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用于水生生物的化妆品生态毒理学建模:一种定量结构-活性关系方法。

Ecotoxicological modelling of cosmetics for aquatic organisms: A QSTR approach.

作者信息

Khan K, Roy K

机构信息

a Department of Pharmacoinformatics , National Institute of Pharmaceutical Educational and Research (NIPER) , Kolkata ; India.

b Drug Theoretics and Cheminformatics Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology , Jadavpur University , Kolkata , India.

出版信息

SAR QSAR Environ Res. 2017 Jul;28(7):567-594. doi: 10.1080/1062936X.2017.1352621. Epub 2017 Aug 7.

Abstract

In this study, externally validated quantitative structure-toxicity relationship (QSTR) models were developed for toxicity of cosmetic ingredients on three different ecotoxicologically relevant organisms, namely Pseudokirchneriella subcapitata, Daphnia magna and Pimephales promelas following the OECD guidelines. The final models were developed by partial least squares (PLS) regression technique, which is more robust than multiple linear regression. The obtained model for P. subcapitata shows that molecular size and complexity have significant impacts on the toxicity of cosmetics. In case of P. promelas and D. magna, we found that the largest contribution to the toxicity was shown by hydrophobicity and van der Waals surface area, respectively. All models were validated using both internal and test compounds employing multiple strategies. For each QSTR model, applicability domain studies were also performed using the "Distance to Model in X-space" method. A comparison was made with the ECOSAR predictions in order to prove the good predictive performances of our developed models. Finally, individual models were applied to predict toxicity for an external set of 596 personal care products having no experimental data for at least one of the endpoints, and the compounds were ranked based on a decreasing order of toxicity using a scaling approach.

摘要

在本研究中,按照经合组织指南,针对化妆品成分对三种不同的具有生态毒理学相关性的生物(即斜生栅藻、大型溞和黑头呆鱼)的毒性,开发了经过外部验证的定量结构-毒性关系(QSTR)模型。最终模型采用偏最小二乘法(PLS)回归技术构建,该技术比多元线性回归更稳健。所获得的针对斜生栅藻的模型表明,分子大小和复杂性对化妆品的毒性有显著影响。对于黑头呆鱼和大型溞,我们发现分别是疏水性和范德华表面积对毒性的贡献最大。所有模型均使用内部和测试化合物,采用多种策略进行验证。对于每个QSTR模型,还使用“X空间中到模型的距离”方法进行了适用域研究。与ECOSAR预测结果进行了比较,以证明我们所开发模型具有良好的预测性能。最后,将各个模型应用于预测一组596种个人护理产品的毒性,这些产品至少有一个端点没有实验数据,并使用一种标度方法根据毒性递减顺序对这些化合物进行排序。

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