Research On The Mechanism Of Dan Qi Class Based On Protein Interaction Network Module Analysis

Salvia miltrorrhiza(SM)and Ponax notoginseng(PN)herb pairs and its analogous prescriptions are commonly used in various cardiovascular diseases such as coronary heart disease and angina pectoris in Traditional Chinese Medicine(TCM)clinic.Diferent compatibility of the prescriptions makes them exert different roles in TCM clinic.The study of analogous prescriptions is conducive to interpret the compatibility law of TCM.Currentlly,studies of the mechanism of analogous prescription mostly focus on the pharmacology,which had not been studied on systematic level.Network pharmacology has provided a scientific method to study the mechanism of TCM at a molecular network level and a rational approach to discuss the compatibility law of TCM.Proteins are the most important part of the body,and take part in the biological processes,such as signal transport,material and energy metabolism,regulation of gene expression and cell cycle and so on,by their interactions.Studying protein interaction network(PIN)is helpful to understand the mechamism of biological signal transport and material and energy metabolism under the pathological state,which is important to comprehend the mechanism of action of the medicine.Module is the basic functional unit of the PIN and studying the function modules of PIN could make us better understand the performance and features of the complex system,which is important to predict and control the complex system,and is significant to the change and development of the complex system.The reasarch make SM and PN herb pairs and its analogous prescriptions as the carrier,have constructed the PIN of the main active ingredients,constituent,herbs and prescriptions.The study has investigated the influence of the network size and algorithm of module identification,and inspected the influence of random disturbance.With the most appropriate algorithm,module identification has been implemented,and followed by GO enrichment analysis.With modules identified from the networks and the function of them,the molecular mechanism of SM and PN herd pairs and its analogous prescriptions have been explained.This study has provided a novel method to interpret the mechanism of TCM.The main contents of this paper include the following three aspects:1.Methodological studyThe study investigated the robust of the PIN by randomly deleting network nodes,the results showed that randomly deleted 20%nodes of the PIN,the average node connectivity of the PIN were changed slightly.The impact of the network size was studied,the results demonstrated that numbers of the protein interaction should not more than 10,the modularity of the PIN was the highest under this condition.The influence of algorithms of module identification(Molecular Complex Detection,MCODE;Markov Cluster algorithm,MCL;A fast agglomerate algorithm of identifying functional modules based on the edge clustering coefficient,FAG_EC)was also investigated,the result illustrated that MCL algorithm was the most suitable.2.Netork building and module-based network analysisFirstly,through data mining and pharmacophore searching,targets of the main active ingredients were determined.Then with the protein-protein interaction information and the software of cytoscape,29 PINs of the main active ingredients,constituent,herbs and prescription were constructed.Then with the MCL algorithm,module identification was implemented to the 29 PINs.Lastly,followed by GO enrichment ananlysis,the function of the modules obtained.With the modules and functions of them,the molecular mechanism of SM and PN herd pairs and its analogous prescriptions were explained systematically.3.Module-based analysis of the synergy,inheritance and emergent propertyTCM could cure disease,which is contribute to the synergy of mutiple ingredients.The synergy,inheritance and emergent property of SM and PN herd pairs and its analogous prescriptions are discussed at the biological process and module level,this provide a methodological surport to reveal the mechanism and compatibility law of analogous prescriptions at molecular and systematic level.