Network Pharmacological Study Of Compound Danshen Dripping Pills Based On Gene Expression Profile,drug Target Recognition And Pattern Analysis

In recent years,traditional Chinese medicine(TCM),due to small side effect and clear activity,has attracted more and more people’s attention.However,TCM has multi-component,multi-target,multi-pathway characteristics,so the research on the material base and mechanism of action remains a big challenge.With the completion of human genome sequencing and the development of computer-aided drug design method,the gene expression profile can be used to locate the target gene and the molecular docking be used to predict the drug target interaction.Combining with the network pharmacology techniques,the omics data and docking method provide an opportunity for revealing the multi-component,multi-target,multi-pathway characteristics,and explaining the material base and action mechanism of TCM.In this paper,the gene expression profile and molecular docking technique in addition to network pharmacology techniques were used to explore the mechanism of Compound Danshen Dropping Pill(DSP)in the treatment of atherosclerosis(AS).The main research contents are as follows:1.Based on network approach to identify atherosclerosis-related targets in gene expression profiling.Firstly,the gene expression profiles were mapped into the control group and the disease target gene interaction network.The genotype was treated with typical correlation analysis(CCA).The gene expression profiles of the carotid atherosclerotic patients were analyzed by using the human protein interaction database(HPRD).The data of the sclerotic gene expression profiles were used to convert the redundant expression profiles into the weight of the gene network of the disease group and the control group.Then we selected the gene target related to atherosclerosis by comparing the network topology of the control group and the disease group,and constructed the pre-selected target network.Finally,the R-language and random walk algorithm were used to decompose the pre-selected network into the community structure with different importance,and then identify the key target of atherosclerosis.As a result,62 target targets such as MAPK1,TP53 and PTPN11 were selected as the main target of atherosclerosis,among which 58 genes were verified by the Commparative Toxicogenomics Database(CTD)and the GeneCards database.2.Based on pharmacophore model to study on the mechanism of DSP in treating AS.In the previous section,62 key targets were predicted to be associated with atherosclerotic disease,of which 21 targets were verified by both the CTD database and the GeneCards database.The 3D structures of these targets were downloaded from the PDB database,and with their embedded ligands the pharmacophore models were trained.After a careful evaluation,these models were used to predict the components of DSP,which were collected by applying the rules of five principles.3.Network pharmacology study of DSP based on molecular docking and recognition of biological network function modules.Firstly,a heterogeneous network was established by combining the compound composition-component network and the target interaction network constructed by molecular similarity.Then,by the module analysis the heterogeneous network was disassembled into several modules with different functions.The results of the module analysis showed that the mechanism of DSP in the treatment of AS was related to inflammation,immune and oxidative stress,and that the main components of DSP included danshensu,protocatechuic aldehyde,tanshinone Ⅵ,etc.Based on the above research results,it can be presumed that the related targets of AS include AKT1,CASP3,EP300,TP53 and so on.The main effective components of DSP may have danshensu,protocatechualdehyde,caffeic acid,tanshinone,ginseng triol,ginsenoalkylene glycol,primordic acid and other components,Danshensu perhaps modulate the MAPK Signaling pathway pathway through CASP3,MAPK1,TP53,AKT1,modulate the pathways in cancer through EP300,MAPK1,TP53,AKT1,and modulate the TNF signaling pathway through CASP3,MAPK1,AKT1.These results were all verified by the literatures,thereby proving that the present method was reliable.However,there were still some shortcomings in this paper.For example,in AS target screening,there was few inflammation-related targets.It may be overcome in our future work by collecting more gene expression profile samples,taking account of the importance of the node in addition to the edge,and constructing a weighted network by considering the contents of components and its metabolites.