Network Pharmacology-Based Antioxidant Effect Study of Zhi-Zi-Da-Huang Decoction for Alcoholic Liver Disease

Liu, An; Fěng, Fang

doi:10.1155/2015/492470

Cited by 21 publications

(10 citation statements)

References 38 publications

(38 reference statements)

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“…Finally, the active compounds were predicted through molecular docking, and network analysis showed that multiple active pharmaceutical compounds of ZZDHD were found to act on different targets [ 50 ].…”

Section: Network Pharmacologymentioning

confidence: 99%

How Can Synergism of Traditional Medicines Benefit from Network Pharmacology?

et al. 2017

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Many prescriptions of traditional medicines (TMs), whose efficacy has been tested in clinical practice, have great therapeutic value and represent an excellent resource for drug discovery. Research into single compounds of TMs, such as artemisinin from Artemisia annua L., has achieved great success; however, it has become evident that a TM prescription (which frequently contains various herbs or other components) has a synergistic effect in effecting a cure or reducing toxicity. Network pharmacology targets biological networks and analyzes the links among drugs, targets, and diseases in those networks. Comprehensive, systematic research into network pharmacology is consistent with the perspective of holisticity, which is a main characteristic of many TMs. By means of network pharmacology, research has demonstrated that many a TM show a synergistic effect by acting at different levels on multiple targets and pathways. This approach effectively bridges the gap between modern medicine and TM, and it greatly facilitates studies into the synergistic actions of TMs. There are different kinds of synergistic effects with TMs, such as synergy among herbs, effective parts, and pure compounds; however, for various reasons, new drug discovery should at present focus on synergy among pure compounds.

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Section: Network Pharmacologymentioning

confidence: 99%

How Can Synergism of Traditional Medicines Benefit from Network Pharmacology?

et al. 2017

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“…The thought of this study accords with the network pharmacology, but the method we adopted is different from other related works [ 24 , 25 ]. The whole process of other related works is carried out manually and the batch processing is impossible.…”

Section: Discussionmentioning

confidence: 99%

Using Bioinformatics Approach to Explore the Pharmacological Mechanisms of Multiple Ingredients in Shuang-Huang-Lian

Zhang

et al. 2015

The Scientific World Journal

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Due to the proved clinical efficacy, Shuang-Huang-Lian (SHL) has developed a variety of dosage forms. However, the in-depth research on targets and pharmacological mechanisms of SHL preparations was scarce. In the presented study, the bioinformatics approaches were adopted to integrate relevant data and biological information. As a result, a PPI network was built and the common topological parameters were characterized. The results suggested that the PPI network of SHL exhibited a scale-free property and modular architecture. The drug target network of SHL was structured with 21 functional modules. According to certain modules and pharmacological effects distribution, an antitumor effect and potential drug targets were predicted. A biological network which contained 26 subnetworks was constructed to elucidate the antipneumonia mechanism of SHL. We also extracted the subnetwork to explicitly display the pathway where one effective component acts on the pneumonia related targets. In conclusions, a bioinformatics approach was established for exploring the drug targets, pharmacological activity distribution, effective components of SHL, and its mechanism of antipneumonia. Above all, we identified the effective components and disclosed the mechanism of SHL from the view of system.

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“…Cytoscape is widely used in network pharmacology for visualizing molecular and component interaction networks [32]. In the graphical network, compounds and proteins were represented as nodes and intermolecular interactions between molecules (compound-target) were denoted with links [33]. The analysis of network parameters were performed by Network Analyzer (a Cytoscape plug-in).…”

Section: Compound-target Network Constructionmentioning

confidence: 99%

Network Pharmacology-based Strategy for Studying the Mechanism of Gegen Qinlian Decoction for the Treatment of Acute Colitis

Wang

et al. 2020

Preprint

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Background: Gegen Qinlian Decoction(GQD) has been used to treat acute colitis (AC) for several years in China and it has shown good efficacy. However, the active components and target proteins of its anti-AC effects remains to be deciphered. Methods: In this study, serum pharmacochemistry and network pharmacology strategy were integrated to identify the constituents in blood and the mechanism of GQD for the treatment of AC. Ultra-performance liquid chromatography and LTQ-Orbitrap mass spectrometry(UPLC-LTQ-Orbitrap-MS) was used to identify the absorbed components of GQD in rat serum; molecular docking and compound-target network analysis were used to predict candidate targets and critical components in GQD responsible for efficacy; In addition, the Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis and Gene Ontology(GO) enrichment analysis were used to predict the related pathways and biological process respectively; Finally, the model rats with acute colitis were induced by DSS(Dextran Sulfact Sodium) in order to verify the effects and potential mechanism of baicalein, which is an important component of GQD. Results: Based on our comprehensive systematic approach, 23 components were successfully identified in rat serum after oral administration of GQD. The predicted results of molecular docking indicated that these 23 active components closely interacted with 41 protein targets associated with inflammation, immunity and enteric mucos. Among the 23 compounds identified, baicalin, baicalein, wogonoside , liquiritin and daidzin may be the most important components of GQD. Futhermore, according to GO enrichment analysis, the 41 candidate targets identified were mainly involved in two biological process, immune system process and inflammatory response. The KEGG pathway analysis revealed that 41 candidate targets were associated with 62 biological pathways, including HIF-1 signaling pathway and PI3K/Akt signaling pathway. Animal experiments found that baicalein could inhibit the activation of PI3K/Akt/HIF-1 signaling pathway and significantly reduce pro-inflammatory cytokines, such as IL-1β, IL-6, IL-8 and TNF-α to alleviate intestinal mucosal damage and achieve a therapeutic effect on AC. Conclusion: This research not only provides a novel and scientific strategy to better understand the complex mechanism of GQD, but also offers a new perspective to identify and/or discover novel active ingredients of TCM drugs.

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Network Pharmacology-Based Antioxidant Effect Study of Zhi-Zi-Da-Huang Decoction for Alcoholic Liver Disease

Cited by 21 publications

References 38 publications

How Can Synergism of Traditional Medicines Benefit from Network Pharmacology?

How Can Synergism of Traditional Medicines Benefit from Network Pharmacology?

Using Bioinformatics Approach to Explore the Pharmacological Mechanisms of Multiple Ingredients in Shuang-Huang-Lian

Network Pharmacology-based Strategy for Studying the Mechanism of Gegen Qinlian Decoction for the Treatment of Acute Colitis

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