scholarly journals An Investigation of the Antigastric Cancer Effect in Tumor Microenvironment of Radix Rhei Et Rhizome: A Network Pharmacology Study

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xinmiao Wang ◽  
Guanghui Zhu ◽  
Haoyu Yang ◽  
Ruike Gao ◽  
Zhe Wu ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Rna Polymerase Ii ◽  
Signaling Pathway ◽  
Kinase Activity ◽  
Topological Analysis ◽  
Chinese Herb ◽  
Estrogen Signaling ◽  
Receptor Protein ◽  
Network Pharmacology ◽  
Target Network

Background. Tumor microenvironment (TME) takes a vital effect on the occurrence and development of cancer. Radix Rhei Et Rhizome (RRER, Da-Huang in pinyin), a classical Chinese herb, has been widely used in gastric cancer (GC) for many years in China. However, inadequate systematic studies have focused on the anti-GC effect of RRER in TME. This study intended to uncover the mechanism of it by network pharmacology. Methods. We collected compounds and targets of RRER from traditional Chinese medicine system pharmacology database and analysis platform (TCMSP) and SwissTargetPrediction. GC targets were obtained from GeneCards. Protein-protein interaction (PPI) network and RRER-GC-target network were built by STRING and Cytoscape 3.2.1. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed using Database for Annotation, Visualization, and Integrated Discovery (DAVID). Results. We obtained 92 compounds of RRER. A total of 10 key compounds and 20 key targets were selected by “RRER-GC-target network” topological analysis. GO analysis showed that the biological process mainly involved in response to the tumor necrosis factor, positive regulation of fibroblast proliferation, and DNA damage response, signal transduction by p53 class mediator resulting in cell cycle arrest. Molecular functions included cyclin-dependent protein serine/threonine kinase activity, RNA polymerase II transcription factor activity, ligand-activated sequence-specific DNA binding, and transmembrane receptor protein tyrosine kinase activity. Cellular components mainly were centrosome, cell surface, and membrane. KEGG pathway enrichment results mainly involved in the p53 signaling pathway, estrogen signaling pathway, and regulation of lipolysis in adipocytes. Conclusion. This study explored the anti-GC mechanism of RRER from the perspective of TME based on network pharmacology, which contributed to the development and application of RRER.

scholarly journals Network Pharmacology-Based Prediction of Mechanism of Shenzhuo Formula for Application to DKD

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xinmiao Wang ◽  
Haoyu Yang ◽  
Lili Zhang ◽  
Lin Han ◽  
Sha Di ◽  
...  
Keyword(s):  
Rna Polymerase Ii ◽  
Signaling Pathway ◽  
Topological Analysis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Go Analysis

Background. Shenzhuo formula (SZF) is a traditional Chinese medicine (TCM) prescription which has significant therapeutic effects on diabetic kidney disease (DKD). However, its mechanism remains unknown. Therefore, this study aimed to explore the underlying anti-DKD mechanism of SZF. Methods. The active ingredients and targets of SZF were obtained by searching TCMSP, TCMID, SwissTargetPrediction, HIT, and literature. The DKD target was identified from TTD, DrugBank, and DisGeNet. The potential targets were obtained and PPI network were built after mapping SZF targets and DKD targets. The key targets were screened out by network topology and the “SZF-key targets-DKD” network was constructed by Cytoscape. GO analysis and KEGG pathway enrichment analysis were performed by using DAVID, and the results were visualized by Omicshare Tools. Results. We obtained 182 potential targets and 30 key targets. Furthermore, a “SZF-key targets-DKD” network topological analysis showed that active ingredients like M51, M21, M5, M71, and M28 and targets like EGFR, MMP9, MAPK8, PIK3CA, and STAT3 might play important roles in the process of SZF treating in DKD. GO analysis results showed that targets were mainly involved in positive regulation of transcription from RNA polymerase II promoter, inflammatory response, lipopolysaccharide-mediated signaling pathway, and other biological processes. KEGG showed that DKD-related pathways like TNF signaling pathway and PI3K-Akt signaling pathway were at the top of the list. Conclusion. This research reveals the potential pharmacological targets of SZF in the treatment of DKD through network pharmacology and lays a foundation for further studies.

scholarly journals Exploring the Mechanisms of Arsenic Trioxide (Pishuang) in Hepatocellular Carcinoma Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xinmiao Wang ◽  
Luchang Cao ◽  
Jingyuan Wu ◽  
Guanghui Zhu ◽  
Xiaoyu Zhu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Transcription Factor ◽  
Rna Polymerase Ii ◽  
Arsenic Trioxide ◽  
Signaling Pathway ◽  
Cellular Response ◽  
Topological Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Nf Kappa B

Objective. Arsenic trioxide (Pishuang, Pishi, arsenolite, As2O3, and CAS 1327-53-3), a naturally occurring and toxic mineral as a drug for more than 2000 years in China, has been found to have a valuable function in hepatocellular carcinoma (HCC) in recent years. However, its exact mechanism remains to be elucidated. Therefore, this study was intended to explore the potential anti-HCC mechanism of arsenic trioxide through network pharmacology. Methods. The potential targets of arsenic trioxide were collected from PubChem and TargetNet. HCC targets were obtained from the GeneCards database. Then, a protein-protein interaction (PPI) network of arsenic trioxide and HCC common targets was established using STRING. GO and KEGG pathway enrichment analyses were performed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Finally, an arsenic trioxide-target-pathway-HCC network was built by Cytoscape 3.2.1, and network topological analysis was carried out to screen the key candidate targets. Results. A total of 346 corresponding targets of arsenic trioxide and 521 HCC-related targets were collected. After target mapping, a total of 52 common targets were obtained. GO analysis showed that the biological process was mainly involved in the negative regulation of cellular senescence, response to tumor necrosis factor, and cellular response to hypoxia. Molecular functions included NF-kappa B binding, enzyme binding, p53 binding, and transcription factor binding. Cellular components mainly were replication fork, ESC/E(Z) complex, RNA polymerase II transcription factor complex, and organelle membrane. KEGG pathways were mainly enriched in the PI3K-Akt signaling pathway, VEGF signaling pathway, p53 signaling pathway, HIF-1 signaling pathway, TNF signaling pathway, AMPK signaling pathway, NF-kappa B signaling pathway, FoxO signaling pathway, ErbB signaling pathway, and MAPK signaling pathway. In the arsenic trioxide-target-pathway-HCC network, targets such as AKT1, RAF1, RELA, TP53, and PTEN had a higher degree. Conclusions. Our study showed that key targets of arsenic trioxide were mainly involved in multiple biological processes and pathways. It provided a theoretical basis for the screening of drug targets.

scholarly journals Identification of the active substances and mechanisms of ginger for the treatment of colon cancer based on network pharmacology and molecular docking

2020 ◽  
Author(s):  
MengMeng Zhang ◽  
Dan Wang ◽  
Feng Lu ◽  
Rong Zhao ◽  
Xun Ye ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Cellular Response ◽  
Protein Localization ◽  
Docking Simulation ◽  
Estrogen Signaling ◽  
Receptor Protein ◽  
Network Pharmacology ◽  
Active Compounds

Abstract Background: Colon cancer is increasing recently but the high cost and adverse side effects experienced always leads to treatment drop out. Zingiber officinale, commonly known as ginger, is a popular herbal medicine and this study was aimed to identify the active compounds from ginger and to investigate its anti-cancer mechanisms through network pharmacology construction. Results: Ginger compounds were discerned through the TCMSP, which were filtered by the metrics of oral bioavailability and drug likeness, and its related targets were searched. After that, the targets interacting with colon cancer were collected using Genecards, OMIM, and Drugbank databases. Six potential active compounds, 288 interacting targets in addition to 1356 disease-related targets were collected, of which 114 intersection targets were obtained. The PPI network showed that 32 targets including SRC, PIK3R1, and TP53 were identified as key targets. These targets were mainly associated with the biological processes like transmembrane receptor protein tyrosine kinase signaling pathway, regulation of cellular protein localization, cellular response to oxidative stress. KEGG enrichment manifested that ginger probably produced preventive effects against colon cancer by regulating significant signaling pathway like pathway in cancer, hepatitis B, and estrogen signaling pathway. TP53, HSP90AA1, MAPK8, JAK2, CASP3, and ERBB2 could be viewed as the most potential target proteins, which were validated by molecular docking simulation.Conclusion: This study demonstrated the multi-component, multi-target, and multi-pathway characteristics of ginger, providing novel insight for ginger compounds developed as new drug for anti-colon cancer.

scholarly journals Network Pharmacology-Based Strategy for Predicting Therapy Targets of Traditional Chinese Medicine Xihuang Pill on Liver Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xu Zhao ◽  
Jian Hao ◽  
Sinuan Chen
Keyword(s):  
Chinese Medicine ◽  
Liver Cancer ◽  
Kinase Activity ◽  
Molecular Targets ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Ppi Network ◽  
Therapy Targets ◽  
Target Network

Objective. To investigate the potential therapy targets and pharmacological mechanism of traditional Chinese medicine (TCM) Xihuang pill in liver cancer based on network pharmacology. Methods. Drug ingredients-target network was constructed based on the target sets of Xihuang pill and liver cancer. The overlapping genes between Xihuang pill targets and liver cancer-related molecular targets were investigated using comparative analysis. Moreover, the PPI network and module was constructed based on overlapping genes and hub nodes, respectively, followed by the pathway enrichment analysis. Results. A drug ingredients-target network was established with 1184 nodes and 11035 interactions. Moreover, a total of 106 overlapping genes were revealed between drug targets and liver cancer molecular targets. Furthermore, a PPI network and 4 modules were further investigated based on overlapping genes, respectively. These hub nodes such as VEGFA and EGFR were mainly enriched in GO functions including positive regulation of MAP kinase activity, activation of protein kinase activity, regulation of MAP kinase activity, and pathways like proteoglycans in cancer, bladder cancer, and estrogen signaling. Conclusion. VEGFA and EGFR might be potential therapy targets of Xihuang pill in liver cancer. Furthermore, the effect of Xihuang pill on liver cancer might be realized by targeting VEGFA and EGFR in pathways like proteoglycans in cancer and estrogen signaling.

scholarly journals A Network Pharmacology-Based Study on Active Ingredients of Corydalis Rhizoma on Coronary Heart Disease

2020 ◽  
Author(s):  
Ying Li ◽  
Guhang Wei ◽  
Zhenkun Zhuang ◽  
Mingtai Chen ◽  
Changjian Yuan ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Signaling Pathway ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Active Components

Abstract BackgroundCorydalis Rhizoma(CR) showed a high efficacy for coronary heart disease (CHD). However, the interaction between the active ingredients of CR and the targets of CHD has not been unequivocally explained in previous researches. To study the active components and potential targets of Corydalis Rhizoma and to determine the mechanism underlying the exact effect of Corydalis Rhizoma on coronary heart disease, a method of network pharmacology was used.Materials and MethodsThe active components of CR and targets corresponding to each component were scanned out from Traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), and target genes of CHD were searched on GeneCards database and Online Mendelian Inheritance in Man(OMIM) database. The active components and common targets of CR and CHD were used to build the “CR-CHD” network through Cytoscape (version 3.2.1) software as well as protein-protein interaction(PPI) network on String database. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis was executed by clusterProfiler(version 3.8) and DOSE(version 3.6) package on R platform.Results49 active ingredients and 394 relevant targets of CR and the 7173 CHD-related genes were retrieved. 40 common genes were selected for subsequent analysis. Crucial biological processes and pathways were obtained and analyzed, including DNA-binding transcription activator activity, RNA polymerase II-specific, RNA polymerase II transcription factor binding, kinase regulator activity, ubiquitin-like protein ligase binding, fluid shear stress and atherosclerosis, TNF signaling pathway, apoptosis, MAPK signaling pathway and PI3K-Akt signaling pathway.ConclusionsOverall, CR could alleviate CHD through the mechanisms predicted by network pharmacology, laying the foundation for future development of new drugs from traditional Chinese medicine on CHD.

scholarly journals Study on the Mechanisms and Experimental Verification of Cuscuta-Salvia (Tusizi-Danshen) in the Treatment of Polycystic Ovary Syndrome (PCOS) via Network Pharmacology

2021 ◽  
Author(s):  
Ying-ying Zhang ◽  
Jian-xiong Ma ◽  
Yu-tian Zhu ◽  
Yi-xuan Wang ◽  
Wang-qiang Chen ◽  
...  
Keyword(s):  
Dna Binding ◽  
Rna Polymerase Ii ◽  
Signaling Pathway ◽  
Polycystic Ovary ◽  
Network Pharmacology ◽  
Transcription Activator ◽  
Active Components ◽  
Ovary Syndrome ◽  
Core Genes ◽  
Tof Ms

Abstract Polycystic ovary syndrome (PCOS) is a sort of endocrine disease associated with Reproduction. The formula of Cuscuta-Salvia has been widely used in treatment of PCOS in clinic. However, its chemical and pharmacological are still not known in detail. First, the active components of Cuscuta-Salvia were identified by UHPLC-ESI-Q-TOF-MS and screened from TCMSP database, and the disease targets were obtained from the DisGeNET and GeneCards databases. Subsequently, common targets between Cuscuta-Salvia and PCOS were obtained via a Venn diagram. Second, a protein-protein interaction (PPI) network was established. Core genes were selected using Cytoscape software plugin. Third, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed for common targets using “pathview” package in R. Finally, several core targets were verified via determination of qRT-PCR and HE staining. Combined UHPLC-ESI-Q-TOF-MS analysis with network pharmacology study, 14 active components were obtained. Eighty common targets were also obtained. Ten core genes were regulated by Cuscuta-Salvia in PCOS, including IL6, AKT1, VEGFA, TP53, TNF, MAPK1, JUN, EGF, CASP3, and EGFR. GO results showed that cellular response to drug, response to oxygen levels, response lipopolysaccharide, and response to molecule of bacterial origin in biological process (BP) category; membrane, transcription regulator complex, nuclear chromatin, postsynaptic membrane, and vesicle lumen in cellular component (CC) category; DNA-binding transcription factor binding, RNA polymerase II-specific DNA-binding transcription factor binding, DNA-binding transcription activator activity, RNA polymerase II-specific, DNA-binding transcription activator activity, and cytokine receptor binding in molecular function (MF) terms. KEGG enrichment pathway mainly involves in PI3K−Akt signaling pathway, MAPK signaling pathway, cellular senescence, TNF signaling pathway, and IL-17signaling pathway. Furthermore, based on an experimental study, Cuscuta-Salvia ameliorated the pathology of ovary, live and adipose tissue. Additional, Cuscuta-Salvia increased the mRNA expression of VEGFA. Cuscuta-Salvia decreased the mRNA expression of IL6, AKT1, TP53, MAPK1, JUN, EGF, AR, LHb, CYP17a1, and CYP19a1. Our results demonstrate that Cuscuta-Salvia may provide a novel pharmacology basis in an experimental model of PCOS via the regulation of the gene expression. This study lays a basis for subsequent research and clinical application.

scholarly journals Systemic Elucidate The Potential Bioactive Compounds and Hypoglycemic Mechanism of Polygonum Multiflorum Based on Network Pharmacology

2020 ◽  
Author(s):  
Yunfei Song ◽  
Jianbo Yang ◽  
Wenguang Jing ◽  
Qi Wang ◽  
Yue Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Acid Metabolism ◽  
Osteoclast Differentiation ◽  
Interaction Network ◽  
Arachidonic Acid Metabolism ◽  
Hypoglycemic Effect ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Polygonum Multiflorum

Abstract Background: Diabetes is a complex metabolic disease characterized by hyperglycemia, plaguing the whole world. However, the action mode of multi-component and multi-target for traditional Chinese medicine (TCM) could be a promising treatment of diabetes mellitus. According to the previous research, the TCM of polygonum multiflorum (PM) showed noteworthy hypoglycemic effect. Up to now, its hypoglycemic active ingredients and mechanism of action are not yet clear. In this study, network pharmacology was employed to elucidate the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum (PM).Methods: First, the compounds with good pharmacokinetic properties were screened from the self-established library of PM, and the targets of these compounds were predicted and collected through database. Relevant targets of diabetes were summarized by searching database. The intersection targets of compound-targets and disease-targets were obtained soon. Secondly, the interaction net between the compounds and the filtered targets was established. These key targets were enriched and analyzed by PPI analysis, molecular docking verification. Finally, the key genes were used to find the biologic pathway and explain the therapeutic mechanism by GO and KEGG analysis. Results: In this study, 29 hypoglycemic components and 63 hypoglycemic targets of PM were filtrated based on online network database. Then the component-target interaction network was constructed and five key components resveratrol, apigenin, kaempferol, quercetin and luteolin were further obtained. Sequential studies turned out, AKT1, EGFR, ESR1, PTGS2, MMP9, MAPK14, and KDR were the common key targets. Docking studies indicated that the bioactive compounds could stably bind the pockets of target proteins. There were 38 metabolic pathways, including regulation of lipolysis in adipocytes, prolactin signaling pathway, TNF signaling pathway, VEGF signaling pathway, FoxO signaling pathway, estrogen signaling pathway, linoleic acid metabolism, Rap1 signaling pathway, arachidonic acid metabolism, and osteoclast differentiation closely connected with the hypoglycemic mechanism of PM.Conclusion: In summary, the study used systems pharmacology to elucidate the main hypoglycemic components and mechanism of PM. The work provided a scientific basis for the further hypoglycemic effect research of PM and its monomer components, but also provided a reference for the secondary development of PM.

scholarly journals Utilizing Network Pharmacology to Explore the Possible Mechanism of Coptidis Rhizoma in Kawasaki Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Xue Fan ◽  
Xin Guo ◽  
Ying Li ◽  
Mingguo Xu
Keyword(s):  
Kawasaki Disease ◽  
Protein Expression ◽  
Signaling Pathway ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Receptor Protein ◽  
Network Pharmacology ◽  
Control Group ◽  
Coptidis Rhizoma

Background: The purpose of the research is to identify the main active ingredients in Coptidis Rhizoma (CR) and explore the possible molecular mechanisms in the treatment of Kawasaki disease (KD).Materials and Methods: A total of 58 children with KD were randomly divided into a control group and a Berberine treatment group. The therapeutic indicators of the two groups before and after treatment were compared. Then, compounds and drug targets of CR from the TCMSP, SWISS, SEA, and the STITCH were collected, and targeted KD genes were retrieved from the DisGeNET, DrugBank, and GeneCards databases. The network pharmacology approach involved network construction, target prediction, and module analysis. GO and KEGG enrichment analysis were performed to investigate the possible pathways related to CR for KD treatments. Finally, protein expression was determined to verify the core targets using Western blotting in the cell experiment.Results: In total, nine compounds, 369 relative drug targets, and 624 KD target genes were collected in the above database. The network analysis revealed that 41 targets might be the therapeutic targets of CR on KD. GO and KEGG enrichment analysis revealed that the biological processes, namely, response to hormone, response to inorganic substance, and enzyme-linked receptor protein signaling pathway, and Pathways in cancer, Toll-like receptor signaling pathway, and Pancreatic cancer are the most significant. Protein expression of CASP3, PTGS2, and SRC was upregulated and AKT1 and ERK were downregulated.Conclusion: We provided useful resources to understand the molecular mechanism and the potential targets for novel therapy of KD.

scholarly journals Study on the Mechanism of Acori Graminei Rhizoma in the Treatment of Alzheimer’s Disease Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yi Kuan Du ◽  
Yue Xiao ◽  
Shao Min Zhong ◽  
Yi Xing Huang ◽  
Qian Wen Chen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
The Elderly ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Active Components

Alzheimer’s disease is a common neurodegenerative disease in the elderly. This study explored the curative effect and possible mechanism of Acori graminei rhizoma on Alzheimer’s disease. In this paper, 8 active components of Acori graminei rhizoma were collected by consulting literature and using the TCMSP database, and 272 targets were screened using the PubChem and Swiss Target Prediction databases. Introduce it into the software of Cytoscape 3.7.2 and establish the graph of “drug-active ingredient-ingredient target.” A total of 276 AD targets were obtained from OMIM, Gene Cards, and DisGeNET databases. Import the intersection targets of drugs and diseases into STRING database for enrichment analysis, and build PPI network in the Cytoscape 3.7.2 software, whose core targets involve APP, AMPK, NOS3, etc. GO analysis and KEGG analysis showed that there were 195 GO items and 30 AD-related pathways, including Alzheimer’s disease pathway, serotonin synapse, estrogen signaling pathway, dopaminergic synapse, and PI3K-Akt signaling pathway. Finally, molecular docking was carried out to verify the binding ability between Acori graminei rhizoma and core genes. Our results predict that Acori graminei rhizoma can treat AD mainly by mediating Alzheimer’s signal pathway, thus reducing the production of Aβ, inhibiting the hyperphosphorylation of tau protein, regulating neurotrophic factors, and regulating the activity of kinase to change the function of the receptor.

scholarly journals Integrating Data Mining, Network Pharmacology, and Molecular Docking Verification to Investigate the Molecular Mechanism of Traditional Chinese Medicine Prescriptions for Treating Male Infertility

2021 ◽  
Author(s):  
Xue Bai ◽  
Yibo Tang ◽  
Qiang Li ◽  
Guimin Liu ◽  
Dan Liu ◽  
...  
Keyword(s):  
Data Mining ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Male Infertility ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Oxidant Stress ◽  
Estrogen Signaling ◽  
Network Pharmacology

Abstract Background: Male infertility (MI) affects almost 5% adult men worldwide, and 75% of these cases are unexplained idiopathic. There are limitations in the current treatment due to the unclear mechanism of MI, which highlight the urgent need for a more effective strategy or drug. Traditional Chinese Medicine (TCM) prescriptions have been used to treat MI for thousands of years, but their molecular mechanism is not well defined. Methods: Aiming at revealing the molecular mechanism of TCM prescriptions on MI, a comprehensive strategy integrating data mining, network pharmacology, and molecular docking verification was performed. Firstly, we collected 289 TCM prescriptions for treating MI from National Institute of TCM Constitution and Preventive Medicine for 6 years. Then, Core Chinese Materia Medica (CCMM), the crucial combination of TCM prescriptions, was obtained by the TCM Inheritance Support System from China Academy of Chinese Medical Sciences. Next, the components and targets of CCMM in TCM prescriptions and MI-related targets were collected and analyzed through network pharmacology approach.Results: The results showed that the molecular mechanism of TCM prescriptions for treating MI are regulating hormone, inhibiting apoptosis, oxidant stress and inflammatory. Estrogen signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway, and TNF signaling pathway are the most important signaling pathways. Molecular docking experiments were used to further validate network pharmacology results. Conclusions: This study not only discovers CCMM and the molecular mechanism of TCM prescriptions for treating MI, but may be helpful for the popularization and application of TCM treatment.

Sign in / Sign up

Export Citation Format

Share Document