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使用毒理网络分析揭示由毒化合物引起的毒性机制
Kexing Xi1, Mengqing Zhang2, Mingrui Li3
1State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Molecular therapy. Nucleic acids
|December 11, 2023
概括
药物诱导的损伤影响全球数十亿人. 这项研究使用网络分析来揭示共同的机制,确定关键途径,如AGE-RAGE和PI3K-Akt,对于理解和预防毒性至关重要.
科学领域:
- 药理学和毒理学 药理学和毒理学
- 系统生物学 系统生物学
- 生物信息学是一种生物信息学.
背景情况:
- 药物诱导的毒性是全球主要的健康问题,导致脏不可逆转的损伤.
- 了解化合物诱导损伤背后的复杂机制对于制定预防策略至关重要.
研究的目的:
- 使用基于网络的方法阐明各种化合物诱导的毒性分子机制.
- 确定药物诱导的损伤中涉及的常见途径和生物过程.
主要方法:
- 从公共资源收集了42种毒化合物和60种相关综合征的数据.
- 应用网络本地化和分离算法,将化合物目标和疾病基因映射到人类互动组.
- 在已识别的毒网络上进行了丰富分析,以确定关键的基因本体学和基因和基因组通路的京都百科全书.
主要成果:
- 确定了199个统计学上显著的毒网络,将化合物标与疾病基因联系起来.
- 发现毒性化合物通常会调解先进的甘化末端产品-先进的甘化末端产品受体 (AGE-RAGE) 信号通路,特别是在糖尿病并发症和病毒感染等情况下.
- 突出了酸丁 3-激酶-Akt (PI3K-Akt) 途径和亡在化合物诱导的毒性中的参与.
结论:
- 这项研究为药物诱导毒性的常见机制性途径提供了宝贵的见解.
- 基于网络的方法为研究化合物毒性提供了一个强大的框架,可以扩展到其他毒性研究领域.
- 这些发现可以帮助开发有针对性的干预措施,以预防药物诱导的损伤.
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