背景:中医,具有多组分协同作用的特点,多途径多靶点,在癌症的治疗中起着重要的作用,心脑血管疾病,等。然而,中药化学成分复杂,大部分药理机制尚不清楚,特别是在代谢过程中,化学成分之间的关系会发生变化。
目的:我们的目的是提供一种基于复杂网络理论的方法,用于分析中药代谢过程中物质的因果关系和动态相关性。
方法:我们提出了一个名为CDCS-TCM的框架,用于分析中药代谢过程中物质之间的因果关系和动态相关性。我们的方法主要包括两部分。第一部分是通过因果关系网络发现局部和全局因果关系。第二部分是研究动态相关性,并通过动态物质相关网络识别基本物质。
结果:我们开发了一种CDCS-TCM方法来分析物质的因果关系和动态相关性。以香丹注射液治疗缺血性脑卒中为例,我们已经确定了代谢过程中的重要物质,包括具有强因果关系的物质对和核心效应物质簇的动态变化。
结论:提出的框架将有助于更有效地探索中药活性成分的相关性,并将为阐明药物作用机制和新药发现提供新的视角。
BACKGROUND: Traditional Chinese medicine, with the feature of synergistic effects of multi-component, multi-pathway and multi-target, plays an important role in the treatment of cancer, cardiovascular and cerebrovascular diseases, etc. However, chemical components in traditional Chinese medicine are complex and most of the pharmacological mechanisms remain unclear, especially the relationships of chemical components change during the metabolic process.
OBJECTIVE: Our aim is to provide a method based on complex network theory to analyze the causality and dynamic correlation of substances in the metabolic process of traditional Chinese medicine.
METHODS: We proposed a framework named CDCS-TCM to analyze the causality and dynamic correlation between substances in the metabolic process of traditional Chinese medicine. Our method mainly consists two parts. The first part is to discover the local and global causality by the causality network. The second part is to investigate the dynamic correlations and identify the essential substance by dynamic substance correlation network.
RESULTS: We developed a CDCS-TCM method to analyze the causality and dynamic correlation of substances. Using the XiangDan Injection for ischemic stroke as an example, we have identified the important substances in the metabolic process including substance pairs with strong causality and the dynamic changes of the core effector substance clusters.
CONCLUSIONS: The proposed framework will be useful for exploring the correlations of active ingredients in traditional Chinese medicine more effectively and will provide a new perspective for the elucidation of drug action mechanisms and the new drug discovery.