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开发用于预测酚类对梨形四膜虫毒性的定量构效关系(QSARs)方法的比较评估

Comparative assessment of methods to develop QSARs for the prediction of the toxicity of phenols to Tetrahymena pyriformis.

作者信息

Cronin Mark T D, Aptula Aynur O, Duffy Judith C, Netzeva Tatiana I, Rowe Philip H, Valkova Iva V, Schultz T Wayne

机构信息

School of Pharmacy and Chemistry, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.

出版信息

Chemosphere. 2002 Dec;49(10):1201-21. doi: 10.1016/s0045-6535(02)00508-8.

Abstract

Quantitative structure-activity relationships (QSARs) for the toxicity of 200 phenols to the ciliated protozoan Tetrahymena pyriformis, and the validation of the QSARs using a test set of a further 50 compounds, are reported. The phenols are structurally heterogeneous and represent a variety of mechanisms of toxic action including polar narcosis, weak acid respiratory uncoupling, electrophilicity, and those compounds capable of being metabolised or oxidised to quinones. For each compound, a total of 108 physico-chemical descriptors have been calculated. A variety of methods were utilised to develop QSARs and are compared. The response-surface, or two parameter, approach was found to be successful, but only following the removal of compounds known to form quinones. Stepwise regression produced a seven parameter QSAR with good statistical fit, but was less interpretable and transparent than the response-surface. Partial least squares produced a good model for phenolic toxicity following supervised selection of parameters, this, however, was the least transparent of all approaches attempted. In all approaches, a large number of outliers were observed, typically these were compounds capable of being metabolised to quinones. The strengths and weaknesses of each of the approaches to predict the toxicity of the validation (test) set of phenols to T. pyriformis are discussed.

摘要

本文报道了200种酚类化合物对梨形四膜虫这种纤毛原生动物的毒性的定量构效关系(QSARs),以及使用另外50种化合物的测试集对这些QSARs进行的验证。这些酚类化合物在结构上具有异质性,代表了多种毒性作用机制,包括极性麻醉、弱酸呼吸解偶联、亲电性,以及那些能够被代谢或氧化为醌类的化合物。对于每种化合物,总共计算了108个物理化学描述符。利用了多种方法来开发QSARs并进行比较。发现响应面法或双参数法是成功的,但前提是去除已知会形成醌类的化合物。逐步回归产生了一个具有良好统计拟合的七参数QSAR,但与响应面法相比,其解释性和透明度较低。偏最小二乘法在对参数进行有监督选择后产生了一个用于酚类毒性的良好模型,然而,这是所有尝试方法中最不透明的。在所有方法中,都观察到大量异常值,通常这些是能够被代谢为醌类的化合物。讨论了每种方法在预测酚类验证(测试)集对梨形四膜虫的毒性方面的优缺点。

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