Network Pharmacology-based Research of Active Components of Albiziae Flos and Mechanisms of Its Antidepressant Effect

Xiong, Weichen; H, Wu; Xiong, Yiyi; Liu, Bo; Xie, Zhengwei; Wu, Songtao; Yao, Yunfeng; Yang, Yong

doi:10.1007/s11596-020-2155-7

Cited by 21 publications

(17 citation statements)

References 28 publications

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“…Among the top 10 signaling pathways predicted by network pharmacological, the signaling pathway ranking at the top had strong correlation with the antidepressant effects of GH, which is the main signaling pathway of the antidepressant mechanism of GH. Therefore, the signaling pathway ranking at the top has more research value (Xiong et al, 2020). The first signaling pathway is neuroactive ligand-receptor interaction, which was related to all receptors and ligands associated with intracellular and extracellular signaling pathways in the plasma membrane (Pan et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

An Integrative Pharmacology-Based Pattern to Uncover the Pharmacological Mechanism of Ginsenoside H Dripping Pills in the Treatment of Depression

et al. 2021

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Objectives: To evaluate the pharmacodynamical effects and pharmacological mechanism of Ginsenoside H dripping pills (GH) in chronic unpredictable mild stress (CUMS) model rats.Methods: First, the CUMS-induced rat model was established to assess the anti-depressant effects of GH (28, 56, and 112 mg/kg) by the changes of the behavioral indexes (sucrose preference, crossing score, rearing score) and biochemical indexes (serotonin, dopamine, norepinephrine) in Hippocampus. Then, the components of GH were identified by ultra-performance liquid chromatography-iron trap-time of flight-mass spectrometry (UPLC/IT-TOF MS). After network pharmacology analysis, the active ingredients of GH were further screened out based on OB and DL, and the PPI network of putative targets of active ingredients of GH and depression candidate targets was established based on STRING database. The PPI network was analyzed topologically to obtain key targets, so as to predict the potential pharmacological mechanism of GH acting on depression. Finally, some major target proteins involved in the predictive signaling pathway were validated experimentally.Results: The establishment of CUMS depression model was successful and GH has antidepressant effects, and the middle dose of GH (56 mg/kg) showed the best inhibitory effects on rats with depressant-like behavior induced by CUMS. Twenty-eight chemical components of GH were identified by UPLC/IT-TOF MS. Subsequently, 20(S)-ginsenoside Rh2 was selected as active ingredient and the PPI network of the 43 putative targets of 20(S)-ginsenoside Rh2 containing in GH and the 230 depression candidate targets, was established based on STRING database, and 47 major targets were extracted. Further network pharmacological analysis indicated that the cAMP signaling pathway may be potential pharmacological mechanism regulated by GH acting on depression. Among the cAMP signaling pathway, the major target proteins, namely, cAMP, PKA, CREB, p-CREB, BDNF, were used to verify in the CUMS model rats. The results showed that GH could activate the cAMP-PKA-CREB-BDNF signaling pathway to exert antidepressant effects.Conclusions: An integrative pharmacology-based pattern was used to uncover that GH could increase the contents of DA, NE and 5-HT, activate cAMP-PKA-CREB-BDNF signaling pathway exert antidepressant effects.

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Section: Discussionmentioning

confidence: 99%

An Integrative Pharmacology-Based Pattern to Uncover the Pharmacological Mechanism of Ginsenoside H Dripping Pills in the Treatment of Depression

et al. 2021

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“…It is generally believed that LiDockscore ≥90 has a strong binding ability when docking with the processed protein. 8 Figure 1 shows a research process of network pharmacology and molecular docking employed for mechanistic investigation of anti-COVID 19 mechanisms of Yinma Jiedu Granules. The five medicinal substances used in the formulation of Yinma Jiedu Granules, namely, purslane, licorice, rhubarb, honeysuckle, and portulaca, were searched through the TCMSP database.…”

Section: Molecular Dockingmentioning

confidence: 99%

Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 Mechanism of Yinma Jiedu Granules

Yuan

Zeng

et al. 2021

Natural Product Communications

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To investigate the mechanism of action of components of Yinma Jiedu granules in the treatment of coronavirus disease 2019 (COVID-19) using network pharmacology and molecular docking. The main chemical components of Yinma Jiedu granules were collected in the literature and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database. Using the SwissTargetPrediction database, the targets of the active component were identified and further correlated to the targets of COVID-19 through the GeneCards database. The overlapping targets of Yinma Jiedu granules components and COVID-19 were identified as the research target. Using the Database for Annotation, Visualization and Integrated Discovery database to carry out the target gene function Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation and Cytoscape 3.6.1 software was used to construct a “component-target-pathway” network. The protein-protein interaction network was built using Search Tool for the Retrieval of Interacting Genes/Proteins database. Using Discovery Studio 2016 Client software to study the virtual docking of key protein and active components. One hundred active components were screened from the Yinma Jiedu Granules that involved 67 targets, including mitogen-activated protein kinase 3 (MAPK3), epidermal growth factor receptor, tumor necrosis factor, tumor protein 53, and MAPK1. These targets affected 109 signaling pathways including hypoxia-inducible factor-1, apoptosis, and Toll-like receptor signaling pathways. Molecular docking results showed that the screened active components have a strong binding ability to the key targets. In this study, through network pharmacology and molecular docking, we justified the multicomponent, multitarget, and multipathways of Yinma Jiedu Granules in the treatment of COVID-19.

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“…Then, the active components were screened based on the threshold of oral bioavailability (OB) ≥30% and drug likeness (DL) ≥0.18. 11 Finally, the SMILE structural formula of each active component was collected on Pubchem (https:// pubchem. ncbi.…”

Section: Collection Screening and Targets Acquisition Of Active Componentsmentioning

confidence: 99%

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

Wang

Yuan

et al. 2021

Natural Product Communications

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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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Network Pharmacology-based Research of Active Components of Albiziae Flos and Mechanisms of Its Antidepressant Effect

Cited by 21 publications

References 28 publications

An Integrative Pharmacology-Based Pattern to Uncover the Pharmacological Mechanism of Ginsenoside H Dripping Pills in the Treatment of Depression

An Integrative Pharmacology-Based Pattern to Uncover the Pharmacological Mechanism of Ginsenoside H Dripping Pills in the Treatment of Depression

Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 Mechanism of Yinma Jiedu Granules

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

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