scholarly journals Network Pharmacology-Based Investigation of the Mechanism of Action of Plantaginis Herba in Hyperuricemia Treatment

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Rong Tang ◽  
Xiaoqing Peng ◽  
Yan Wang ◽  
Xiaohong Zhou ◽  
Hong Liu
Keyword(s):  
Signaling Pathways ◽  
Enrichment Analysis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Ingredients ◽  
Bioinformatics Analyses ◽  
Network Construction ◽  
Kegg Analysis ◽  
Underlying Mechanisms

This study used a network pharmacology approach to investigate the potential active ingredients of Plantaginis Herba and its underlying mechanisms in hyperuricemia treatment. The potential active ingredients of Plantaginis Herba were obtained from TCMSP and ETCM databases, and the potential targets of the active ingredients were predicted using the Swiss TargetPrediction database. The potential therapeutic targets of hyperuricemia were retrieved from the GeneCards, DisGeNET, and Online Mendelian Inheritance in Man (OMIM) databases. Then, the integrative bioinformatics analyses of candidates were performed by GO analysis, KEGG analysis, and PPI network construction. There were 15 predicted active ingredients in Plantaginis Herba and 41 common targets that may be involved in the treatment of hyperuricemia. A total of 61 GO annotations and 35 signaling pathways were identified by enrichment analysis ( P < 0.01 ). The underlying mechanisms of Plantaginis Herba may be related to insulin resistance, PI3K/AKT, TNF, VEGF, AMPK, and glucagon signaling pathways. Thus, the present study provided potential and promising strategies of Plantaginis Herba for hyperuricemia treatment.

scholarly journals A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Artemisia annua on the Treatment of Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-9 ◽  
Author(s):  
Shuqiao Zhang ◽  
Zhuomao Mo ◽  
Shijun Zhang ◽  
Xinyu Li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Signaling Pathway ◽  
Tumor Invasion ◽  
Artemisia Annua ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Invasion And Metastasis ◽  
Active Ingredients ◽  
Underlying Mechanisms

Objective. To investigate the potential active ingredients and underlying mechanisms of Artemisia annua (AA) on the treatment of hepatocellular carcinoma (HCC) based on network pharmacology. Methods. In the present study, we used a network pharmacological method to predict its underlying complex mechanism of treating HCC. First, we obtained relative compounds of AA based on the traditional Chinese medicine systems pharmacology (TCMSP) database and collected potential targets of these compounds by target fishing. Then, we built HCC-related targets target by the oncogenomic database of hepatocellular carcinoma (OncoDB.HCC) and biopharmacological network (PharmDB-K) database. Based on the matching results between AA potential targets and HCC targets, we built a protein-protein interaction (PPI) network to analyze the interactions among these targets and screen the hub targets by topology. Furthermore, the function annotation and signaling pathways of key targets were performed by Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis using DAVID tools. Finally, the binding capacity between active ingredients and key targets was validated by molecular docking. Results. A total of 19 main active ingredients of AA were screened as target prediction; then, 25 HCC-related common targets were seeked out via multiple HCC databases. The areas of nodes and corresponding degree values of EGFR, ESR1, CCND1, MYC, EGF, and PTGS2 were larger and could be easily found in the PPI network. Furthermore, GO and KEGG enrichment analysis showed that these key targets were significantly involved in multiple biological processes and pathways which participated in tumor cell proliferation, apoptosis, angiogenesis, tumor invasion, and metastasis to accomplish the anti-HCC activity. The molecular docking analysis showed that quercetin could stably bind to the active pocket of EGFR protein 4RJ5 via LibDock. Conclusion. The anticancer effects of AA on HCC were predicted to be associated with regulating tumor cell proliferation, apoptosis, angiogenesis, tumor invasion, and metastasis via various pathways such as the EGFR signaling pathway, ESR1 signaling pathway, and CCND1 signaling pathway. It is suggested that AA might be developed as a broad-spectrum antitumor drug based on its characteristics of multicomponent, multipath, and multitarget.

scholarly journals Network Pharmacology-Based Systematic Analysis of Molecular Mechanisms of Dingji Fumai Decoction for Ventricular Arrhythmia

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yi Liang ◽  
Bo Liang ◽  
Xin-Rui Wu ◽  
Wen Chen ◽  
Li-Zhi Zhao
Keyword(s):  
Molecular Docking ◽  
Ventricular Arrhythmia ◽  
Molecular Mechanisms ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Systematic Analysis ◽  
Chemical Structures ◽  
Function Modules ◽  
Underlying Mechanisms

Background. Dingji Fumai Decoction (DFD), a traditional herbal mixture, has been widely used to ventricular arrhythmia (VA) in clinical practice in China. However, research on the bioactive components and underlying mechanisms of DFD in VA is still scarce. Methods. Components of DFD were collected from TCMSP, ETCM, and literature. The chemical structures of each component were obtained from PubChem. Next, SwissADME and SwissTargetPrediction were applied for compounds screening and targets prediction of DFD; meanwhile, targets of VA were collected from DrugBank and Online Mendelian Inheritance in Man (OMIM). Then, the H-C-T-D network and the protein-protein interaction (PPI) network were constructed based on the data obtained above. CytoNCA was utilized to filter hub genes and VarElect was used to analyze the relationship between genes and diseases. At last, Metascape was employed for systematic analysis on the potential targets of herbals against VA, and AutoDock was applied for molecular docking to verify the results. Results. A total of 434 components were collected, 168 of which were qualified, and there were 28 shared targets between DFD and VA. Three function modules of DFD were found from the PPI network. Further systematic analysis of shared genes and function modules explained the potential mechanism of DFD in the treatment of VA; molecular docking has verified the interactions. Conclusions. DFD could be employed for VA through mechanisms, including complex interactions between related components and targets, as predicted by network pharmacology and molecular docking. This work confirmed that DFD could apply to the treatment of VA and promoted the explanation of DFD for VA in the molecular mechanisms.

scholarly journals The Active Compounds and Therapeutic Mechanisms of Pentaherbs Formula for Oral and Topical Treatment of Atopic Dermatitis Based on Network Pharmacology

Plants ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1166
Author(s):  
Man Chu ◽  
Miranda Sin-Man Tsang ◽  
Ru He ◽  
Christopher Wai-Kei Lam ◽  
Zhi Bo Quan ◽  
...  
Keyword(s):  
Atopic Dermatitis ◽  
Signaling Pathways ◽  
Topical Treatment ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Docking Analysis ◽  
Protein Protein Interaction

To examine the molecular targets and therapeutic mechanism of a clinically proven Chinese medicinal pentaherbs formula (PHF) in atopic dermatitis (AD), we analyzed the active compounds and core targets, performed network and molecular docking analysis, and investigated interacting pathways. Information on compounds in PHF was obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and target prediction was performed using the Drugbank database. AD-related genes were gathered using the GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. Network analysis was performed by Cytoscape software and protein-protein interaction was analyzed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). The Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources were applied for the enrichment analysis of the potential biological process and pathways associated with the intersection targets between PHF and AD. Autodock software was used to perform protein compound docking analysis. We identified 43 active compounds in PHF associated with 117 targets, and 57 active compounds associated with 107 targets that form the main pathways linked to oral and topical treatment of AD, respectively. Among them, quercetin, luteolin, and kaempferol are key chemicals targeting the core genes involved in the oral use of PHF against AD, while apigenin, ursolic acid, and rosmarinic acid could be used in topical treatment of PHF against AD. The compound–target–disease network constructed in the current study reveals close interactions between multiple components and multiple targets. Enrichment analysis further supports the biological processes and signaling pathways identified, indicating the involvement of IL-17 and tumor necrosis factor signaling pathways in the action of PHF on AD. Our data demonstrated the main compounds and potential pharmacological mechanisms of oral and topical application of PHF in AD.

Analysis of Herbal Mechanisms and Prescriptions for Chronic Cerebral Circulatory Insufficiency Based on Data Mining and Network Pharmacology

2021 ◽  
Vol 24 ◽  
Author(s):  
Ying Yu ◽  
Gong Zhang ◽  
Tao Han ◽  
Hai-liang Huang
Keyword(s):  
Signaling Pathways ◽  
Target Genes ◽  
Herbal Medicines ◽  
Circulatory System ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Hormone Regulation ◽  
Active Ingredients ◽  
The Core ◽  
Circulatory Insufficiency

Background: Traditional Chinese medicine has accumulated rich resources and experience through clinical research to explore the prevention and treatment of chronic cerebral circulatory insufficiency, but current medicine lacks in-depth research and confirmation on the established protocols and mechanism of prescribed TCMs at the macro and micro levels. Objective: To explore the prescription of Chinese medicines for the treatment of chronic cerebral circulation insufficiency (CCCI) and to explore the mechanism of core drugs. Methods: 229 Chinese prescriptions for CCCI were collected from CNKI, CBM, VIP and WANFANG databases. Analyze the frequency and association rules of drugs and to extract the core drugs by TCMISSV2.5 software. The active ingredients and targets were obtained by TCMSP, and genes of CCCI were collected from the DisGeNET, OMIM, DrugBank disease databases. The intersection targets of herbal medicine and disease was imported into the STRING database for PPI network. The key targets were screened by network topology algorithm. The Systems Dock website was used to verify the molecular docking. The GOEAST and DAVID tools were used to perform GO and KEGG pathway analysis with the key target genes. Results: 117 drugs involved in 229 prescriptions were identified, 2 core drugs were identified. We identified 8 active ingredients, which were mandenol, myricanone, perlolyrine, senkyunone, wallichilide, sitosterol, beta-sitosterol and stigmasterol. 371 herbal targets predicted and 335 disease targets. The enrichment analysis showed that the core herbal medicines could prevent CCCI by 15 key signaling pathways. Conclusion: There are direct or indirect connections in key signaling pathways, which not only participate in energy metabolism, hormone regulation, signal transduction, but also play a role in the comprehensive intervention of nervous system, immune system, circulatory system and other systems, which is consistent with the comprehensive pathogenesis of CCCI induced by multiple factors.

scholarly journals A Network Pharmacology Technique to Investigate the Synergistic Mechanisms of Salvia miltiorrhiza and Radix puerariae in Treatment of Cardio-Cerebral Vascular Diseases

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Yang Ma ◽  
Wenjun Wang ◽  
Jiani Yang ◽  
Sha Zhang ◽  
Zhe Li ◽  
...  
Keyword(s):  
Drug Targets ◽  
Salvia Miltiorrhiza ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Radix Puerariae ◽  
Cerebral Vascular

Objective. This study is aimed to analyze the active ingredients, drug targets, and related pathways in the combination of Salvia miltiorrhiza (SM) and Radix puerariae (RP) in the treatment of cardio-cerebral vascular diseases (CCVDs). Method. The ingredients and targets of SM and RP were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the disease targets were obtained from Therapeutic Target Database (TTD), National Center for Biotechnology Information (NCBI), and Online Mendelian Inheritance in Man (OMIM) Database. The synergistic mechanisms of the SM and RP were evaluated by gene ontology (GO) enrichment analyses and Kyoto encyclopedia of genes and genomes (KEGG) path enrichment analyses. Result. A total of 61 active ingredients and 58 common targets were identified in this study. KEGG pathway enrichment analysis results showed that SM- and RP-regulated pathways were mainly inflammatory processes, immunosuppression, and cardiovascular systems. The component-target-pathway network indicated that SM and RP exert a synergistic mechanism for CCVDs through PTGS2 target in PI3k-Akt, TNF, and Jak-STAT signaling pathways. Conclusion. In summary, this study clarified the synergistic mechanisms of SM and RP, which can provide a better understanding of effect in the treatment of CCVDs.

scholarly journals Network Pharmacological Analysis of Huanglian Jiedu Decoction for Anti- Atherosclerosis

2020 ◽  
Author(s):  
Kerui Wu ◽  
Lu Jiang ◽  
Lanlin Huang ◽  
Yaxing He ◽  
Xia Yan ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Fluid Shear Stress ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Active Ingredients ◽  
Active Components ◽  
Protein Protein Interaction ◽  
Target Regulation

Abstract Objective: We aimed to predict the possible active components,key targets and pathways of Huanglian Jiedu Decoction(HLJDD) for anti-atherosclerosis. Methods: The TCMSP database was searched to obtain the active components and targets of HLJDD, the GeneCards and OMIM databases were searched to obtain related targets of atherosclerosis, and we obtain the intersection targets of them, which are the potential targets of HLJDD for anti-atherosclerosis.Application of Cytoscape 3.6.0 software to build a herbal-active ingredient-potential target regulation network.We perform protein-protein interaction(PPI) network analysis of potential targets through STRING 11.0 database and obtain the key targets,and the results of PPI network of key targets were visualized by Cytoscape3.6.0 software. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the key targets were performed using STRING11.0 database, and we finally constructed the possible pharmacological network of HLJDD for anti-atherosclerosis .Results: We finally obtained 14 key active ingredients of HLJDD, 65 key targets of anti-atherosclerosis, and 14 key active ingredients corresponded to 52 of these targets. These targets are mainly involved in biological processes such as reaction to organic substance, reaction to chemical stimulation,etc.They mainly involved in biological signaling pathways such as pathways in cancer,IL-17 signaling pathway,etc. Conclusion: HLJDD may act on 52 key targets such as PTGS2, HSP90AA1 and RELA through 14 key active ingredients, and influence the signaling pathways including fluid shear stress and atherosclerosis,PI3K-Akt signaling pathway,IL-17 signaling pathway,AGE-RAGE signaling pathway in diabetic complications,TNF signaling pathway,etc.Thus, it may play an anti-atherosclerosis role by inhibiting inflammatory reaction, oxidative stress and improving hemodynamics,etc.

scholarly journals Uncovering the Pharmacological of Xiaochaihu Decoction in the Treatment of Pancreatitis Based on the Network Pharmacology

2020 ◽  
Author(s):  
Lianghui Zhan ◽  
Jinbao Pu ◽  
Yijuan Hu ◽  
Pan Xu ◽  
Weiqing Liang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Pancreatic Neoplasms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Ppi Network ◽  
Kegg Analysis ◽  
Key Genes

Abstract BackgroundXiaochaihu Decoction (XD) was a traditional prescription, has been demonstrated the pharmacodynamic on pancreatitis. But the underline mechanism remained to be explored. Therefore, this study was aimed to combined network pharmacology method and molecular docking technology to demonstrate the potential mechanism of XD treated with pancreatitis.MethodsFirstly, compounds of seven herbs containing XD were collected from TCMSP Database and the putative targets of Pancreatitis were obtained from OMIM, TTD, Genecards Database. Then PPI network was constructed according to the matching results between XD potential targets and pancreatic neoplasms targets. Furthermore, enrichment analysis on GO and KEGG by DAVID utilized bioinformatics resources. Finally, Molecular Docking was performed to simulate the interaction between the active compound of XD and putative targets.ResultsA total of 196 active ingredients and 91 putative targets were selected out. The PPI interaction network analysis demonstrated that Quercetin was the candidate agents and MAPK3, IL-6 and TP53 were the potential targets for the XD treatment of pancreatitis. The KEGG analysis revealed that pathways in cancers, TNF signaling way, MAPK signaling way might play an important role in pancreatitis therapy. And Molecular Docking results showed that Quercetin combined well with MAPK3, IL-6 and TP53.ConclusionThis study illustrated that Quercetin containing in XD might played an important role in pancreatitis therapy by acting the key genes of MPAK3, IL-6 and TP53. And it also provided a strategy to elucidate the mechanisms of Traditional Chinese Medicine (TCM) at the level of network pharmacology.

scholarly journals Uncovering the underlying mechanisms of Compound Yuxingcao Mixture in the treatment of COVID-19 based on network pharmacology

2020 ◽  
Author(s):  
Xiaoyue Chen ◽  
Yongqiang Zhang ◽  
Dongbo Yuan ◽  
Bin Hu ◽  
Guohua Zhu ◽  
...  
Keyword(s):  
Binding Energy ◽  
Inflammatory Responses ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Immune Defense ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Docking Approach ◽  
Underlying Mechanisms ◽  
Novel Coronavirus

Abstract Background and objective: The novel coronavirus named COVID-19 emerged in Wuhan, China in December, 2019 and has spread rapidly in China and around the world. The traditional Chinese medicine Compound Yuxingcao Mixture (CYM) has been recommended in recent editions of the national guideline while the underlying mechanisms are still unclear. In this study, we analyzed the effectiveness and potential mechanisms of CYM on COVID-19 based on network pharmacology and molecular docking approach. Methods: The active ingredients and potential targets of CYM were screened using TCMSP and STITCH databases. Genes related severe acute respiratory syndromes (SARS) and Middle East respiratory syndrome (MERS) were queried on the DisGeNET and MalaCards databases. CYM-COVID-19 common target protein interaction network was established by STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to generate the relative pathways based on KOBAS databases. In addition, the possible binding site of screened compounds were also predicted by Autodock vina software. Results: A total of 103 active ingredients and 205 putative targets were screened from CYM, of which 32 overlapped with the targets of COVID-19 and were considered therapeutic targets. The analysis of the network diagram demonstrated that the CYM activity of ingredients of quercetin, luteolin, β-sitosterol and kaempferol may play a crucial role in treating COVID-19 by regulating TNF, IL-6, IL-1β, etc. The analysis of molecular binding energy showed that β-sitosterol had the lowest binding energy with COVID-19 3CLpro (-8.63 kJ/mol). GO and KEGG enrichment analysis revealed that these targets were closely associated with inflammatory responses and immune defense processes. Conclusion: In summary, our study identified the potential mechanisms and targets of CYM for the prevention of COVID-19, providing directions for further clinical research.

scholarly journals Use of Network Pharmacology to Investigate the Mechanism of the Compound Xuanju Capsule in the Treatment of Rheumatoid Arthritis

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Wenyang Wei ◽  
Wanpeng Lu ◽  
Xiaolong Chen ◽  
Yunfeng Yang ◽  
Mengkai Zheng
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathways ◽  
Active Ingredient ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Ingredients ◽  
Related Disease ◽  
Ppi Networks ◽  
Target Network ◽  
The Common

Objective. To clarify the therapeutic mechanisms of compound Xuanju capsule-treated rheumatoid arthritis (RA) based on network pharmacology tactics. Method. The TCMSP, TCMID and STITCH databases were used to screen the active ingredients and targets in the compound Xuanju capsule; the OMIM, TTD, PharmGKB and GeneCards databases were applied to screen the RA-related disease targets. Then, the obtained targets were imported into Cytoscape 3.7.1 software to construct the active ingredient-target network and the RA-related disease-target network. The active ingredient-target PPI network, the RA-related disease-target PPI network and the common target PPI network were built by using the STRING platform and Cytoscape 3.7.1 software. The GO and KEGG analyses of the common targets were analyzed by using the Metascape and Bioinformatics online tools. Results. A total of 51 active ingredients and 513 corresponding ingredient targets were harvested from the compound Xuanju capsule; 641 RA-related disease targets were obtained. After two PPI networks were constructed and merged, 116 RA-related targets of compound Xuanju capsules were identified and analyzed. 116 RA-related targets of compound Xuanju capsules are mainly involved in the biological processes and molecular functions, such as the cytokine-mediated signaling pathways, the response to lipopolysaccharide and the blood vascular development, the cytokine activity, the cytokine receptor binding and the receptor regulator activity. Furthermore, 116 RA-related targets of compound Xuanju capsules are concentrated in signaling pathways such as the IL-17, TNF, Th17 cell differentiation, Toll receptor and RA signaling pathway. Conclusion. The compound Xuanju capsule had the action characteristics of multiple components, multiple targets, and multiple pathways in the treatment of RA, which might primarily reduce the release of proinflammatory factors (such as IL-6 and TNF-α) and increase the production of anti-inflammatory factors (such as IL-10) by regulating inflammation-related signaling pathways (such as IL-17), thereby alleviating the inflammatory damage and improving the bone tissue repair.

scholarly journals Identification of Key Genes and Pathways in Gefitinib-Resistant Lung Adenocarcinoma using Bioinformatics Analysis

2021 ◽  
Vol 17 ◽  
pp. 117693432110237
Author(s):  
Kailin Mao ◽  
Fang Lin ◽  
Yingai Zhang ◽  
Hailong Zhou
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Signaling Pathways ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Underlying Mechanisms ◽  
Gefitinib Resistance

Gefitinib resistance is a serious threat in the treatment of patients with non-small cell lung cancer (NSCLC). Elucidating the underlying mechanisms and developing effective therapies to overcome gefitinib resistance is urgently needed. The differentially expressed genes (DEGs) were screened from the gene expression profile GSE122005 between gefitinib-sensitive and resistant samples. GO and KEGG analyses were performed with DAVID. The protein-protein interaction (PPI) network was established to visualize DEGs and screen hub genes. The functional roles of CCL20 in lung adenocarcinoma (LUAD) were examined using gene set enrichment analysis (GSEA). Functional analysis revealed that the DEGs were mainly concentrated in inflammatory, cell chemotaxis, and PI3K signal regulation. Ten hub genes were identified based on the PPI network. The survival analysis of the hub genes showed that CCL20 had a significant effect on the prognosis of LUAD patients. GSEA analysis showed that CCL20 high expression group was mainly enriched in cytokine-related signaling pathways. In conclusion, our analysis suggests that changes in inflammation and cytokine-related signaling pathways are closely related to gefitinib resistance in patients with lung cancer. The CCL20 gene may promote the formation of gefitinib resistance, which may serve as a new biomarker for predicting gefitinib resistance in patients with lung cancer.

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