一个基于蛋白质相互作用的框架揭示了化学品的一般毒性
Xiao Gan1, Geng Li1, Weiyi Yang1
1Jiangsu Key Laboratory of Intelligent Medical Image Computing, School of Artificial Intelligence, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Environmental science & technology
|November 4, 2025
概括
这项研究引入了一个新的框架,通过分析蛋白质相互作用来预测化学毒性,揭示隐藏的化学疾病联系. 这种方法提高了我们对环境健康风险和毒性模式的理解.
科学领域:
- 毒理学 毒理学 毒理学
- 系统生物学 系统生物学
- 计算生物学 计算生物学
背景情况:
- 人类健康受到各种化学物质暴露的影响.
- 目前的毒性评估往往缺乏整体观点,只关注特定的化学物质或疾病.
- 识别更广泛的毒性模式对于公共卫生至关重要.
研究的目的:
- 提出一个理解化学毒性的一般框架.
- 通过蛋白质相互作用介导的化学物质和疾病之间的关系来概念化毒性.
- 用蛋白质互动组中的网络近距离来预测化学疾病关联.
主要方法:
- 使用了比较毒基因组学数据库 (CTD).
- 分析了化学点和与疾病相关的蛋白质之间的网络近距离.
- 用斑马鱼急性毒性实验和人类暴露组数据分析验证的预测.
主要成果:
- 网络的接近有效地预测了化学疾病的关联.
- 在预测杀菌剂毒性和解释药物细胞毒性方面展示了框架应用.
- 发现了"间接打击"化学疾病毒性模式.
结论:
- 拟议的框架为毒性研究提供了一个新的范式.
- 提供有关化学品健康风险的见解,并解决公共卫生挑战.
- 提高了化学产生的不良健康影响的预测.
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