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首页> 外文期刊>Environmental toxicology and chemistry >THE OCTANOL-WATER PARTITION COEFFICIENT: STRENGTHS AND LIMITATIONS
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THE OCTANOL-WATER PARTITION COEFFICIENT: STRENGTHS AND LIMITATIONS

机译：辛醇-水分配系数：强度和局限性

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摘要

No physicochemical parameter in environmental toxicology and chemistry is better known than K_(OW), the octanol-water partition coefficient. This parameter, also called log P or log P_(oct), originates from research into quantitative structure-activity relationships (QSARs) [1]. The first studies were from Corwin Hansch and were focused on optimizing the biological as well as the pharmacological activity of chemicals. The coefficient K_(OW) is a measure of hydrophobicity, and several processes, including sorption and accumulation, are driven by hydrophobicity. It is the key parameter for environmental fate and exposure modeling programs [2]. An ecological risk assessment for organic compounds without consideration of its K_(OW) value seems impossible. Also, as an input parameter in QSARs, K_(OW) is dominant. Guidance documents for risk assessment of existing chemicals list numerous models for the prediction of bioconcentration factors, soil sorption, and sorption to dissolved organic carbon that are all based on K_(OW) [3]. Classic examples are QSARs for prediction of soil sorption [4], bioaccumulation [5,6], and baseline toxicity [7]. A clear example of the strength of K_(OW) as a parameter is in the development of models for the prediction of quality criteria for chemicals that act via narcosis. Here, predictions of effect concentrations, bioconcentration factors, and sediment sorption from K_(OW) are combined into one overall model [8,9]. Several papers in the "Top 100" show examples of methods for estimating parameters from octanol-water partition coefficients, including the estimation of aqueous solubility [10] and bioconcentration factors [11].
机译：在环境毒理学和化学中，没有任何理化参数比辛醇-水分配系数K_（OW）更好。此参数也称为log P或log P_（oct），源自对定量结构-活性关系（QSAR）的研究[1]。最初的研究来自Corwin Hansch，致力于优化化学物质的生物学和药理活性。系数K_（OW）是疏水性的量度，并且疏水性驱动着几个过程，包括吸附和积累。它是环境命运和暴露建模程序的关键参数[2]。不考虑其K_（OW）值就不可能对有机化合物进行生态风险评估。另外，作为QSAR中的输入参数，K_（OW）是主要的。现有化学品风险评估的指导文件列出了许多基于K_（OW）[3]的模型来预测生物富集因子，土壤吸附和对溶解有机碳的吸附[3]。经典的例子是用于预测土壤吸附[4]，生物蓄积[5,6]和基线毒性[7]的QSAR。 K_（OW）作为参数强度的一个明显例子是在预测通过麻醉作用起作用的化学品的质量标准的模型的开发中。在这里，对效应浓度，生物富集因子和来自K_（OW）的沉积物吸附的预测被合并为一个整体模型[8,9]。 “前100名”中的几篇论文显示了根据辛醇-水分配系数估算参数的方法示例，包括估算水溶性[10]和生物浓缩系数[11]。

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  • 来源
    《Environmental toxicology and chemistry》 |2013年第4期|732-733|共2页
  • 作者

    Joop L.M. Hermens; Jack H.M. de Bruijn; David N. Brooke;

  • 作者单位

    Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands;

    European Chemicals Agency, Helsinki, Finland;

    European Chemicals Agency, Helsinki, Finland;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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