scholarly journals A network pharmacology approach to discover active compounds and action mechanisms of San-Cao Granule for treatment of liver fibrosis

2016 ◽  
pp. 733 ◽  
Author(s):  
Yan-ling Zhao ◽  
Shizhang Wei ◽  
Ming Niu ◽  
Jian Wang ◽  
Jiabo Wang ◽  
...  
Keyword(s):  
Liver Fibrosis ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Action Mechanisms

scholarly journals Active Compounds Derived from Fuzheng Huayu Formula Protect Hepatic Parenchymal Cells from Apoptosis Based on Network Pharmacology and Transcriptomic Analysis

Molecules ◽  
2019 ◽  
Vol 24 (2) ◽  
pp. 338 ◽  
Author(s):  
Rong Wu ◽  
Shu Dong ◽  
Fei-Fei Cai ◽  
Xiao-Le Chen ◽  
Meng-Die Yang ◽  
...  
Keyword(s):  
Liver Fibrosis ◽  
Cell Apoptosis ◽  
Caspase 3 ◽  
Stellate Cell ◽  
Parenchymal Cell ◽  
Transcriptomic Analysis ◽  
Tanshinone Iia ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Parenchymal Cells

Fuzheng huayu formula (FZHY), an antifibrotic traditional Chinese medicine, is frequently used for the treatment of liver fibrosis. In this study, network analysis, transcriptomic analysis, assays of cell apoptosis, viability and protein expression were used for investigating the effects and mechanisms of compounds derived from FZHY on hepatic parenchymal cell (HPC) protection and hepatic stellate cell activation. Network pharmacology analysis found that 6 major compounds and 39 potential targets were important network nodes. Our analysis predicted that the active compounds of FZHY, including hederagenin, luteolin and tanshinone IIA inhibited cell apoptosis (p < 0.05), increased PI3K expression and reduced cleaved caspase 3 expression and the Bax/Bcl-w ratio (p < 0.05) in L02 cells that had apoptosis induced by TNF-α. Few significant changes caused by FZHY, hederagenin, luteolin and tanshinone IIA were observed in hepatic stellate Lx2 cells upon TGF-β1 induction. These data suggest that FZHY is active against liver fibrosis, protects hepatic parenchymal cells from apoptosis, and recovers liver function, possibly through the effects of its active compounds hederagenin, luteolin and tanshinone IIA and is involved in the inhibition of apoptosis in HPCs, possibly through regulating the PI3K, ERK, cleaved caspase 3 and Bax/Bcl-w levels.

scholarly journals Network Pharmacology-Based Prediction of the Active Compounds, Potential Targets, and Signaling Pathways Involved in Danshiliuhao Granule for Treatment of Liver Fibrosis

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yueying Tao ◽  
Kunming Tian ◽  
Ji Chen ◽  
Danfeng Tan ◽  
Yan Liu ◽  
...  
Keyword(s):  
Liver Fibrosis ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Target Genes ◽  
Process Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Ras Signaling ◽  
Active Ingredients ◽  
Active Compounds

This study aims to predict the active ingredients, potential targets, signaling pathways and investigate the “ingredient-target-pathway” mechanisms involved in the pharmacological action of Danshiliuhao Granule (DSLHG) on liver fibrosis. Pharmacodynamics studies on rats with liver fibrosis showed that DSLHG generated an obvious anti-liver fibrosis action. On this basis, we explored the possible mechanisms underlying its antifibrosis effect using network pharmacology approach. Information about compounds of herbs in DSLHG was collected from TCMSP public database and literature. Furthermore, the oral bioavailability (OB) and drug-likeness (DL) were screened according to ADME features. Compounds with OB≥30% and DL≥0.18 were selected as active ingredients. Then, the potential targets of the active compounds were predicted by pharmacophore mapping approach and mapped with the target genes of the specific disease. The compound-target network and Protein-Protein Interaction (PPI) network were built by Cytoscape software. The core targets were selected by degree values. Furthermore, GO biological process analysis and KEGG pathway enrichment analysis were carried out to investigate the possible mechanisms involved in the anti-hepatic fibrosis effect of DSLHG. The predicted results showed that there were 108 main active components in the DSLHG formula. Moreover, there were 192 potential targets regulated by DSLHG, of which 86 were related to liver fibrosis, including AKT1, EGFR, and IGF1R. Mechanistically, the anti-liver fibrosis effect of DSLHG was exerted by interfering with 47 signaling pathways, such as PI3K-Akt, FoxO signaling pathway, and Ras signaling pathway. Network analysis showed that DSLHG could generate the antifibrosis action by affecting multiple targets and multiple pathways, which reflects the multicomponent, multitarget, and multichannel characteristics of traditional Chinese medicine and provides novel basis to clarify the mechanisms of anti-liver fibrosis of DSLHG.

Exploring the Mechanism of Lingzhu San in Treating Febrile Seizures by Using Network Pharmacology

2020 ◽  
Vol 23 ◽  
Author(s):  
Xiao Zhou ◽  
Xiao-Fei Zhang ◽  
Dong-Yan Guo ◽  
Yan-Jun Yang ◽  
Lin Liu ◽  
...  
Keyword(s):  
Febrile Seizures ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Active Compounds ◽  
Potential Core ◽  
R Language ◽  
The Core ◽  
Multiple Factors ◽  
Therapeutic Mechanism

Objective: Lingzhu San (LZS) is a traditional Chinese medicine (TCM) prescription which can be effective in treating febrile seizures (FS) and has few researches on the mechanisms. In order to better guide the clinical use of LZS, we used the research ideas and methods of network pharmacology to find the potential core compounds, targets and pathways of LZS in the complex TCM system for the treatment of FS, and predict the mechanism. Materials and Methods: Databases such as BATMAN, TCMSP, TCMID, and SWISS TARGET are used to mine the active compounds and targets of LZS, and the target information of FS was obtained through GENECARDS and OMIM. Using Venny2.1.0 and Cytoscape software to locked the potential core compounds and targets of FS. The R language and ClusterProfiler software package were adopt to enrich and analyze the KEGG and GO pathways of the core targets and the biological processes and potential mechanisms of the core targets were revealed. Results: 187 active compounds and 2113 target proteins of LZS were collected. And 38 potential core compounds, 35 core targets and 775 metabolic and functional pathways were screened which involved in mediating FS. Finally, the role of the core compounds, targets and pivotal pathways of LZS regulated FS in the pathogenesis and therapeutic mechanism of FS was discussed and clarified. Conclusions: In this paper, the multi-compounds, multi-targets and multi-pathways mechanism of LZS in the treatment of FS was preliminarily revealed through the analysis of network pharmacology data, which is consistent with the principle of multi-compounds compatibility of TCM prescriptions and unified treatment of diseases from multiple angles, and it provides a new way for TCM to treat complex diseases caused by multiple factors.

Preliminary Study on the Mechanism of Carvacrol Regulating Hepatocellular Carcinoma Based on Network Pharmacology

2019 ◽  
Vol 16 (11) ◽  
pp. 1286-1295
Author(s):  
Sha Li ◽  
Haixia Zhao ◽  
Lidao Bao
Keyword(s):  
Hepatocellular Carcinoma ◽  
Western Blot ◽  
Target Prediction ◽  
Network Pharmacology ◽  
Literature Mining ◽  
Active Compounds ◽  
Prediction Server ◽  
Preliminary Study ◽  
Alignment Analysis ◽  
Endogenous Interactions

Objective: To predict and analyze the target of anti-Hepatocellular Carcinoma (HCC) in the active constituents of Safflower by using network pharmacology. Methods: The active compounds of safflower were collected by TCMSP, TCM-PTD database and literature mining methods. The targets of active compounds were predicted by Swiss Target Prediction server, and the target of anti-HCC drugs was collected by DisGeNET database. The target was subjected to an alignment analysis to screen out Carvacrol, a target of safflower against HCC. The mouse HCC model was established and treated with Carvacrol. The anti-HCC target DAPK1 and PPP2R2A were verified by Western blot and co-immunoprecipitation. Results: A total of 21 safflower active ingredients were predicted. Carvacrol was identified as a possible active ingredient according to the five principles of drug-like medicine. According to Carvacrol's possible targets and possible targets of HCC, three co-targets were identified, including cancer- related are DAPK1 and PPP2R2A. After 20 weeks of Carvacrol treated, Carvacrol group significantly increased on DAPK1 levels and decreased PPP2R2A levels in the model mice by Western blot. Immunoprecipitation confirmed the endogenous interaction between DAPK1 and PPP2R2A. Conclusion: Safflower can regulate the development of HCC through its active component Carvacrol, which can affect the expression of DAPK1 and PPP2R2A proteins, and the endogenous interactions of DAPK1 and PPP2R2A proteins.

scholarly journals Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang
Keyword(s):  
Molecular Docking ◽  
Liver Fibrosis ◽  
Molecular Mechanisms ◽  
Docking Simulation ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Bipartite Network ◽  
Metabolomics Data ◽  
Metabolic Products ◽  
Compound Target

Abstract Background The traditional Chinese medicine Huangqi decoction (HQD) consists of Radix Astragali and Radix Glycyrrhizae in a ratio of 6: 1, which has been used for the treatment of liver fibrosis. In this study, we tried to elucidate its action of mechanism (MoA) via a combination of metabolomics data, network pharmacology and molecular docking methods. Methods Firstly, we collected prototype components and metabolic products after administration of HQD from a publication. With known and predicted targets, compound-target interactions were obtained. Then, the global compound-liver fibrosis target bipartite network and the HQD-liver fibrosis protein–protein interaction network were constructed, separately. KEGG pathway analysis was applied to further understand the mechanisms related to the target proteins of HQD. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets. Finally, considering the concentrations of prototype compounds and metabolites of HQD, the critical compound-liver fibrosis target bipartite network was constructed. Results 68 compounds including 17 prototype components and 51 metabolic products were collected. 540 compound-target interactions were obtained between the 68 compounds and 95 targets. Combining network analysis, molecular docking and concentration of compounds, our final results demonstrated that eight compounds (three prototype compounds and five metabolites) and eight targets (CDK1, MMP9, PPARD, PPARG, PTGS2, SERPINE1, TP53, and HIF1A) might contribute to the effects of HQD on liver fibrosis. These interactions would maintain the balance of ECM, reduce liver damage, inhibit hepatocyte apoptosis, and alleviate liver inflammation through five signaling pathways including p53, PPAR, HIF-1, IL-17, and TNF signaling pathway. Conclusions This study provides a new way to understand the MoA of HQD on liver fibrosis by considering the concentrations of components and metabolites, which might be a model for investigation of MoA of other Chinese herbs.

scholarly journals Potential mechanisms of Guizhi decoction against hypertension based on network pharmacology and Dahl salt-sensitive rat model

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Jiye Chen ◽  
Yongjian Zhang ◽  
Yongcheng Wang ◽  
Ping Jiang ◽  
Guofeng Zhou ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Rat Model ◽  
Experimental Studies ◽  
Matrix Metalloproteinase 2 ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Active Compounds ◽  
Guizhi Decoction

Abstract Background Guizhi decoction (GZD), a classical Chinese herbal formula, has been widely used to treat hypertension, but its underlying mechanisms remain elusive. The present study aimed to explore the potential mechanisms and therapeutic effects of GZD on hypertension by integrating network pharmacology and experimental validation. Methods The active ingredients and corresponding targets were collected from the Traditional Chinese Medicine Systems Pharmacology database and Analysis Platform (TCMSP). The targets related to hypertension were identified from the CTD, GeneCards, OMIM and Drugbank databases. Multiple networks were constructed to identify the key compounds, hub targets, and main biological processes and pathways of GZD against hypertension. The Surflex-Dock software was used to validate the binding affinity between key targets and their corresponding active compounds. The Dahl salt-sensitive rat model was used to evaluate the therapeutic effects of GZD against hypertension. Results A total of 112 active ingredients, 222 targets of GZD and 341 hypertension-related targets were obtained. Furthermore, 56 overlapping targets were identified, five of which were determined as the hub targets for experimental verification, including interleukin 6 (IL-6), C–C motif chemokine 2 (CCL2), IL-1β, matrix metalloproteinase 2 (MMP-2), and MMP-9. Pathway enrichment analysis results indicated that 56 overlapping targets were mainly enriched in several inflammation pathways such as the tumor necrosis factor (TNF) signaling pathway, Toll-like receptor (TLR) signaling pathway and nuclear factor kappa-B (NF-κB) signaling pathway. Molecular docking confirmed that most active compounds of GZD could bind tightly to the key targets. Experimental studies revealed that the administration of GZD improved blood pressure, reduced the area of cardiac fibrosis, and inhibited the expression of IL-6, CCL2, IL-1β, MMP-2 and MMP-9 in rats. Conclusion The potential mechanisms and therapeutic effects of GZD on hypertension may be attributed to the regulation of cardiac inflammation and fibrosis.

scholarly journals Network Pharmacological Analysis and Experimental Validation of the Mechanisms of Action of Si-Ni-San Against Liver Fibrosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Siliang Wang ◽  
Cheng Tang ◽  
Heng Zhao ◽  
Peiliang Shen ◽  
Chao Lin ◽  
...  
Keyword(s):  
Liver Fibrosis ◽  
Hepatic Stellate Cells ◽  
Stellate Cells ◽  
Mechanisms Of Action ◽  
Network Pharmacology ◽  
Related Factor ◽  
Alcoholic Fatty Liver ◽  
Ppar Γ ◽  
Liver Tissues

Background: Si-Ni-San (SNS), a commonly used traditional Chinese medicine (TCM) formula, has potency against liver diseases, such as hepatitis and non-alcoholic fatty liver disease (NAFLD). However, the therapeutic efficacy and pharmacological mechanisms of action of SNS against liver fibrosis remain largely unclear.Methods: A carbon tetrachloride (CCl4)-induced liver fibrosis mouse model was adopted for the first time to investigate the beneficial effects of SNS on liver fibrosis. The potential mechanisms of action of SNS were explored using the network pharmacology-based strategy and validated with the aid of diverse assays.Results: SNS treatment reduced collagen and ECM deposition, downregulated fibrosis-related factor (hyaluronic acid and laminin) contents in serum, maintained the morphological structure of liver tissue, and improved liver function in the liver fibrosis model. Based on network pharmacology results, apoptosis, inflammation and angiogenesis, together with the associated pathways (including VEGF, TNF, caspase, PPAR-γ and NF-κB), were identified as the mechanisms underlying the effects of SNS on liver fibrosis. Further in vivo experiments validated the significant mitigatory effects of SNS on inflammatory infiltration and pro-inflammatory cytokine contents (IFNγ, IL-1β and TGF-β1) in liver tissues of mice with liver fibrosis. SNS suppressed pathologic neovascularization as well as levels of VEGFR1, VEGF and VEGFR2 in liver tissues. SNS treatment additionally inhibited hepatic parenchyma cell apoptosis in liver tissues of mice with liver fibrosis and regulated apoptin expression while protecting L02 cells against apoptosis induced by TNF-α and Act D in vitro. Activation of hepatic stellate cells was suppressed and the balance between MMP13 and TIMP1 maintained in vitro by SNS. These activities may be associated with SNS-induced NF-κB suppression and PPAR-γ activation.Conclusion: SNS effectively impedes liver fibrosis progression through alleviating inflammation, ECM accumulation, aberrant angiogenesis and apoptosis of hepatic parenchymal cells along with inhibiting activation of hepatic stellate cells through effects on multiple targets and may thus serve as a novel therapeutic regimen for this condition.

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

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.

scholarly journals Identifying Active Compounds and Targets of Fritillariae thunbergii against Influenza-Associated Inflammation by Network Pharmacology Analysis and Molecular Docking

Molecules ◽  
2020 ◽  
Vol 25 (17) ◽  
pp. 3853 ◽  
Author(s):  
Minjee Kim ◽  
Ki Hoon Park ◽  
Young Bong Kim
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Target Genes ◽  
Inflammatory Diseases ◽  
Network Pharmacology ◽  
Pharmacokinetic Parameters ◽  
Active Compounds ◽  
Biological Targets ◽  
Underlying Mechanisms ◽  
Cox 1

Complications due to influenza are often associated with inflammation with excessive release of cytokines. The bulbs of Fritillariae thunbergii (FT) have been traditionally used to control airway inflammatory diseases, such as bronchitis and pneumonia. To elucidate active compounds, the targets, and underlying mechanisms of FT for the treatment of influenza-induced inflammation, systems biology was employed. Active compounds of FT were identified through the TCMSP database according to oral bioavailability (OB) and drug-likeness (DL) criteria. Other pharmacokinetic parameters, Caco-2 permeability (Caco-2), and drug half-life (HL) were also identified. Biological targets of FT were retrieved from DrugBank and STITCH databases, and target genes associated with influenza, lung, and spleen inflammation were collected from DisGeNET and NCBI databases. Compound-disease-target (C-D-T) networks were constructed and merged using Cytoscape. Target genes retrieved from the C-D-T network were further analyzed with GO enrichment and KEGG pathway analysis. In our network, GO and KEGG results yielded two compounds (beta-sitosterol (BS) and pelargonidin (PG)), targets (PTGS1 (COX-1) and PTGS2 (COX-2)), and pathways (nitric oxide, TNF) were involved in the inhibitory effects of FT on influenza-associated inflammation. We retrieved the binding affinity of each ligand-target, and found that PG and COX-1 showed the strongest binding affinity among four binding results using a molecular docking method. We identified the potential compounds and targets of FT against influenza and suggest that FT is an immunomodulatory therapy for influenza-associated inflammation.

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