Devillers J, Marchand-Geneste N, Doré J C, Porcher J M, Poroikov V
CTIS, 3 Chemin de la Gravière, 69140 Rillieux La Pape, France.
SAR QSAR Environ Res. 2007 May-Jun;18(3-4):181-93. doi: 10.1080/10629360701303669.
A number of chemicals released into the environment have the potential to disturb the normal functioning of the endocrine system. These chemicals termed endocrine disruptors (EDs) act by mimicking or antagonizing the normal functions of natural hormones and may pose serious threats to the reproductive capability and development of living species. Batteries of laboratory bioassays exist for detecting these chemicals. However, due to time and cost limitations, they cannot be used for all the chemicals which can be found in the ecosystems. SAR and QSAR models are particularly suited to overcome this problem but they only deal with specific targets/endpoints. The interest to account for profiles of endocrine activities instead of unique endpoints to better gauge the complexity of endocrine disruption is discussed through a SAR study performed on 11,416 chemicals retrieved from the US-NCI database and for which 13 different PASS (Prediction of Activity Spectra for Substances) endocrine activities were available. Various multivariate analyses and graphical displays were used for deriving structure-activity relationships based on specific structural features.
释放到环境中的多种化学物质有可能干扰内分泌系统的正常功能。这些被称为内分泌干扰物（EDs）的化学物质通过模拟或拮抗天然激素的正常功能发挥作用，可能对生物物种的生殖能力和发育构成严重威胁。现有一系列实验室生物测定方法来检测这些化学物质。然而，由于时间和成本的限制，它们不能用于检测生态系统中发现的所有化学物质。SAR和QSAR模型特别适合解决这个问题，但它们只处理特定的靶点/终点。通过对从美国国家癌症研究所（US-NCI）数据库中检索到的11416种化学物质进行的SAR研究，讨论了考虑内分泌活性概况而非单一终点以更好地衡量内分泌干扰复杂性的意义，这些化学物质有13种不同的PASS（物质活性谱预测）内分泌活性数据。基于特定的结构特征，使用了各种多元分析和图形显示来推导构效关系。
