细胞绘制和化学结构读数交叉可在化学品早期风险预测中对大鼠急性经口毒性进行互补。

IF 3.7 3区 医学 Q2 CHEMISTRY, MEDICINAL Chemical Research in Toxicology Pub Date : 2024-11-18 Epub Date: 2024-11-08 DOI:10.1021/acs.chemrestox.4c00169
Fabrice Camilleri, Joanna M Wenda, Claire Pecoraro-Mercier, Jean-Paul Comet, David Rouquié
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引用次数: 0

摘要

在开发新化合物的过程中,及早做出降低风险的决定,可以确定安全性能更高的新型候选化学品。传统上,在早期评估作物保护产品的急性口服毒性时会进行体内研究,以避免使用体内致死剂量为 50%(LD50)≤ 60 毫克/千克体重的 "剧毒 "化合物。这些研究耗时长、成本高,而且会引起伦理方面的担忧,因此催生了非动物替代品的使用。我们分析的目的是通过比较使用化学结构信息、U2OS 细胞上的细胞凋亡分析法得出的体外生物数据或两者的结合使用,来评估 "读取-交叉 "方法对大鼠急性口服毒性的预测效果。我们的研究结果表明,使用化学结构信息、形态特征或两者结合的交叉阅读法,可以将化合物分类为极急性口服毒性(LD50 ≤ 60 mg/kg)或非极急性口服毒性。在对结构与训练集中的化合物相似的化合物进行分类时,化学结构更具有预测性(平衡准确率为 0.82)。相反,当要分类的化合物在结构上与训练集中的化合物不同时,形态特征则更具预测性(平衡准确率为 0.72)。将这两个模型结合起来,可以对结构与训练集中的化合物相似的化合物进行分类,从而略微提高预测结果(平衡准确率为 0.85)。
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Cell Painting and Chemical Structure Read-Across Can Complement Each Other for Rat Acute Oral Toxicity Prediction in Chemical Early Derisking.

Early derisking decisions in the development of new chemical compounds enable the identification of novel chemical candidates with improved safety profiles. In vivo studies are traditionally conducted in the early assessment of acute oral toxicity of crop protection products to avoid compounds, which are considered "very acutely toxic", with an in vivo lethal dose of 50% (LD50) ≤ 60 mg/kg body weight. Those studies are lengthy and costly and raise ethical concerns, catalyzing the use of nonanimal alternatives. The objective of our analysis was to assess the predictive efficacy of read-across approaches for acute oral toxicity in rats, comparing the use of chemical structure information, in vitro biological data derived from the Cell Painting profiling assay on U2OS cells, or the combination of both. Our findings indicate that the classification of compounds as very acute oral toxic (LD50 ≤ 60 mg/kg) or not is possible using a read-across approach, with chemical structure information, morphological profiles, or a combination of both. When classifying compounds structurally similar to those in the training set, the chemical structure was more predictive (balanced accuracy of 0.82). Conversely, when the compounds to be classified were structurally different from those in the training set, the morphological profiles were more predictive (balanced accuracy of 0.72). Combining the two models allowed for the classification of compounds structurally similar to those in the training set to slightly improve the predictions (balanced accuracy of 0.85).

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来源期刊
CiteScore
7.90
自引率
7.30%
发文量
215
审稿时长
3.5 months
期刊介绍: Chemical Research in Toxicology publishes Articles, Rapid Reports, Chemical Profiles, Reviews, Perspectives, Letters to the Editor, and ToxWatch on a wide range of topics in Toxicology that inform a chemical and molecular understanding and capacity to predict biological outcomes on the basis of structures and processes. The overarching goal of activities reported in the Journal are to provide knowledge and innovative approaches needed to promote intelligent solutions for human safety and ecosystem preservation. The journal emphasizes insight concerning mechanisms of toxicity over phenomenological observations. It upholds rigorous chemical, physical and mathematical standards for characterization and application of modern techniques.
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