Exploration of Ziziphi Spinosae Semen in Treating Insomnia Based on Network Pharmacology Strategy

Ziziphi Spinosae Semen (ZSS) is a common natural medicine used to treat insomnia, and to show clearly its method of action, we managed and did an in-depth discussion. Network pharmacology research is very suitable for the analysis of multiple components, multiple targets, and multiple pathways of Traditional Chinese Medicine (TCM). According to the relevant theory, we first carefully collected and screened the active ingredients in ZSS and received 11 active ingredients that may work. The targets going along with these active components were also strongly related to insomnia targets, 108 common genes were identified, and drug-compound-gene symbol-disease visualization network and protein-protein interaction network were constructed. Forty-eight core genes were identified by PPI analysis and subjected to GO functional analysis with KEGG pathway analysis. The results of GO analysis pointed that there were 998 gene ontology items for the treatment of insomnia, including terms of 892 biological processes, 47 cellular components, and 59 molecular functions. It mainly shows the coupling effect and transport mode of some proteins in the biological pathways of ZSS in the treatment of insomnia and explains the mechanism of action through the connection between the target and the cell biomembrane. KEGG enrichment analyzed 19 signaling pathways, which were collectively classified into seven categories. We have identified the potential pathways of ZSS against insomnia and obtained the regulatory relationship between core genes and pathways and know that the same target can be regulated by multiple components at the same time. The results of molecular docking also prove this conclusion. We sought to provide a new analytical approach to explore TCM treatments for diseases using network pharmacology analysis tools.

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Investigation of the Mechanisms of Neuroprotection Mediated by Lobelia Species via Computational Network Pharmacology and Molecular Modeling

10.21203/rs.3.rs-61537/v1 ◽

2020 ◽

Author(s):

Qinfang Zheng ◽

Liangzi Fang ◽

Xiaolong Huang ◽

Ye Wang ◽

Shuihan Zhang

Keyword(s):

Molecular Modeling ◽

Neurodegenerative Diseases ◽

Interaction Network ◽

Enrichment Analysis ◽

Docking Studies ◽

Network Pharmacology ◽

Active Ingredients ◽

Active Components ◽

Neuroprotective Actions ◽

Gaba Transporter 1

Abstract BackgroundSeveral species of the medicinally valuable genus Lobelia (Campanulaceae) exhibit neuroprotection. While the neuroprotective mechanisms of some components (e.g. lobeline, lobelanine, and lobelanidine) belonging to the L. nicotianaefolia or L. inflata are extensively characterized, there remains the need to study and elucidate the mechanism of action of other species and their active components. In this work, we have studied the neuroprotective mechanism of the pharmacokinetically favorable active compounds of 17 Lobelia species.MethodsNetwork pharmacology approach and molecular modeling were employed. We have conducted drug-likeness evaluation, oral bioavailability prediction followed by the Gene Ontology (GO) terms and pathways enrichment analysis, protein-protein and protein-compound interaction network construction and analysis, and molecular docking studies. Five neurodegenerative diseases viz. Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, epilepsy, and Amyotrophic lateral sclerosis along with the common neuroprotection mechanism-associated genes were evaluated.ResultsWe revealed the neuroprotective mechanism of the active ingredients of Lobelia species. Our study strongly indicates that 12 unique active ingredients viz. luteolin, kaempferol, acacetin, chryseriol, norlobelanine, lobelanine, 2-[(2R,6S)-6-[(2R)-2-hydroxy-2-phenylethyl]-1-methylpiperidin-2-yl]-1-phenylethanone, hydroxygenkwanin, lobelanidine, quercetin, and diosmetin regulates 31 targets within multiple signaling pathways. The nitric oxide synthase, brain (NOS1), androgen receptor (ANDR), sodium- and chloride-dependent GABA transporter 1 (SC6A1), apoptosis regulator Bcl-2 (BCL2), RAC-alpha serine/threonine-protein kinase (AKT1), cellular tumor antigen p53, apoptosis regulator BAX, and tumor necrosis factor (TNFA) were identified as the majorly regulated genes. A majority of these target proteins act via several cancer-related pathways proven to have cross-talks with the pathogenesis of neurodegenerative diseases.ConclusionsThis study explains how the active ingredients of the Lobelia species exhibit their neuroprotective actions and provide a reference basis to investigate their pharmacological effects in detail.

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Revealing Synergistic Mechanism of Multiple Components in Gandi Capsule for Diabetic Nephropathy Therapeutics by Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2018/6503126 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Jian Zhang ◽

Qiqiang Zhang ◽

Xiaofei Chen ◽

Yan Liu ◽

Jiyang Xue ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Interaction Network ◽

Network Pharmacology ◽

Active Components ◽

Multiple Components ◽

Uniprotkb Database ◽

Synergistic Mechanism ◽

Compound Database ◽

Main Action ◽

Herbal Medicinal

Gandi capsule, a traditional Chinese herbal medicinal formulation that consists of eight herbs, is used as a clinical therapy for diabetic nephropathy. To clarify the potential synergistic mechanism, this study adopted a network pharmacology strategy to screen the action targets that corresponded to the active components in the Gandi capsule. We first constructed a compound database of 315 components in the Gandi capsule and a target database of diabetic nephropathy, which included 155 target proteins. Six representative compounds were selected to dock with 99 proteins found in the UniProtKB database with their PDB code, and interaction networks between the active ingredients of the Gandi capsule and their targets were mapped out. Results revealed 47 proteins with a high affinity with at least one compound molecule in the Gandi capsule. The main action pathways closely related to the development of diabetic nephropathy were the TGF-β1, AMPK, insulin, TNF-α, and lipid metabolism pathways as per network pharmacology analysis. In the interaction network, ACC1, SOD2, COX2, PKC-B, IR, and ROCK1 proteins had the most frequent interactions with the six compounds. We performed visual molecular docking in silico and experimentally confirmed competitive component-protein binding by SPR and an enzyme activity test, which highlighted the relationships of wogonin to COX2 and SOD2, astragaloside IV to ACC1, and morroniside to ACC1. We concluded that the potential synergistic mechanism of the Gandi capsule resulted from high affinities with multiple proteins and intervention in multiple pathways in combination therapy of diabetic nephropathy.

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Exploration of the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology

10.21203/rs.3.rs-39351/v1 ◽

2020 ◽

Author(s):

Rong-Bin Chen ◽

Ying-Dong Yang ◽

Kai Sun ◽

Shan Liu ◽

Wei Guo ◽

...

Keyword(s):

Signaling Pathways ◽

Postmenopausal Osteoporosis ◽

Target Genes ◽

Interaction Network ◽

Network Pharmacology ◽

Regulation Of Transcription ◽

Active Ingredients ◽

Active Components ◽

Kegg Pathways ◽

Key Genes

Abstract Background Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease that poses huge challenges to individuals and society. Previous studies have confirmed that Ziyin Tongluo Formula (ZYTLF) has a good clinical effect in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP has not been thoroughly explained. Methods TCMSP, TCMID, and BATMAN-TCM databases were used to identify the active ingredients and their putative targets. Genes associated with PMOP were mined from GeneCards, OMIM, DisGeNET databases, and then mapped with the putative targets to obtain overlapping target genes. A network model of "herb-active ingredient-overlapping target genes" was constructed and a protein-protein interaction network of overlapping target genes was built and the key genes were selected based on the MCC algorithm. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analyses. Results Ninety-two active components of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. GO analysis results showed that biological process mainly included positive regulation of transcription, negative regulation of apoptosis, and cell components were mainly nucleus, cytoplasm, and molecular functions mainly included enzyme binding, protein binding and transcription factor binding. There were two main types of significant KEGG pathways in PMOP, hormone-related signaling pathways (estrogen, prolactin, thyroid hormone) and inflammation-related pathways (TNF, PI3K-Akt, MAPK ). Conclusions The underlying therapeutic mechanisms of ZYTLF action on PMOP maybe is that, the active ingredients such as quercetin, kaempferol, luteolin act on ESR1, TNF, IL6, MAPK8 and other key genes, which mainly enrich in estrogen, TNF, PI3K-Akt, MAPK and other signaling pathways.

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The Prediction of Active Ingredients and Polypharmacological Mechanisms of Orthosiphon stamineus Benth. (Lamiaceae) of Dai medicine based on Network Pharmacology

10.1101/2021.06.12.448214 ◽

2021 ◽

Author(s):

Xingqiang Wang ◽

Weiqing Zhao ◽

Jiangyun Peng

Keyword(s):

Drug Discovery ◽

Pathway Analysis ◽

Interaction Network ◽

Network Pharmacology ◽

Signal Pathways ◽

Active Ingredients ◽

Target Interaction ◽

Orthosiphon Stamineus ◽

Natural Medicine ◽

The Relationship

Background: Orthosiphon stamineus Benth. (OS) was a traditional folk herb with widespread clinical application, but it was lack of comprehensive understanding of its active ingredients and polypharmacological mechanisms. The aim of this work was to systematically study its natural compounds and the molecular mechanisms of the OS via network pharmacology. Methods: Compounds from OS were collected by literature retrieval and evaluated by SwissADME with the physicochemical property (ADMET model) and the likelihood for a natural medicine. The connection of active ingredients and target genes was built and confirmed by Cytoscape and AutoDock vina. Then, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were separately performed to obtain more in-depth understanding of OS. Finally, the relationship among active ingredients, targets, and diseases was built to clarify the polypharmacological mechanisms and found relevant active substances for further drug discovery. Results: A total of 140 compounds of OS were collected, and 16 potentially active ingredients were screened out. The Ingredient-Target Interaction Network was built with 6 flavonoids, 3 diterpenes, 3 phenols, 4 volatile oils, and 64 targets. The Docking analysis indicated that the ingredient-target interaction network was reliable; most ligand-receptor had a strong binding affinity (lowest binding energy: -6.9 kcal/mol). After pathway analysis, 185 significant biological processes and 36 signal pathways were found, and the ingredient-target-disease network of OS was constructed for polypharmacological mechanisms. Conclusion: Our study clarified the polypharmacological mechanisms via the relationship among active ingredients, targets, and diseases and provided better guidance for subsequent experiments and potential active ingredients for drug discovery.

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Mechanism of Compound Houttuynia Mixture as an Anti-COVID-19 Drug Based on Network Pharmacology and Molecular Docking

Natural Product Communications ◽

10.1177/1934578x211016727 ◽

2021 ◽

Vol 16 (5) ◽

pp. 1934578X2110167

Author(s):

Xing-Pan Wu ◽

Tian-Shun Wang ◽

Zi-Xin Yuan ◽

Yan-Fang Yang ◽

He-Zhen Wu

Keyword(s):

Molecular Docking ◽

Target Prediction ◽

Interaction Network ◽

Scientific Basis ◽

Network Pharmacology ◽

Chemical Components ◽

Active Components ◽

Discovery Studio ◽

The Core ◽

Pathway Annotation

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.

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Elucidating the Mechanisms of Hugan Buzure Granule in the Treatment of Liver Fibrosis via Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/8385706 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Yi Zhu ◽

Ming Qiao ◽

Jianhua Yang ◽

Junping Hu

Keyword(s):

Liver Fibrosis ◽

Rna Polymerase Ii ◽

Molecular Mechanisms ◽

Target Genes ◽

Docking Simulation ◽

Interaction Network ◽

Network Pharmacology ◽

Transcription Activator ◽

Active Ingredients ◽

Oxidoreductase Activity

Objective. To holistically explore the latent active ingredients, targets, and related mechanisms of Hugan buzure granule (HBG) in the treatment of liver fibrosis (LF) via network pharmacology. Methods. First, we collected the ingredients of HBG by referring the TCMSP server and literature and filtered the active ingredients though the criteria of oral bioavailability ≥30% and drug-likeness index ≥0.18. Second, herb-associated targets were predicted and screened based on the BATMAN-TCM and SwissTargetPrediction platforms. Candidate targets related to LF were collected from the GeneCards and OMIM databases. Furthermore, the overlapping target genes were used to construct the protein-protein interaction network and “drug-compound-target-disease” network. Third, GO and KEGG pathway analyses were carried out to illustrate the latent mechanisms of HBG in the treatment of LF. Finally, the combining activities of hub targets with active ingredients were further verified based on software AutoDock Vina. Results. A total of 25 active ingredients and 115 overlapping target genes of HBG and LF were collected. Besides, GO enrichment analysis exhibited that the overlapping target genes were involved in DNA-binding transcription activator activity, RNA polymerase II-specific, and oxidoreductase activity. Simultaneously, the key molecular mechanisms of HBG against LF were mainly involved in PI3K-AKT, MAPK, HIF-1, and NF-κB signaling pathways. Also, molecular docking simulation demonstrated that the key targets of HBG for antiliver fibrosis were IL6, CASP3, EGFR, VEGF, and MAPK. Conclusion. This work validated and predicted the underlying mechanisms of multicomponent and multitarget about HBG in treating LF and provided a scientific foundation for further research.

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Discussing the Mechanism of Dahuang Huanglian Xiexin Decoction in the Treatment of Type 2 Diabetes Mellitus via Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-531851/v1 ◽

2021 ◽

Author(s):

Xi Cen ◽

Yan Wang ◽

LeiLei Zhang ◽

XiaoXiao Xue ◽

Yan Wang ◽

...

Keyword(s):

Diabetes Mellitus ◽

Molecular Docking ◽

Target Genes ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Overlapping Genes ◽

Potential Mechanism ◽

Active Components ◽

The Core ◽

Core Genes

Abstract BackgroundType 2 diabetes mellitus (T2DM) is regarded as Pi Dan disease in traditional Chinese medicine (TCM). Dahuang Huanglian Xiexin Decoction (DHXD), a classical TCM formula, has been used for treating Pi Dan disease in clinic, its pharmacological mechanism has not been elucidated. MethodsThis study used network pharmacological analysis and molecular docking approach to explore the mechanism of DHXD on T2DM. Firstly, the compounds in DHXD were obtained from TCMSP and TCMID databases, the potential targets were determined based on TCMSP and UniProt databases. Next, Genecards, Digenet and UniProt databases were used to identify the targets of T2DM. Then, the protein-protein interaction (PPI) network was established with overlapping genes of T2DM and compounds, and the core targets in the network were identified and analyzed. Then, the David database was used for GO and KEGG enrichment analysis. Finally, the target genes were selected and the molecular docking was completed by Autodock software to observe the binding level of active components with target genes.ResultsA total of 397 related components and 128 overlapping genes were identified. After enrichment analysis, it was found that HIF-1, TNF, IL-17 and other signaling pathways, as well as DNA transcription, gene expression, apoptosis and other cellular biological processes had the strongest correlation with the treatment of T2DM by DHXD, and most of them occurred in the extracellular space, plasma membrane and other places, which were related to enzyme binding and protein binding. In addition, 42 core genes of DHXD, such as VEGFA, TP53 and MAPK1, were considered as potential therapeutic targets, indicating the potential mechanism of DHXD on T2DM. Finally, the results of molecular docking showed that HIF-1 pathway had strong correlation with the target genes INSR and GLUT4, quercetin and berberine had the strongest binding power with them respectively.ConclusionThis study summarized the main components of DHXD in the treatment of T2DM, identified the core genes and pathways, and systematically analyzed the interaction of related targets, trying to lay the foundation for clarifying the potential mechanism of DHXD on T2DM, so as to carry out further research in the future.

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Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/8872593 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Ping Yang ◽

Haifeng He ◽

Shangfu Xu ◽

Ping Liu ◽

Xinyu Bai

Keyword(s):

Molecular Docking ◽

Signaling Pathways ◽

Target Genes ◽

Target Prediction ◽

Interaction Network ◽

Network Pharmacology ◽

Core Network ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

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Identification of “Multiple Components-Multiple Targets-Multiple Pathways” Associated with Naoxintong Capsule in the Treatment of Heart Diseases Using UPLC/Q-TOF-MS and Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2016/9468087 ◽

2016 ◽

Vol 2016 ◽

pp. 1-15 ◽

Cited By ~ 12

Author(s):

Xianghui Ma ◽

Bin Lv ◽

Pan Li ◽

Xiaoqing Jiang ◽

Qian Zhou ◽

...

Keyword(s):

Drug Absorption ◽

Heart Diseases ◽

Network Pharmacology ◽

Chemical Compositions ◽

Active Components ◽

Multiple Targets ◽

Multiple Components ◽

Main Components ◽

Tof Ms ◽

Universal Protein

Naoxintong capsule (NXT) is a commercial medicinal product approved by the China Food and Drug Administration which is used in the treatment of stroke and coronary heart disease. However, the research on the composition and mechanism of NXT is still lacking. Our research aimed to identify the absorbable components, potential targets, and associated pathways of NXT with network pharmacology method. We explored the chemical compositions of NXT based on UPLC/Q-TOF-MS. Then, we used the five principles of drug absorption to identify absorbable ingredients. The databases of PharmMapper, Universal Protein, and the Molecule Annotation System were used to predict the main targets and related pathways. By the five principles of drug absorption as a judgment rule, we identified 63 compositions that could be absorbed in the blood in all 81 chemical compositions. Based on the constructed networks by the significant regulated 123 targets and 77 pathways, the main components that mediated the efficacy of NXT were organic acids, saponins, and tanshinones. Radix Astragali was the critical herbal medicine in NXT, which contained more active components than other herbs and regulated more targets and pathways. Our results showed that NXT had a therapeutic effect on heart diseases through the pattern “multiple components-multiple targets-multiple pathways.”

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

10.21203/rs.3.rs-90765/v1 ◽

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.

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