聚和化基物质和其他化学类别的物理化学性质模型
Todd M Martin1, Landon R Batts2, Nathaniel Charest1
1United States Environmental Protection Agency, Center for Computational Toxicology and Exposure, 109 TW Alexander Dr., Research Triangle Park, North Carolina 27711, United States.
Journal of chemical information and modeling
|September 8, 2025
概括
新的定量结构-属性关系 (QSPR) 模型准确预测了和多基物质 (PFAS) 的物理化学特性,改善了环境命运评估. 全球模型的表现优于本地模型,提高了对这些持久化学物质的预测准确度.
科学领域:
- 环境化学环境化学
- 计算化学计算化学
- 毒理学 毒理学 毒理学
背景情况:
- 由于其物理化学性质的数据缺口,和多基基物质 (PFAS) 构成环境风险.
- 预测模型对于评估PFAS环境命运,运输和暴露至关重要.
研究的目的:
- 为PFAS的关键物理化学性质开发和验证定量结构-性质关系 (QSPR) 模型.
- 将全球QSPR模型的性能与本地模型和现有工具进行比较.
主要方法:
- 从公共数据源中提取了超过20万个实验性财产记录.
- 开发了使用各种化学品类的全球QSPR模型和使用仅PFAS数据的本地模型.
- 使用R平方和测试数据的平均绝对误差 (MAE) 评估模型性能.
- 实现了基于最近邻域的适用性域 (AD) 测量.
主要成果:
- 全球模型显示,与本地模型相比,PFAS属性的预测准确度更高 (11%的MAE减少).
- 全球模型在所有物业终点上取得了强的表现 (R平方0.76-0.89).
- 与现有的毒性估计软件工具 (T.E.S.T.) 模型相比,新的模型显示了13%的MAE减少.
- 适用性领域有效排除了糟糕的预测,在AD中保留了约95%的化学物质.
结论:
- 全球QSPR模型为PFAS物理化学性质提供了准确的预测,这对于环境风险评估至关重要.
- 开发的模型和应用领域提高了PFAS环境暴露预测的可靠性.
- 这些发现支持对PFAS污染的更好的监管和管理策略.
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