Division of Risk Assessment, National Institute of Health Sciences, Tokyo 158-8501, Japan.
Food Chem Toxicol. 2012 May;50(5):1538-46. doi: 10.1016/j.fct.2012.02.009. Epub 2012 Feb 17.
Most exposure levels of flavor in food are considered to be extremely low. If at all, genotoxic properties should be taken into account in safety evaluations. We have recently established a (quantitative) structure-activity relationship, (Q)SAR, combination system, which is composed of three individual models of mutagenicity prediction for industrial chemicals. A decision on mutagenicity is defined as the combination of predictive results from the three models. To validate the utility of our (Q)SAR system for flavor evaluation, we assessed 367 flavor chemicals that had been evaluated mainly by JECFA and for which Ames test results were available. When two or more models gave a positive evaluation, the sensitivity was low (19.4%). In contrast, when one or more models gave a positive evaluation, the sensitivity increased to 47.2%. The contribution of this increased sensitivity was mainly due to the result of the prediction by Derek for Windows, which is a knowledge-based model. Structural analysis of false negatives indicated some common sub-structures. The approach of improving sub-structural alerts could effectively contribute to increasing the predictability of the mutagenicity of flavors, because many flavors possess categorically similar functional sub-structures or are composed of a series of derivatives.
大多数食品中香料的暴露水平被认为是极低的。如果有的话,在安全性评估中应考虑遗传毒性特性。我们最近建立了一个(定量)构效关系,(QSAR),组合系统,由三个用于工业化学品致突变性预测的单独模型组成。致突变性的决定定义为三个模型的预测结果的组合。为了验证我们的(QSAR)系统用于香料评估的效用,我们评估了 367 种香料化学物质,这些化学物质主要由 JECFA 评估,并且可提供 Ames 测试结果。当两个或更多模型给出阳性评价时,灵敏度较低(19.4%)。相比之下,当一个或多个模型给出阳性评价时,灵敏度增加到 47.2%。这种灵敏度增加的贡献主要归因于 Derek for Windows 的预测结果,这是一个基于知识的模型。假阴性的结构分析表明存在一些常见的亚结构。改进亚结构警报的方法可以有效地提高香料致突变性的可预测性,因为许多香料具有类别相似的功能亚结构或由一系列衍生物组成。