Clustering a Chemical Inventory for Safety Assessment of Fragrance Ingredients: Identifying Read-Across Analogs to Address Data Gaps.,Chemical Research in Toxicology

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Clustering a Chemical Inventory for Safety Assessment of Fragrance Ingredients: Identifying Read-Across Analogs to Address Data Gaps.
Chemical Research in Toxicology ( IF 3.7 ) Pub Date : 2020-04-27 , DOI: 10.1021/acs.chemrestox.9b00518
Mihir S Date ₁ , Devin O'Brien , Danielle J Botelho , Terry W Schultz ₂ , Daniel C Liebler ₃ , Trevor M Penning ₄ , Daniel T Salvito ₁

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A valuable approach to chemical safety assessment is the use of read-across chemicals to provide safety data to support the assessment of structurally similar chemicals. An inventory of over 6000 discrete organic chemicals used as fragrance materials in consumer products has been clustered into chemical class-based groups for efficient search of read-across sources. We developed a robust, tiered system for chemical classification based on (1) organic functional group, (2) structural similarity and reactivity features of the hydrocarbon skeletons, (3) predicted or experimentally verified Phase I and Phase II metabolism, and (4) expert pruning to consider these variables in the context of specific toxicity end points. The systematic combination of these data yielded clusters, which may be visualized as a top-down hierarchical clustering tree. In this tree, chemical classes are formed at the highest level according to organic functional groups. Each subsequent subcluster stemming from classes in this hierarchy of the cluster is a chemical cluster defined by common organic functional groups and close similarity in the hydrocarbon skeleton. By examining the available experimental data for a toxicological endpoint within each cluster, users can better identify potential read-across chemicals to support safety assessments.

中文翻译：

对化学品清单进行聚类以评估香精成分的安全性：识别可读取的类似物以解决数据空白。

化学品安全评估的一种有价值的方法是使用交叉读取的化学品来提供安全数据，以支持对结构相似的化学品进行评估。消费品中用作香精原料的6000多种离散有机化学物质的清单已被归类为基于化学类别的组，以有效地搜索交叉阅读源。我们基于（1）有机官能团，（2）烃骨架的结构相似性和反应性特征，（3）预测或实验验证的I和II期新陈代谢以及（4）开发了一种强大的化学分类系统专家修剪在特定毒性终点的背景下考虑这些变量。这些数据的系统组合产生了聚类，可以将其可视化为自上而下的层次聚类树。在这棵树中，根据有机官能团在最高级别上形成了化学类别。源自该簇的该层次结构中的类的每个随后的子簇是由共同的有机官能团和烃骨架中的紧密相似性所定义的化学簇。通过检查每个簇中毒理学终点的可用实验数据，用户可以更好地识别潜在的交叉化学物质，以支持安全性评估。

更新日期：2020-04-27

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