用针对性转录组数据使用通用阅读 (GenRA) 预测重复剂量毒性:一个概念验证案例研究
Tia Tate1, John Wambaugh1, Grace Patlewicz1
1Center for Computational Toxicology and Exposure, Office of Research and Development, U.S Environmental Protection Agency, Research Triangle Park, NC 27709, USA.
Computational toxicology (Amsterdam, Netherlands)
|June 13, 2023
概括
通用阅读 (GenRA) 通过结合转录基因数据,改善了毒性预测. 结合化学和基因表达数据,增强了预测,特别是肝脏毒性.
科学领域:
- 计算毒理学计算毒理学
- 化学安全评估的in silico方法
背景情况:
- 交叉阅读是利用类似化合物的数据预测化学毒性的关键方法.
- 通用阅读 (GenRA) 使用化学和生物活性指纹自动预测.
- 生物相似性对交叉读取性能的影响需要进一步研究.
研究的目的:
- 评估生物相似性对GenRA社区形成的影响.
- 用转录组数据评估GenRA在预测化学危险方面的表现.
- 为了比较化学指纹,转录指纹和混合方法的毒性预测的有效性.
主要方法:
- 利用HepaRGTM细胞中的1060种化学物质的向转录基因数据 (93个基因).
- 从度-反应数据使用二进制命中调用计算的转录学相似性.
- 通过使用接收器运行特征曲线 (AUC) 下的面积来评估GenRA性能,以获得美国EPA ToxRefDB v2.0危险结果.
主要成果:
- 在所有终点上观察到ROC AUC得分的适度改善 (转录组的2.1%,混合的7.3%).
- 肝脏特异性毒性终点的显著改善,ROC AUC得分增加了10% (转录组) 和17% (混合).
结论:
- 结合化学和向转录组数据的混合描述器提供了改善的体内毒性预测.
- 转录信息提高了自动横读的准确性,特别是在特定器官的毒性方面.
- 该研究强调了整合多模式数据的价值,以进行可靠的化学安全评估.
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