Devillers J, Bro E, Millot F
a CTIS , Rillieux La Pape , France.
b Research Department , National Game and Wildlife Institute (ONCFS) , Le Perray en Yvelines , France.
SAR QSAR Environ Res. 2015;26(10):831-52. doi: 10.1080/1062936X.2015.1104809. Epub 2015 Nov 7.
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.
释放到环境中的大量人造化学物质会干扰正常的、受激素调节的生物过程，对生物物种的发育和生殖功能产生不利影响。已经设计了各种体内和体外试验来检测内分泌干扰物，但需要测试的化学物质数量如此之多，为了节省时间和金钱，（定量）构效关系（（Q）SAR）模型越来越多地被用作这些实验室检测的替代方法。然而，它们中的大多数只关注特定的靶点（例如雌激素或雄激素受体），而要提高效率，内分泌干扰建模应优先考虑活性谱，以便更好地衡量这种复杂现象。在此背景下，人们尝试使用内分泌干扰组模拟（EDS）工具评估220种结构各异的农药的内分泌干扰谱，该工具可同时预测化学物质与12种核受体结合的概率。第一步，基于网络的EDS系统成功应用于16种已知靶向至少一种所研究受体的药物化合物。由于对至少一种受体具有较高的预测亲和力，约13%的被研究农药被估计为内分泌系统的潜在干扰物。相比之下，约55%的农药不太可能是内分泌干扰物。对模拟结果进行了讨论，并对EDS工具的使用提出了一些看法。
