通过偏向的随机步行算法对抗甲状腺功能障碍症的多级互动原子引导发现候选草药和活性成分
Seok-Hoon Han1, Ji-Hwan Kim2, Yewon Han3
1College of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.
International journal of molecular sciences
|October 16, 2025
概括
这项研究通过分析草药-化合物-点网络来确定甲状腺功能障碍的潜在草药治疗方法. 它强调了Geranii Herba和Gastrodiae Rhizoma作为开发新疗法的有希望的候选人.
科学领域:
- 计算生物学是一种计算生物学.
- 系统药理学 系统药理学
- 传统中国医药 传统中国医药
背景情况:
- 甲状腺功能障碍症涉及过多的甲状腺激素和高代谢状态.
- 目前的治疗方法存在,但需要基于机制的选择.
- 草药提供了新的治疗发现的潜力.
研究的目的:
- 为了确定潜在的草药候选者,活性化合物和甲状腺功能障碍治疗的机制.
- 开发和应用一个计算框架来优先考虑自然产品.
- 为了发现甲状腺功能障碍的新治疗方法.
主要方法:
- 构建了一个多尺度的互动原子网络.
- 应用了一个有偏见的随机散步扩散模型来优先考虑草药候选者.
- 来自OASIS,药物银行,TTD,STITCH和DisGeNET的综合数据.
- 通过相关性和目标重叠来评估草药疾病关系.
主要成果:
- 优先考虑的草药候选者包括Geranii Herba,Gastrodiae Rhizoma和Veratri Rhizoma Et Radix. 这三种植物.
- 确定了关键的信号通路:MAPK,PI3K-AKT,p53,HIF-1和甲状腺激素信号.
- 提出了像白醇和红胺这样的新型化合物,并证实了像酸这样的已知药物.
结论:
- 计算框架成功地识别了已知和新的甲状腺功能障碍的草药治疗方法.
- 这种方法支持发现基于天然产品的多目标疗法.
- 强调了整合系统生物学和网络药理学在药物发现方面的潜力.
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