scholarly journals Network Pharmacology‐Based Study on the Active Component and Mechanism of the Anti-Gastric-Cancer Effect of Herba Sarcandrae

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Li Han ◽  
Ying Han
Keyword(s):  
Gastric Cancer ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Target Genes ◽  
Scientific Basis ◽  
Gene Expression Omnibus ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Pathway Network

Background. Herba Sarcandrae is used in the clinical practice of traditional Chinese medicine to deal with gastric cancer. However, there are few studies on its precise mechanism. Method. In this study, a network pharmacological approach was utilized to construct a molecular/target/pathway molecular regulatory network for the anti-gastric-cancer effect of Herba Sarcandrae. The active components of Herba Sarcandrae and their potential mechanisms were explored. Chemical components of the Herba Sarcandrae were identified through a database, and they were evaluated and screened based on oral bioavailability and drug similarity. Results. Genes related to gastric cancer were found in the Gene Expression Omnibus (GEO) database, and gene targets related to anti-gastric-cancer were chosen by comparison. Using annotation, visualization, and a comprehensive discovery database, the function and related pathways of target genes were analyzed and screened. Cytoscape software was utilized to construct a component/target/pathway network for the antitumor effect of Herba Sarcandrae. Finally, 6 drug ingredients and 29 target genes related to gastric cancer were detected. IL-17 signaling pathway, NF-kappa B signaling pathway, and other signaling pathways were significantly enriched. Many signaling pathways that directly act on tumors and indirect pathways inhibit the development of gastric cancer. Conclusion. This study provides a scientific basis for further elucidating the mechanism of the anti-gastric-cancer effect of Herba Sarcandrae.

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

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.

scholarly journals Investigation of Active Ingredients and Mechanism of Sanao Decoction in the Treatment of Chronic Cough by Network Pharmacology

2020 ◽  
Author(s):  
Mengke Sheng ◽  
Xing Liu ◽  
Qingsong Qu ◽  
Xiaowen Wu ◽  
Yuyao Liao ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Chronic Cough ◽  
Fluid Shear Stress ◽  
Oxidant Stress ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Ingredients ◽  
Active Components ◽  
Pathway Network

Abstract Background: Chronic cough significantly affects human health and quality of life. Studies have shown that Sanao Decoction（SAD）can clinically treat chronic cough. To investigate its mechanisms, we used the method of network pharmacology to conduct research at the molecular level.Methods: The active ingredients and their targets were screened by pharmacokinetics parameters from the traditional Chinese medicine system pharmacology analysis platform (TCMSP). The relevant targets of chronic cough were obtained from two databases: GeneCards and DrugBank. Take the intersection to get potential targets of SAD to treat chronic cough and establish the component-target regulatory network by CytoScape3.7.2 and protein-protein interaction (PPI) network by STRING 1.0. The function of the target gene and related pathways were analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) in the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The significant pathways and their relevant targets were obtained and the target-pathway network was established by CytoScape3.7.2. Finally, molecular docking of the core active components and relevant targets was performed.Results: A total of 98 active components, 113 targets were identified. The component-target and target-pathway network of SAD and PPI network were established. Enrichment analysis of DAVID indicated that 2062 terms were in biological processes, 77 in cellular components, 142 in molecular functions and 20 significant pathways. In addition, the molecular docking showed that quercetin and luteolin had a good combination with the corresponding targets.Conclusions: It indicates that the active compounds of SAD, such as quercetin, luteolin, may act on AKT1, MAPK1, RELA, EGFR, BCL2 and regulate PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetic complications and Fluid shear stress and atherosclerosis pathway to exert the effects of anti-inflammatory, anti-airway remodeling, anti-oxidant stress and repair airway damage to treat chronic cough.

scholarly journals Network pharmacology based research into the effect and mechanism of Yinchenhao Decoction against Cholangiocarcinoma

2021 ◽  
Author(s):  
Zhiqiang Chen ◽  
Tong Lin ◽  
Xiaozhong Liao ◽  
Zeyun Li ◽  
Ruiting Lin ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Experimental Results ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Active Components ◽  
Active Compounds ◽  
Apoptosis Rate

Abstract Background: Cholangiocarcinoma refers to an epithelial cell malignancy with poor prognosis. Yinchenhao decoction (YCHD) showed positive effects on cancers, and associations between YCHD and cholangiocarcinoma remain unclear. This study aimed to screen out the effective active components of Yinchenhao decoction (YCHD) using network pharmacology, estimate their potential targets, screen out the pathways, as well as delve into the potential mechanisms on treating cholangiocarcinoma. Methods: By the traditional Chinese medicine system pharmacology database and analysis platform (TCMSP) as well as literature review, the major active components and their corresponding targets were estimated and screened out. Using the software Cytoscape 3.6.0, a visual network was established using the active components of YCHD and the targets of cholangiocarcinoma. Based on STRING online database, the protein interaction network of vital targets was built and analyzed. With the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server, the gene ontology (GO) biological processes and the Kyoto encyclopedia of genes and genomes (KEGG) signaling pathways of the targets enrichment were performed. The AutoDock Vina was used to perform molecular docking and calculate the binding affinity. The PyMOL software was utilized to visualize the docking results of active compounds and protein targets. In vivo experiment, the IC50 values and apoptosis rate in PI-A cells were detected using CCK-8 kit and Cell Cycle Detection Kit. The predicted targets were verified by the real-time PCR and western blot methods. Results: 32 effective active components with anti-tumor effects of YCHD were sifted in total, covering 209 targets, 96 of which were associated with cancer. Quercetin, kaempferol, beta-sitosterol, isorhamnetin, and stigmasterol were identified as the vital active compounds, and AKT1, IL6, MAPK1, TP53 as well as VEGFA were considered as the major targets. The molecular docking revealed that these active compounds and targets showed good binding interactions. These 96 putative targets exerted therapeutic effects on cancer by regulating signaling pathways (e.g., hepatitis B, the MAPK signaling pathway, the PI3K-Akt signaling pathway, and MicroRNAs in cancer). Our in vivo experimental results confirmed that YCHD showed therapeutic effects on cholangiocarcinoma by decreasing IC50 values, down-regulating apoptosis rate of cholangiocarcinoma cells, and lowering protein expressions. Conclusion:As predicted by network pharmacology strategy and validated by the experimental results, YCHD exerts anti-tumor effectsthrough multiple components, targets, and pathways, thereby providing novel ideas and clues for the development of preparations and the treatment of cholangiocarcinoma.

scholarly journals Network Pharmacology-Based Strategy Reveals the Effects of Hedysarum multijugum Maxim.-Radix Salviae Compound on Oxidative Capacity and Cardiomyocyte Apoptosis in Rats with Diabetic Cardiomyopathy

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Shiying Zhang ◽  
Zhiying Yuan ◽  
Huaying Wu ◽  
Weiqing Li ◽  
Liang Li ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Diabetic Cardiomyopathy ◽  
Ion Homeostasis ◽  
Oxidative Capacity ◽  
Cardiomyocyte Apoptosis ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Active Components

Objective. To explore the effects of the Hedysarum multijugum Maxim.-Radix Salviae compound (Huangqi-Danshen Compound (HDC)) on oxidative capacity and cardiomyocyte apoptosis in rats with diabetic cardiomyopathy by a network pharmacology-based strategy. Methods. Traditional Chinese Medicine (TCM)@Taiwan, TCM Systems Pharmacology Database and Analysis Platform (TCMSP), TCM Integrated Database (TCMID), and High-Performance Liquid Chromatography (HPLC) technology were used to obtain and screen HDC’s active components, and the PharmMapper database was used to predict HDC human target protein targets. The DCM genes were collected from the GeneCards and OMIM databases, and the network was constructed and analyzed by Cytoscape 3.7.1 and the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Finally, HDC was used to intervene in diabetic cardiomyopathy (DCM) model rats, and important biological processes and signaling pathways were verified using techniques such as immunohistochemistry. Results. A total of 176 of HDC’s active components and 442 potential targets were obtained. The results of network analysis show that HDC can regulate DCM-related biological processes (such as negative regulation of the apoptotic process, response to hypoxia, the steroid hormone-mediated signaling pathway, cellular iron ion homeostasis, and positive regulation of phosphatidylinositol 3-kinase signaling) and signaling pathways (such as the HIF-1 signaling pathway, the estrogen signaling pathway, insulin resistance, the PPAR signaling pathway, the VEGF signaling pathway, and the PI3K-Akt signaling pathway). Animal experiments show that HDC can reduce fasting plasma glucose (FPG), HbA1c, and malondialdehyde (MDA) and increase superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) ( P < 0.05 ). The results of immunohistochemistry showed that HDC can regulate the protein expression of apoptosis-related signaling pathways in DCM rats ( P < 0.05 ). Conclusion. It was initially revealed that HDC improves DCM through its antiapoptotic and anti-inflammatory effects. HDC may play a therapeutic role by improving cardiomyocyte apoptosis in DCM rats.

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

2021 ◽  
Vol 16 (2) ◽  
pp. 1934578X2199171
Author(s):  
ZiXin Yuan ◽  
Can Zeng ◽  
Bing Yu ◽  
Ying Zhang ◽  
TianShun Wang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Hypoxia Inducible Factor ◽  
Growth Factor Receptor ◽  
Interaction Network ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Discovery Studio

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.

scholarly journals Mechanism of Tripterygium Wilfordii for the Treatment of Idiopathic Membranous Nephropathy Based on Network Pharmacology

2021 ◽  
Author(s):  
Honghong Shi ◽  
Yanjuan Hou ◽  
Xiaole Su ◽  
Jun Qiao ◽  
Qian Wang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Protein Interactions ◽  
Membranous Nephropathy ◽  
Target Genes ◽  
Experimental Studies ◽  
Idiopathic Membranous Nephropathy ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Tripterygium Wilfordii ◽  
Active Components

Abstract Background Tripterygium wilfordii has been widely used for idiopathic membranous nephropathy (IMN), while the pharmacological mechanisms are still unclear. This study is aimed at revealing potential therapeutic targets and pharmacological mechanism of tripterygium wilfordii for the treatment of IMN based on network pharmacology. Methods Active components of tripterygium wilfordii were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. IMN-associated target genes were collected from GeneCards database, DisGeNET database, and OMIMI database. VENNY 2.1 was used to identify the overlapping genes between active compounds of tripterygium wilfordii and IMN target genes. Using STRING database and Cytoscape 3.7.2 software to analyze interactions among overlapping genes. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment of the targets were analyzed using the Rx64 4.0.2 software, colorspace, stringi, DOSE, clusterProfiler, and enrichplot packages. Results A total of 153 compounds-related genes, 1485 IMN-related genes were obtained, and 77 overlapping genes between them were identified. The protein–protein interactions network indicated that the targets AKT1, TNF, VEGFA, TP53, PTGS2, CXCL8, MAPK8, STAT3, JUN, and CASP3 play an important role in the treatment effect of tripterygium wilfordii for IMN. The enrichment analysis showed that the main pathways of targets were AGE signaling pathway, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway. Conclusion This study reveals potential mechanisms of multi-component and multi-target of tripterygium wilfordii for the treatment of IMN based on network pharmacologic approach, and provide a scientific basis for further experimental studies.

scholarly journals Investigating the Mechanisms of Pollen Typhae in the Treatment of Diabetic Retinopathy Based on Network Pharmacology and Molecular Docking

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Rongrong Zhou ◽  
De Jin ◽  
Yuqing Zhang ◽  
Liyun Duan ◽  
Yuehong Zhang ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Network Pharmacology ◽  
Docking Analysis ◽  
Pathway Network ◽  
Gene Pathway ◽  
Vegf Signaling ◽  
Vegf Signaling Pathway

Objective. To explore the main bioactive compounds and investigate the underlying mechanism of Pollen Typhae (PT) against diabetic retinopathy (DR) by network pharmacology and molecular docking analysis. Methods. Bioactive ingredients and the target proteins of PT were obtained from TCMSP, and the related target genes were acquired from the SwissTargetPrediction database. The target genes of DR were obtained from GeneCards, TTD database, DisGeNET database, and DrugBank. The compound-target interaction network was established based on Cytoscape 3.7.2. The protein-protein interaction (PPI) network was constructed via STRING database and Cytoscape 3.7.2. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were visualized through DAVID database and Bioinformatics. Ingredient-gene-pathway network analysis was conducted to further screen the ingredients, target proteins, and pathways closely related to the biological mechanism on PT for DR, and molecular docking analysis was performed by SYBYL-X 2.1.1 software. Finally, the mechanism and underlying targets of PT in the treatment of DR were predicted. Results. A total of 8 compounds and 171 intersection targets were obtained based on the online network database. 7 main compounds were screened from compound-target network, and 53 targets including the top six key targets (PTGS2, AKT1, VEGFA, MAPK3, TNF, and EGFR) were further acquired from PPI analysis. The 53 key targets covered 80 signaling pathways, among which PI3K-Akt signaling pathway, focal adhesion, Rap1 signaling pathway, VEGF signaling pathway, and HIF-1 signaling pathway were closely connected with the biological mechanism involved in the alleviation of DR by PT. Ingredient-gene-pathway network shows that AKTI, EGFR, and VEGFA were core genes, kaempferol and isorhamnetin were pivotal ingredients, and VEGF signaling pathway and Rap1 signaling pathway were closely involved in anti-DR. The docking results indicated that five main compounds (arachidonic acid, isorhamnetin, quercetin, kaempferol, and (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one) had good binding activity with EGFR and AKT1 targets. Conclusion. The active ingredients in PT may regulate the levels of inflammatory factors, suppress the oxidative stress, and inhibit the proliferation, migration, and invasion of retinal pericytes by acting on PTGS2, AKT1, VEGFA, MAPK3, TNF, and EGFR targets through VEGF signaling pathway, PI3K-Akt signaling pathway, Rap1 signaling pathway, and HIF-1 signaling pathway to play a therapeutic role in diabetic retinopathy.

Network Pharmacology Analysis of Molecular Mechanism of Curcuma Longa L. extracts Regulating Glioma Immune Inflammatory Factors: Implications for Precise Cancer Treatment

2021 ◽  
Vol 21 ◽  
Author(s):  
Hui Li ◽  
Yongwei Li
Keyword(s):  
Cell Differentiation ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Curcuma Longa ◽  
Interleukin 4 ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Regulatory Pathway ◽  
Active Components ◽  
The Common

Introduction: : Curcuma longa L. has been associated with different antioxidant, anti-inflammatory, bactericidal and anticancer effects, but the mechanisms of the effects are not yet clearly understood. This study aimed to investigate the key targets and the effect of potential molecular mechanisms of Curcuma longa L. extracts on glioma using different network pharmacology analysis approaches. Methods: The components of Curcuma longa were extracted by gas chromatography-mass spectrometry (GC-MS), and the active components related to the occurrence and development of glioma were determined by traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) database, and the same targets of the active components and glioma were screened by network pharmacology approach. Then, the protein’s function and regulatory pathway of the common targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The protein’s action and regulatory pathway of the common targets were analyzed with the Cytoscape package using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database to construct the target interaction network through which the key targets were identified. Results : GC-MS combined with TCMSP database was used to identify the active components related to the occurrence and development of glioma in Curcuma longa. Finally, we identified the active components 1-(1,5-Dimethyl-4-hexenyl)-4-methyl benzene and Zingiberene. At the same time, 190 target genes of Curcuma longa extracts on glioma were obtained using the Venn diagram. The results of GO analysis showed that the biological processes involved included a response to stimulation, metabolic process, inflammatory process, cell differentiation, and regulation of biological processes. KEGG analysis showed that the PI3K-Akt signaling pathway, MAPK signaling pathway, Th17 cell differentiation, and proteoglycan pathway might be involved in cancer. Further analyses showed that the IL-17 signaling pathway and Interleukin-4 and interleukin-13 signaling were involved in the inflammatory pathway. The analysis of key nodes showed that GSK3B, MAPK14, HSP90AA1, MAPK3 and MAPK8 were IL-17 signaling pathways, while HIF1A and JAK3 were Interleukin-4 and interleukin-13 signaling pathways. Conclusion: Curcuma longa extracts can regulate the occurrence and development of glioma by regulating the immune-inflammatory responses.

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

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.

scholarly journals Application of Network Pharmacology to Elucidate The Potential Mechanism of Finger Citron Against Obesity

2020 ◽  
Author(s):  
Zhen Wu ◽  
Yujiao Yang ◽  
Yao Wei ◽  
Xu-guang Hu
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Active Components ◽  
Docking Analysis ◽  
Treatment Of Obesity ◽  
Molecular Docking Analysis

Abstract Background: Finger citron (FS) is one of many traditional Chinese herbs that have been used to treat obesity. However, the active components and potential targets of FS in improving obesity remain unclear. Methods：The aim of this study was to elucidate the pharmacological effects and mechanisms of FS on obesity using network pharmacology analysis. We used network pharmacology to determine the active components, potential targets and mechanisms in the treatment of obesity.Results：We identified 25 active ingredients of FS such as diosmetin, hesperidin and sitosterol-alpha1 with important biological effect. A total of 258 key targets were screened, containing TNF，NOS2, MAPK8 which were found to be enriched in 27 signaling pathways, such as apoptosis, TNF, PPAR and AKT1, and Insulin resistance signaling pathways. Moreover, molecular docking analysis showed that the main ingredients were tightly bound to the core targets, further confirming the effects of weight loss. Conclusion: Based on network pharmacology and molecular docking analysis, our study provides insights into the potential mechanism of FS in ameliorating obesity after screening for associated key target genes and signaling pathways. These findings further provide a theoretical basis for further pharmacological research into the potential mechanism of FS in treating obesity.

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