of living species. Various in vivo and in vitro tests have been designed for detecting endocrine disruptors, but the number of chemicals to test is so high that to save time and money, (quantitative) structure–activity relationship ((Q)SAR) models are increasingly used as a surrogate for these laboratory assays. However, most of them focus only on a specific target (e.g. estrogenic or androgenic receptor) while, to be more efficient, endocrine disruption modelling should preferentially consider profiles of activities to better gauge this complex phenomenon. In this context, an attempt was made to evaluate the endocrine disruption profile of 220 structurally diverse pesticides using the Endocrine Disruptome simulation (EDS) tool, which simultaneously predicts the probability of binding of chemicals on 12 nuclear receptors. In a first step, the EDS web-based system was successfully applied to 16 pharmaceutical compounds known to target at least one of the studied receptors. About 13% of the studied pesticides were estimated to be potential disruptors of the endocrine system due to their high predicted affinity for at least one receptor. In contrast, about 55% of them were unlikely to be endocrine disruptors. The simulation results are discussed and some comments on the use of the EDS tool are made.

Keywords:

• pesticides
• endocrine disruption profile
• nuclear receptors
• in silico
• molecular docking
• Endocrine Disruptome

Acknowledgements

J.D. thanks Dr Samo Turk for the valuable exchanges and the rapid actions on the Endocrine Disruptome software. This research was supported by the pesticide research programme (M6P) funded by the French Ministry of Ecology, Sustainable Development and Energy and the National Water and Aquatic Environment Institute (ONEMA).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

^$ Presented at the 8th International Symposium on Computational Methods in Toxicology and Pharmacology Integrating Internet Resources, CMTPI-2015, 21–25 June 2015, Chios, Greece.