scholarly journals Network pharmacology reveals hub bio-active ingredients and possible mechanisms of a Chinese herbal prescription Ru-kang-yin against breast cancer

2020 ◽  
Author(s):  
Shirun Chu ◽  
Fang Chen ◽  
Jun Li ◽  
Mei Yang ◽  
Delin Xu
Keyword(s):  
Breast Cancer ◽  
Therapeutic Targets ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Components ◽  
Active Compounds ◽  
Chinese Herbal ◽  
Underlying Mechanisms ◽  
Herbal Prescription

Abstract Background Ru-kang-yin (RKY), a traditional Chinese herbal prescription, has been clinically used as adjuvant therapy for breast cancer via inhibiting cell invasion, proliferation, and promoting apoptosis. However, its anti-breast cancer bio-active ingredients and possible mechanisms are still unclear. In the present study, the hub bio-active compounds and underlying mechanisms of RKY in treatment of breast cancer were systematically elucidated by the approach of network pharmacology. Methods By using network pharmacology approach, a total of 53 nonredundant bio-active components met the drug screening criteria and 155 putative targets of RKY in treatment of breast cancer were identified. Besides, 381 potential breast cancer-related targets were obtained. Among of the targets, 56 shared targets of RKY and breast cancer were acquired. Results Based on topological network analysis of PPI network of shared targets, 19 hub therapeutic targets of RKY against breast cancer were obtained. GO and KEGG pathway enrichment analysis of core therapeutic targets showed that the core targets remarkably involved in multiple biological functions and KEGG pathways which mainly participated in inflammatory response, cell proliferation, and apoptosis. Conclusions These findings uncover the hub bio-active compounds and underlying mechanisms of RKY against breast cancer and provide crucial information regarding using RKY as a promising candidate for treating breast cancer.

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

2020 ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Postmenopausal Osteoporosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Core Proteins ◽  
Key Genes

Abstract Background: Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease, which poses huge challenges to individuals and society. Ziyin Tongluo Formula (ZYTLF) has been proved effective in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP have not been thoroughly elucidated.Methods: Online databases were used to identify the active ingredients of ZYTLF and corresponding putative targets. Genes associated with PMOP were mined, and then mapped with the putative targets to obtain overlapping genes. Multiple networks were constructed and analyzed, from which the key genes were selected. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analysis. Finally, AutoDock Tools and other software were used for molecular docking of core compounds and key proteins. Results: Ninety-two active compounds of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. Network analysis showed the top 5 active ingredients including quercetin, kaempferol, luteolin, scutellarein, and formononetin., and the top 50 key genes such as VEGFA, MAPK8, AKT1, TNF, ESR1. Enrichment analysis uncovered two significant types of KEGG pathways in PMOP, hormone-related signaling pathways (estrogen , prolactin, and thyroid hormone signaling pathway) and inflammation-related pathways (TNF, PI3K-Akt, and MAPK signaling pathway). Moreover, molecular docking analysis verified that the main active compounds were tightly bound to the core proteins, further confirming the anti-PMOP effects. Conclusions: Based on network pharmacology and molecular docking technology, this study initially revealed the mechanisms of ZYTLF on PMOP, which involves multiple targets and multiple pathways.

scholarly journals A Network Pharmacology Study on the Molecular Mechanisms of FDY003 for Breast Cancer Treatment

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ho-Sung Lee ◽  
In-Hee Lee ◽  
Kyungrae Kang ◽  
Sang-In Park ◽  
Seung-Joon Moon ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Herbal Medicines ◽  
Enrichment Analysis ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Anticancer Efficacy ◽  
Artemisia Capillaris

Herbal medicines have drawn considerable attention with regard to their potential applications in breast cancer (BC) treatment, a frequently diagnosed malignant disease, considering their anticancer efficacy with relatively less adverse effects. However, their mechanisms of systemic action have not been understood comprehensively. Based on network pharmacology approaches, we attempted to unveil the mechanisms of FDY003, an herbal drug comprised of Lonicera japonica Thunberg, Artemisia capillaris Thunberg, and Cordyceps militaris, against BC at a systemic level. We found that FDY003 exhibited pharmacological effects on human BC cells. Subsequently, detailed data regarding the biochemical components contained in FDY003 were obtained from comprehensive herbal medicine-related databases, including TCMSP and CancerHSP. By evaluating their pharmacokinetic properties, 18 chemical compounds in FDY003 were shown to be potentially active constituents interacting with 140 BC-associated therapeutic targets to produce the pharmacological activity. Gene ontology enrichment analysis using g:Profiler indicated that the FDY003 targets were involved in the modulation of cellular processes, involving the cell proliferation, cell cycle process, and cell apoptosis. Based on a KEGG pathway enrichment analysis, we further revealed that a variety of oncogenic pathways that play key roles in the pathology of BC were significantly enriched with the therapeutic targets of FDY003; these included PI3K-Akt, MAPK, focal adhesion, FoxO, TNF, and estrogen signaling pathways. Here, we present a network-perspective of the molecular mechanisms via which herbal drugs treat BC.

scholarly journals Network pharmacology-based active compounds and pharmacological mechanisms of ginseng for depression in post-COVID-19

2020 ◽  
Author(s):  
Na Wang ◽  
Xianlei Wang ◽  
Mengjiao He ◽  
Wenxiu Zheng ◽  
Xiaoqing Cai ◽  
...  
Keyword(s):  
Immune Regulation ◽  
Enrichment Analysis ◽  
Sudden Onset ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Life Threatening Illness ◽  
Novel Coronavirus

Abstract Introduction: The novel coronavirus disease 2019 (COVID-19) is in the midst of worldwide panic. Sudden onset of an immediate life-threatening illness, quarantine and unemployment caused by epidemic are all contributors to depression. Ginseng has been reported to be an effective and safe clinical treatment on both immune-regulation and anti-depression. However, the mechanism of its anti-depression effect has not been fully characterized. In order to provide theoretical guidance for further clinical application in post-pandemic, we investigated active compounds and pharmacological mechanisms of ginseng to exert anti-depressant activity using network pharmacology, and discussed the active ingredients with immune-regulation and anti-depression.Methods: Information on compounds in ginseng was obtained from public databases, and genes related to depression were gathered using the GeneCards database. Networks of ginseng-associated targets and depression-related genes were constructed through STRING database. Potential targets and pathway enrichment analysis related to the therapeutic efficacy of ginseng for depression were identified using Cytoscape and Database for Annotation, Visualization and Integrated Discovery (DAVID). Results: Network pharmacological analysis of ginseng in treatment of depression identified 16 active ingredients, 47 potential targets, 32 GO terms, and 8 target gene-regulated major pathways. Among them, kaempferol, beta-sitosterol, stigmasterol, fumarine and frutinone A are bioactive compounds and key chemicals. Core genes in PPI network were AKT1, CASP3, NOS3, TNF, and PPARG. Enrichment results revealed that ginseng could regulate multiple aspects of depression through neuroactive ligand-receptor interaction, HIF-1 signaling pathway, and Serotonergic synapse. More importantly, we found that frutinone A and kaempferol are key ingredients in ginseng with dual activities of immune-regulation and anti-depression. Conclusions: We discovered that the therapeutic activities of ginseng for depression mainly involve neurotransmitters, neurotrophic factors, neurogenesis, HPA axis and inflammatory response. Pharmacological network analysis can help to explain the potential effects of ginseng for treating depression, indicating that ginseng is a preferable herb clinically for immune-regulation and anti-depression in post-pandemic.

scholarly journals Study on the mechanism of Erzhi Pill in the treatment of breast cancer based on network pharmacology

2021 ◽  
Vol 245 ◽  
pp. 03055
Author(s):  
Fahu Yuan ◽  
Xinghua Liao ◽  
Tongcun Zhang
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Suppressor Gene ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Annotation Database ◽  
Amino Terminal ◽  
Target Network

Objective: To explore the possible mechanism of Erzhi Pill in the treatment of breast cancer based on network pharmacology. Methods: Through systematic pharmacology database and analysis platform of Traditional Chinese medicine (TCMSP) and literature review, the candidate active ingredients and corresponding targets of Erzhi Pill were retrieved and collected. The UniProt database and the Human Genome Annotation Database (Genecards) were used to compare the results, and the potential target genes were obtained for the coincidence of Erzhi Pill and breast cancer. Cytoscape was used to construct the “candidate component - action target” network of Erzhi Pill. Generate Style from Statistics tool in String database and Cytoscape software was combined to construct protein interaction network.The Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway enrichment analysis and GO classification enrichment analysis for targets of Erzhi Pill were conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID ) bioinformation resource Database. Results: A total of 21 candidate active components, including Beta-sitosterol, Quercetin, Luteolin, Demethylwedelolactone, Kaempferol and so on, were screened from Erzhi Pill, corresponding to 158 target genes, including vascular endothelial growth factor (VEGF), amino-terminal kinase (C-Jun), proto-oncogene (C-MYC), matrix metalloproteinase-9 (MMP-9), and mainly involved in TNF-α, phosphatidylinositol-3-kinase/protein kinase B(PI3K/Akt), tumor suppressor gene p53, toll-like receptor family and other signaling pathways. Conclusion: This study predicted the possible mechanism of action of Erzhi Pill in the treatment of breast cancer based on the method of network pharmacology, and provided a direction for further research.

scholarly journals Predicting the Molecular Mechanism of Sini Jia Renshen Decoction in Treating Severe COVID-19 Patients Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (12) ◽  
pp. 1934578X2110592
Author(s):  
Yi Wen Liu ◽  
Ai Xia Yang ◽  
Li Lu ◽  
Tie Hua Huang
Keyword(s):  
Molecular Docking ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interactions ◽  
Active Ingredients ◽  
Active Compounds ◽  
Pathway Network ◽  
Function Enrichment Analysis

Objective: To explore the potential mechanism of Sini jia Renshen Decoction (SJRD) in the treatment of COVID-19 based on network pharmacology and molecular docking. Methods: The active compounds and potential therapeutic targets of SJRD were collected through the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). Then a string database was used to build a protein–protein interactions (PPI) network between proteins, and use the David database to perform gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on core targets. Then we used Cytoscape software to construct an active ingredients-core target-signaling pathway network, and finally the active ingredients of SJRD were molecularly docked with the core targets to predict the mechanism of SJRD in the treatment of COVID-19. Results: A total of 136 active compounds, 51 core targets and 93 signaling pathways were selected. Molecular docking results revealed that quercetin, 3,22-dihydroxy-11-oxo-delta(12)-oleanene-27-alpha-methoxycarbonyl-29-oic acid, 18α-hydroxyglycyrrhetic acid, gomisin B and ignavine had considerable binding ability with ADRB2, PRKACA, DPP4, PIK3CG and IL6. Conclusions: This study preliminarily explored the mechanism of multiple components，multiple targets，and multiple pathways of SJRD in the treatment of COVID-19 by network pharmacology．

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.

scholarly journals Deciphering Pharmacological Mechanism of Buyang Huanwu Decoction for Spinal Cord Injury by Network Pharmacology Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Zhencheng Xiong ◽  
Feng Yang ◽  
Wenhao Li ◽  
Xiangsheng Tang ◽  
Haoni Ma ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Molecular Docking ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Buyang Huanwu Decoction ◽  
Active Compounds ◽  
Cord Injury

Objective. The purpose of this study was to investigate the mechanism of action of the Chinese herbal formula Buyang Huanwu Decoction (BYHWD), which is commonly used to treat nerve injuries, in the treatment of spinal cord injury (SCI) using a network pharmacology method. Methods. BYHWD-related targets were obtained by mining the TCMSP and BATMAN-TCM databases, and SCI-related targets were obtained by mining the DisGeNET, TTD, CTD, GeneCards, and MalaCards databases. The overlapping targets of the abovementioned targets may be potential therapeutic targets for BYHWD anti-SCI. Subsequently, we performed protein-protein interaction (PPI) analysis, screened the hub genes using Cytoscape software, performed Gene Ontology (GO) annotation and KEGG pathway enrichment analysis, and finally achieved molecular docking between the hub proteins and key active compounds. Results. The 189 potential therapeutic targets for BYHWD anti-SCI were overlapping targets of 744 BYHWD-related targets and 923 SCI-related targets. The top 10 genes obtained subsequently included AKT1, IL6, MAPK1, TNF, TP53, VEGFA, CASP3, ALB, MAPK8, and JUN. Fifteen signaling pathways were also screened out after enrichment analysis and literature search. The results of molecular docking of key active compounds and hub target proteins showed a good binding affinity for both. Conclusion. This study shows that BYHWD anti-SCI is characterized by a multicomponent, multitarget, and multipathway synergy and provides new insights to explore the specific mechanisms of BYHWD against SCI.

scholarly journals Predicting the Molecular Mechanism of Shenling Baizhu San in Treating Convalescent Patients With COVID-19 Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (10) ◽  
pp. 1934578X2110460
Author(s):  
Ying Zhang ◽  
Li Lu ◽  
YiWen Liu ◽  
AiXia Yang ◽  
Yanfang Yang
Keyword(s):  
Molecular Docking ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Binding Energies ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interactions ◽  
Active Ingredients ◽  
Active Components ◽  
Pathway Network

Objective: Shenling Baizhu San (SBS) was selected as the regimen for the treatment of COVID-19 in Guangdong Province. It is mainly used for the convalescent treatment of COVID-19 patients with deficiency of both lung and spleen. In this study, we aimed to explore the mechanism of SBS in the treatment of COVID-19 through network pharmacology combined with molecular docking. Methods: The targets of active components of SBS were collected through Traditional Chinese Medicine Systems Pharmacology (TCMSP) and ETCM databases. Using the Genecards, TTD, OMIM and other databases, the targets of COVID-19 were determined. The next step was to use a string database to build a protein–protein interactions (PPI) network between proteins, and use David database to perform gene ontology (GO) function enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on core targets. Then we used Cytoscape software to construct the active ingredients-core target-signaling pathway network, and finally the active ingredients of SBS were molecularly docked with the core targets to predict the mechanism of SBS in the treatment of COVID-19. Results: A total of 177 active compounds, 43 core targets and 58 signaling pathways were selected. Molecular docking results showed that the binding energies of the top six active components and the targets were all less than −5 kcal/MOL. Conclusion: The potential mechanism of action of SBS in the treatment of COVID-19 may be associated with the regulation of genes co-expressed with IL6, DPP4, PTGS2, PTGS1 and TNF.

scholarly journals Molecular mechanism underlying the hypolipidemic effect of Shanmei Capsule based on network pharmacology and molecular docking

2021 ◽  
Vol 29 ◽  
pp. 239-256
Author(s):  
Qian Wang ◽  
Lijing Du ◽  
Jiana Hong ◽  
Zhenlin Chen ◽  
Huijian Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Kegg Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Hypolipidemic Effect ◽  
Active Ingredients ◽  
Pathway Enrichment

BACKGROUND: Shanmei Capsule is a famous preparation in China. However, the related mechanism of Shanmei Capsule against hyperlipidemia has yet to be revealed. OBJECTIVE: To elucidate underlying mechanism of Shanmei Capsule against hyperlipidemia through network pharmacology approach and molecular docking. METHODS: Active ingredients, targets of Shanmei Capsule as well as targets for hyperlipidemia were screened based on database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed via Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 database. Ingredient-target-disease-pathway network was visualized utilizing Cytoscape software and molecular docking was performed by Autodock Vina. RESULTS: Seventeen active ingredients in Shanmei Capsule were screened out with a closely connection with 34 hyperlipidemia-related targets. GO analysis revealed 40 biological processes, 5 cellular components and 29 molecular functions. A total of 15 signal pathways were enriched by KEGG pathway enrichment analysis. The docking results indicated that the binding activities of key ingredients for PPAR-α are equivalent to that of the positive drug lifibrate. CONCLUSIONS: The possible molecular mechanism mainly involved PPAR signaling pathway, Bile secretion and TNF signaling pathway via acting on MAPK8, PPARγ, MMP9, PPARα, FABP4 and NOS2 targets.

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