预测草药疾病的关联使用基于网络的措施在人类蛋白质互动组.
Seunghyun Wang1, Hyun Chang Lee2, Sunjae Lee3
1Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.
BMC complementary medicine and therapies
|June 6, 2024
概括
本研究引入了一种计算方法来预测草药疾病的关联,考虑多化合物多目标效应. 基于网络的方法,加权平均最接近的路径 (WACP),成功地确定了潜在的关系,用科学证据现代化了草药.
科学领域:
- 计算生物学是一种计算生物学.
- 药理学 药理学是指药理学的学科.
- 系统生物学 系统生物学
背景情况:
- 自然草药被广泛用于疾病治疗,但往往缺乏科学验证.
- 当前的研究往往侧重于单个化合物,忽视了草药的多化合物多目标 (MCMT) 性质.
- 需要基于证据的计算方法来预测草药疾病的关联.
研究的目的:
- 开发和验证基于网络的计算方法,用于预测草药疾病的关联.
- 将多组合和多目标效应纳入预测模型.
- 为自然草药的疗效提供科学证据.
主要方法:
- 设计了一种基于网络的新型测量方法,即加权平均最接近路径 (WACP).
- 该方法量化了与草药相关的和与疾病相关的基因之间的近距离,考虑到草药化合物组成.
- 使用人类蛋白质互动组验证了预测.
主要成果:
- 通过WACP方法,成功预测了草药疾病的相关性,AUROC为0.777.
- 简单的基于网络的近距离测量比WACP方法的性能更好.
- 案例研究,包括Brassica oleracea var. 在内. 分析,并提出了新的潜在草药疾病对.
结论:
- 拟议的计算方法为现代化草药提供了一个有希望的方法.
- 它为草药和疾病之间的分子关联提供了科学证据.
- 这种方法可以促进发现天然草药的新疗法应用.
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