Research On The Correlation Of Traditional Chinese Medicine Ingredients Based On Complex Network

Traditional Chinese medicine(TCM),which is characterized by "multi-ingredient,multipathway and multi-target" synergistic effects,plays an important role in the treatment of cancer,cardiovascular and cerebrovascular diseases,etc.However,the complex ingredients of TCM and the unclear pharmacological mechanism,especially the dynamic changes of the correlation of ingredients in the metabolic process,make it difficult for traditional pharmacological methods to comprehensively analyze the effector substances of TCM in the treatment of complex diseases and explain the mechanism of action from a systematic perspective.Therefore,based on the example of Dan Shen and Jiang Xiang in the treatment of ischemic stroke(IS),three network models based on multilayer network,causality network and dynamic correlation network have been constructed to explore the correlation between TCM ingredients and substances in the body so as to identify key substances and explain their mechanisms of action.The main research contents of this paper are as follows:1.A multilayer network was constructed based on the association information of TCM,targets,diseases and symptoms,and the complex network theory was used for systematic research.Based on the association information of Dan Shen,Jiang Xiang and IS,the proteinprotein interaction network and the "drug pair-pharmacodynamic ingredient-target-IS" network were constructed.Different network topological characteristics were analyzed and the core pharmacodynamic ingredients and core targets were identified based on multiple central indexes.Furthermore,a method was proposed to screen candidate TCMs for IS based on TCM symptoms,and the "drug pair-TCM symptoms-syndrome-stroke" network was used to find the key TCM symptoms and syndromes.The results showed that Pu Huang,San Leng and Ze Lan were potential candidates for the treatment of IS,which provided theoretical reference for development of drugs for the treatment of IS.2.Mining the local causality and global causality among substances in the metabolic process based on the causality network.In this study,the time series data of the contents of substances in the plasma of rats with cerebral ischemia after the administration of Xiang Dan Injection(XDI)were used as the research objects.Firstly,Convergent Cross Mapping(CCM)algorithm was used to calculate the causal relationship between substances in the metabolic system.Considering the complex types and large number of components in a complex metabolic system,a causality network is further constructed.Through the analysis of the local causality between two substances and the analysis of the global causality between many substances based on the causality network,the substance pairs with strong causality relationship and the key substances in the metabolic process were identified.3.Mining the dynamic changes of substance-substance correlation in metabolic process based on dynamic substance-substance correlation network.Firstly,the dynamic substancesubstance correlation was calculated,and the dynamic substance-substance correlation network was constructed based on the dynamic correlation.Then the Persistent Communities by Eigenvector Smoothing(Pis CES)algorithm is used to detect the substance cluster in the dynamic correlation network to analyze the evolution of the correlation between the substances.The dynamic centrality of nodes in the network was calculated to analyze the core substances in the metabolic process.The study found that the key period of drug action was the 5 hours after drug administration.Combined with the conclusion of the causal network model,core substances and core substance groups were identified.This paper explores the correlations between TCM ingredients and with substances in body through the study of multilayer networks,causal networks and dynamic correlation network models,providing a new approach to analyse TCM ingredients for the treatment of complex diseases,helping to identify key effectors and explain their mechanisms of action.This study provides a theoretical reference for the development of TCM for the treatment of complex diseases.