Bacterial reverse mutation test is one of the most common methods used to address genotoxicity. The experimental test is designed to include a step to simulate mammalian metabolism. The most common metabolic activation system is the incubation with S9 fraction prepared from the livers of rodents. Usually, in silico models addressing this endpoint are developed on the basis of an overall call disregarding the fact that the toxic effect was observed before or after metabolic activation. Here, we present a new in silico model to predict mutagenicity as measured by activity in the bacterial reverse mutation test, bearing in mind the role of S9 activation to stimulate metabolism. We applied the software SARpy, which identifies structural alerts associated with the effect. Different rules codified by these structural alerts were found in case of positive or negative mutagenicity, observed in the presence or absence of the S9 fraction. These rules can be used to understand the role of metabolism in mutagenicity better. We also identified a possible association of the results from these models with carcinogenicity.

中文翻译：

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考虑到新陈代谢，采用计算机模拟诱变模型（Ames测试）。

细菌反向突变试验是用于解决基因毒性的最常用方法之一。实验测试旨在包括模拟哺乳动物新陈代谢的步骤。最常见的代谢活化系统是与从啮齿动物肝脏制备的S9组分一起孵育。通常，在不考虑在代谢活化之前或之后观察到毒性作用这一事实的基础上，开发了针对该终点的计算机模型。在这里，我们牢记S9激活刺激新陈代谢的作用，提出了一种新的计算机模拟模型，可预测通过细菌反向突变测试中的活性测得的致突变性。我们应用了SARpy软件，该软件可识别与效果相关的结构性警报。在存在或不存在S9馏分的情况下，在出现正向或负向诱变性的情况下，发现了由这些结构性警报整理的不同规则。这些规则可以用来更好地理解代谢在诱变中的作用。我们还确定了这些模型的结果与致癌性的可能关联。