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定量构效关系:局部淋巴结试验中的磺酸酯

Quantitative structure-activity relationships: sulfonate esters in the local lymph node assay.

作者信息

Roberts D W, Basketter D A

机构信息

Unilever Research, Port Sunlight, Bebington, Wirral, UK.

出版信息

Contact Dermatitis. 2000 Mar;42(3):154-61. doi: 10.1034/j.1600-0536.2000.042003154.x.

DOI:10.1034/j.1600-0536.2000.042003154.x
PMID:10727166
Abstract

The biological activity of skin-sensitizing chemicals is related to their ability to react, either directly or after metabolic activation, with appropriate skin proteins. For direct acting electrophilic compounds, this ability can be modelled, using the RAI (relative alkylation index) approach, by a combination of electrophilicity and hydrophobicity parameters. The development of predictive quantitative structure-activity relationships (QSAR) models of skin sensitization, using mechanism-based physicochemical parameters, has been greatly facilitated by the introduction of the murine local lymph node assay (LLNA), which is able to describe the extent of the biological response in objective and quantitative terms. In the present work, sensitization response data in the LLNA is generated for a series of 6 sulfonate esters. An RAI-based hybrid QSAR/dose-response relationship is derived using a negative hydrophobicity coefficient in the RAI expression, to model the effect of retention of the hydrophobic test chemicals in the stratum corneum. Dose-response analyses are used to estimate EC3 and EC20 values as quantitative indices of skin sensitization potential for each compound, and regression analysis is applied to develop QSARs correlating these EC3 and EC20 values with an RAI-based parameter. The high statistical quality of these QSARs demonstrates both the consistency of the LLNA method for generating high quality skin sensitization data, and the value of the RAI approach in development of mathematical models for skin sensitization.

摘要

皮肤致敏化学物质的生物活性与其直接或经代谢活化后与合适的皮肤蛋白发生反应的能力有关。对于直接作用的亲电化合物,这种能力可以通过RAI(相对烷基化指数)方法,结合亲电性和疏水性参数来模拟。小鼠局部淋巴结试验(LLNA)的引入极大地促进了使用基于机制的物理化学参数建立皮肤致敏预测定量构效关系(QSAR)模型的发展,该试验能够客观、定量地描述生物反应的程度。在本研究中,针对一系列6种磺酸酯生成了LLNA中的致敏反应数据。在RAI表达式中使用负疏水系数,推导出基于RAI的混合QSAR/剂量反应关系,以模拟疏水性测试化学物质在角质层中的保留效应。剂量反应分析用于估计每种化合物的EC3和EC20值,作为皮肤致敏潜力的定量指标,并应用回归分析建立将这些EC3和EC20值与基于RAI的参数相关联的QSAR。这些QSAR的高统计质量既证明了LLNA方法生成高质量皮肤致敏数据的一致性,也证明了RAI方法在建立皮肤致敏数学模型中的价值。

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