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Integrating computational methods to predict mutagenicity of aromatic azo compounds.
Journal of Environmental Science and Health, Part C ( IF 1.650 ) Pub Date : 2017-10-14 , DOI: 10.1080/10590501.2017.1391521
Domenico Gadaleta 1 , Nicola Porta 1 , Eleni Vrontaki 1, 2 , Serena Manganelli 1 , Alberto Manganaro 3 , Guido Sello 4 , Masamitsu Honma 5 , Emilio Benfenati 1
Affiliation  

Azo dyes have several industrial uses. However, these azo dyes and their degradation products showed mutagenicity, inducing damage in environmental and human systems. Computational methods are proposed as cheap and rapid alternatives to predict the toxicity of azo dyes. A benchmark dataset of Ames data for 354 azo dyes was employed to develop three classification strategies using knowledge-based methods and docking simulations. Results were compared and integrated with three models from the literature, developing a series of consensus strategies. The good results confirm the usefulness of in silico methods as a support for experimental methods to predict the mutagenicity of azo compounds.

中文翻译:

集成计算方法来预测芳族偶氮化合物的致突变性。

偶氮染料具有几种工业用途。然而,这些偶氮染料及其降解产物显示出致突变性,在环境和人类系统中引起破坏。提出了计算方法作为廉价且快速的替代方案,以预测偶氮染料的毒性。使用基于偶氮染料的354种基准Ames数据基准数据集,使用基于知识的方法和对接模拟来开发三种分类策略。对结果进行了比较,并与文献中的三个模型进行了整合,从而制定了一系列共识策略。良好的结果证实了计算机方法可用于支持预测偶氮化合物诱变性的实验方法。
更新日期:2019-11-01
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