Based On Data Mining And Network Pharmacology To Explore The Mechanism Of Action Of Commonly Used Drugs For Conditioning Phlegm-Dampness Constitution

Objective:Collect and sort out the clinical research literature on chronic diseases of phlegm-dampness constitution based on body differentiation in the past 15 years,use data mining technology to analyze the traditional Chinese medicine prescriptions involved in the literature,explore the drug compatibility rules of body differentiation for chronic diseases of phlegm-dampness constitution,and analyze body differentiation for chronic diseases.The high-frequency drug pairs of phlegm-damp constitution chronic diseases are analyzed by network pharmacology,the targets and pathways of drug action are predicted,and through the cell model to verify the results of network pharmacology prediction,analyze the mechanism of high-frequency medicine on the conditioning of chronic diseases of phlegm-dampness constitution,and provide a way of thinking and method for the study of body-differentiation in the treatment of chronic diseases of phlegm-dampness constitution..Methods:1.By searching the Chinese database China National Knowledge Infrastructure(CNKI),Wanfang Data Knowledge Service Platform(WANFANG DATA),VIP Full-text Database(VIP),Pub Med,and Web of Science databases from January 2007 to December 2021 on identification Based on the clinical research literature on chronic diseases of phlegm-dampness constitution,the literature was screened according to the inclusion and exclusion criteria,and the prescriptions were extracted,and the traditional Chinese medicine inheritance calculation platform V3.Analyzed and excavated the compatibility rules of prescriptions and drugs,and carried out network pharmacology analysis on the core drug pairs.2.The components of the core drug pair were retrieved through the Traditional Chinese Medicine System Pharmacology Analysis Platform(TCMSP),and the target of each component was predicted through the Swiss Target Prediction platform.Metabolic syndrome,atherosclerosis,obesity,hyperuricemia,hypertension,hyperlipidemia,coronary heart disease,chronic obstructive pulmonary disease,cerebral infarction,diabetes,Proper nouns for impaired glucose regulation,impaired glucose tolerance,impaired fasting glucose,prediabetes,non-alcoholic fatty liver disease,obstructive sleep apnea hypopnea syndrome,and target genes associated with these diseases were obtained.The intersection of drug targets and genes related to chronic diseases of phlegm-dampness constitution was imported into STRING database for protein interaction network(PPI)analysis.Cytoscape 3.8.2 was used to calculate the degree value of each node in the PPI network,and the protein was redrawn according to the degree value The interaction network diagram and the core targets in the protein interaction network are extracted through the Cyto Hubba plugin.Metascape was used to perform GO functional enrichment analysis and KEGG pathway enrichment analysis on the intersection genes.A "component-target-pathway" network was constructed using Cytoscape 3.8.2.The target with higher ranking in the PPI network was selected for molecular docking with the top three small molecules of traditional Chinese medicine in the "component-target-pathway" network,and the binding state of the small molecule of traditional Chinese medicine and the target was judged according to the binding energy.Result:(1)A total of 96 literatures were included in this study,and a total of 102 prescriptions were obtained.After statistics,there were 166 traditional Chinese medicines in the 102 prescriptions,and the cumulative frequency was 826 times.The top five in frequency are Poria,tangerine peel,Baizhu,Pinellia,Zhigancao;the distribution of medicinal properties is mainly warm,flat,and cold;the distribution of medicinal tastes is mainly sweet,bitter,and acrid;the statistics of medicines return to meridians,ranking The top five are spleen,lung,stomach,liver,and heart meridians;the top five in efficacy statistics are tonic,diuresis and dampness,clearing heat,regulating qi,resolving phlegm,relieving cough and relieving asthma;association rule analysis,The number of support degrees is set to 10,and the confidence level is set to 0.6.Finally,97 commonly used drug combinations with a frequency of ≥10times are obtained.The top five pairs of drugs are Poria,Atractylodes,Poria,Chenpi,Poria,Pinellia,Poria,Zhigancao,Chenpi,Pinellia.The top five horn medicines are Poria,Chenpi,Pinellia,Poria,Atractylodes,Zhigancao,Poria,Pinellia,Zhigancao,Poria,Chenpi,Zhigancao,Poria,Chenpi,Atractylodes,the top five four flavors The medicinal combination includes Poria,tangerine peel,Pinellia,Zhigancao,Poria,Atractylodes,Pinellia,Zhigancao,Poria,Chenpi,Atractylodes,Zhigancao,Poria,Chenpi,Atractylodes,Pinellia,Poria,Chenpi,Atractylodes,Atractylodes.A total of 3core prescriptions were obtained by cluster analysis: Poria,Pinellia,Atractylodes,dried tangerine peel,Zhigancao,Poria,Chinese yam,Astragalus,Atractylodes,dried orange peel,Poria,Coix seed,dried dried orange peel,hawthorn,and lotus leaf.(2)Through the network pharmacology analysis of the "Poria-tangerine peel" drug pair,according to the pharmacokinetic screening,a total of 20 active ingredients were included,and the intersection of drugs and diseases was 47 targets;the top five targets in the PPI network are TNFα,VEGFA,PPARG,PTGS2,ESR1;KEGG enrichment analysis pathways include AGE-RAGE signaling pathway in diabetic complications,Serotonergic synapse,HIF-RAGE signaling pathway in diabetic complications 1 signaling pathway(HIF-1 signaling pathway),insulin resistance signaling pathway(insulin resistance),PPAR signaling pathway(PPAR signaling pathway),TNF signaling pathway(TNF signaling pathway)and so on.(3)The "Poria-tangerine peel" freeze-dried powder was used to intervene Hep G2 cells to construct an insulin resistance cell model,and it was found by PCR and Western Blot technology that "Poria-tangerine peel" freeze-dried powder could reduce the expression of TNF-α and increase the expression of PPAR family.Conclusion:In the treatment of chronic diseases with phlegm-dampness constitution,the main prescriptions for treating chronic diseases with phlegm-dampness constitution are tonic medicines and diuresis-dampness medicines,which shows that phlegm-dampness constitution is based on spleen deficiency,and the evil of phlegm-dampness is the standard.The analysis results of association rules show that Poria,Atractylodes,Pinellia,and Chenpi cover basically all the core compatibility combinations.The core drug pair is "Poria-Chenpi".Through network pharmacology analysis,the main components of "Poria-Chenpi" are 3β-hydroxy-24-methylene-8-lanolin-21-oleic acid,trimene acid,naringenin,etc.The core targets of action There are tumor necrosis factor,vascular endothelial factor A,peroxisome proliferator-activated receptor γ,prostaglandin-endoperoxidase synthase 2,estrogen receptor 1,etc.Among the regulated pathways,the HIF-1 signaling pathway(HIF-1 signaling pathway),insulin resistance signaling pathway(insulin resistance),PPAR signaling pathway(PPAR signaling pathway),TNF signaling pathway(TNF signaling pathway),AGE-RAGE signaling pathway(AGE-RAGE signaling pathway in diabetic complications)in diabetic complications),etc.are all related to the disorder of glucose and lipid metabolism,and the "Poria-tangerine peel" drug pair may regulate multiple pathways related to glucose and lipid metabolism through multi-component and multi-target pathways,as well as multiple pathways related to glucose and lipid metabolism.Target,play the role of conditioning phlegm-dampness constitution.The experimental verification shows that the combination of "Poria-tangerine peel" can reduce the expression of TNF-α in the IR-Hep G2 cell model,increase the expression of PPARA and PPARG,and achieve the effect of improving insulin resistance,which is consistent with the prediction results of network pharmacology.