title: Prediction of the endocrine disruption profile of pesticides.
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.
authors.affiliation: a CTIS , Rillieux La Pape , France.
authors.forename: J
authors.initials: J
authors.lastname: Devillers
authors.affiliation: b Research Department , National Game and Wildlife Institute (ONCFS) , Le Perray en Yvelines , France.
authors.forename: E
authors.initials: E
authors.lastname: Bro
authors.affiliation: b Research Department , National Game and Wildlife Institute (ONCFS) , Le Perray en Yvelines , France.
authors.forename: F
authors.initials: F
authors.lastname: Millot
mesh_terms: D003198:Computer Simulation; D064420:Drug-Related Side Effects and Adverse Reactions; D052244:Endocrine Disruptors / Q000737:chemistry* / Q000633:toxicity; D062105:Molecular Docking Simulation; D010575:Pesticides / Q000737:chemistry / Q000633:toxicity*; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D018160:Receptors, Cytoplasmic and Nuclear / Q000737:chemistry*
chemical_list: D052244:Endocrine Disruptors; D010575:Pesticides; D004364:Pharmaceutical Preparations; D018160:Receptors, Cytoplasmic and Nuclear
keywords: Endocrine Disruptome; endocrine disruption profile; in silico; molecular docking; nuclear receptors; pesticides