scholarly journals Network Pharmacology-Based Strategy for Predicting Therapy Targets of Traditional Chinese Medicine Xihuang Pill on Liver Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xu Zhao ◽  
Jian Hao ◽  
Sinuan Chen
Keyword(s):  
Chinese Medicine ◽  
Liver Cancer ◽  
Kinase Activity ◽  
Molecular Targets ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Ppi Network ◽  
Therapy Targets ◽  
Target Network

Objective. To investigate the potential therapy targets and pharmacological mechanism of traditional Chinese medicine (TCM) Xihuang pill in liver cancer based on network pharmacology. Methods. Drug ingredients-target network was constructed based on the target sets of Xihuang pill and liver cancer. The overlapping genes between Xihuang pill targets and liver cancer-related molecular targets were investigated using comparative analysis. Moreover, the PPI network and module was constructed based on overlapping genes and hub nodes, respectively, followed by the pathway enrichment analysis. Results. A drug ingredients-target network was established with 1184 nodes and 11035 interactions. Moreover, a total of 106 overlapping genes were revealed between drug targets and liver cancer molecular targets. Furthermore, a PPI network and 4 modules were further investigated based on overlapping genes, respectively. These hub nodes such as VEGFA and EGFR were mainly enriched in GO functions including positive regulation of MAP kinase activity, activation of protein kinase activity, regulation of MAP kinase activity, and pathways like proteoglycans in cancer, bladder cancer, and estrogen signaling. Conclusion. VEGFA and EGFR might be potential therapy targets of Xihuang pill in liver cancer. Furthermore, the effect of Xihuang pill on liver cancer might be realized by targeting VEGFA and EGFR in pathways like proteoglycans in cancer and estrogen signaling.

scholarly journals An Investigation of the Antigastric Cancer Effect in Tumor Microenvironment of Radix Rhei Et Rhizome: A Network Pharmacology Study

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xinmiao Wang ◽  
Guanghui Zhu ◽  
Haoyu Yang ◽  
Ruike Gao ◽  
Zhe Wu ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Rna Polymerase Ii ◽  
Signaling Pathway ◽  
Kinase Activity ◽  
Topological Analysis ◽  
Chinese Herb ◽  
Estrogen Signaling ◽  
Receptor Protein ◽  
Network Pharmacology ◽  
Target Network

Background. Tumor microenvironment (TME) takes a vital effect on the occurrence and development of cancer. Radix Rhei Et Rhizome (RRER, Da-Huang in pinyin), a classical Chinese herb, has been widely used in gastric cancer (GC) for many years in China. However, inadequate systematic studies have focused on the anti-GC effect of RRER in TME. This study intended to uncover the mechanism of it by network pharmacology. Methods. We collected compounds and targets of RRER from traditional Chinese medicine system pharmacology database and analysis platform (TCMSP) and SwissTargetPrediction. GC targets were obtained from GeneCards. Protein-protein interaction (PPI) network and RRER-GC-target network were built by STRING and Cytoscape 3.2.1. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed using Database for Annotation, Visualization, and Integrated Discovery (DAVID). Results. We obtained 92 compounds of RRER. A total of 10 key compounds and 20 key targets were selected by “RRER-GC-target network” topological analysis. GO analysis showed that the biological process mainly involved in response to the tumor necrosis factor, positive regulation of fibroblast proliferation, and DNA damage response, signal transduction by p53 class mediator resulting in cell cycle arrest. Molecular functions included cyclin-dependent protein serine/threonine kinase activity, RNA polymerase II transcription factor activity, ligand-activated sequence-specific DNA binding, and transmembrane receptor protein tyrosine kinase activity. Cellular components mainly were centrosome, cell surface, and membrane. KEGG pathway enrichment results mainly involved in the p53 signaling pathway, estrogen signaling pathway, and regulation of lipolysis in adipocytes. Conclusion. This study explored the anti-GC mechanism of RRER from the perspective of TME based on network pharmacology, which contributed to the development and application of RRER.

scholarly journals Evidence of TCM Theory in Treating the Same Disease with Different Methods: Treatment of Pneumonia with Ephedra sinica and Scutellariae Radix as an Example

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Liping Sun ◽  
Dandan Wang ◽  
Yan Xu ◽  
Wenxiu Qi ◽  
Yanbo Wang
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Future Directions ◽  
Network Construction ◽  
Ephedra Sinica ◽  
Scutellariae Radix ◽  
Tcm Theory ◽  
Global Health Problem

Pneumonia is a serious global health problem and the leading cause of mortality in children. Antibiotics are the main treatment for bacterial pneumonia, but there are serious drug resistance problems. Traditional Chinese medicine (TCM) has been used to treat diseases for thousands of years and has a unique theory. This article takes the treatment of pneumonia with Ephedra sinica as a representative hot medicine and Scutellariae Radix as a representative cold medicine as an example. We explore and explain the theory of treating the same disease with different TCM treatments. Using transcriptomics and network pharmacology methods, GO, KEGG enrichment, and PPI network construction were carried out, demonstrating that Ephedra sinica plays a therapeutic role through the NF-κB and apoptosis signaling pathways targeting PLAU, CD40LG, BLC2L1, CASP7, and CXCL8. The targets of Scutellariae Radix through the IL-17 signaling pathway are MMP9, CXCL8, and MAPK14. Molecular docking technology was also used to verify the results. In short, our results provide evidence for the theory of treating the same disease with different treatments, and we also discuss future directions for traditional Chinese medicine.

scholarly journals Exploring the Pharmacological Mechanism of the modified Chinese medicine formulas “Shenfu-Linguizhugan decoction” treating Dilated cardiomyopathy Based on Network Pharmacology

2020 ◽  
Author(s):  
Wuxia Quan ◽  
Yandong Miao
Keyword(s):  
Gene Expression ◽  
Chinese Medicine ◽  
Dilated Cardiomyopathy ◽  
Target Genes ◽  
Muscle Disease ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Bioactive Components ◽  
Ppi Network ◽  
Compound Target

Abstract Background: Dilated cardiomyopathy (DCM) is a non-ischaemic cardiac muscle disease with structural and functional myocardial aberration can lead to extensive morbidity and mortality due to complications in particular heart failure and arrhythmia. Two classic Chinese medicine formulas, Shenfu decoction and Linguizhugan decoction, were both shown to exert therapeutic effects on heart disease. Thus, modified Shenfu and Linguizhugan decoction (SFLGZGD) is recommended for treatment DCM. However, its chemical and pharmacological characteristics remain to be elucidated. In the current study, a network pharmacology approach was applied to characterize the action mechanism and target genes of SFLGZGD on DCM.Methods: The gene expression of DCM was obtained from the Gene Expression Omnibus (GEO). All compounds were obtained from the correlative databases, and active mixture were selected according to their oral bioavailability (OB) and drug-likeness (DL) index. The potential targets of SFLGZGD were obtained from the traditional Chinese medicine systems pharmacology (TCMSP) database. The compound-target and target-pathway networks were constructed. The protein-protein interactive (PPI) network generated by R software was visualized by Cytoscape, and the topology scores, functional regions, and gene annotations were analyzed using plugins of Bisogenet and CytoNCA. The potential pathways related to target genes were determined by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.Results: A total of 963 differentially expressed genes (DEGs), including 538 upregulated genes and 425 downregulated, were obtained from GSE19303. A total of 636 ingredients in SFLGZGD were obtained, among which, 93 were chosen as bioactive components. The compound-target network included 10 bioactive components and 18 potential targets and a total of 1939 genes obtained in the PPI network, among them, a total of 16 genes were screened out. Moreover,129 terms on the GO analysis and six pathways obtained. Among these potential targets, EGFR, CDKN1A, MMP1, COL1A1, COL3A1, MMP3, ICAM1, and HSPB1 were identified as relatively high-degree targets.Conclusions: The network pharmacology-based approach in the current study has shown promising potential in identifying major therapeutic targets from TCM formulations. Besides, our study suggested that network pharmacology prediction may provide a useful tool for describing the molecular mechanism of SFLGZGD on DCM.

scholarly journals Integrating Data Mining, Network Pharmacology, and Molecular Docking Verification to Investigate the Molecular Mechanism of Traditional Chinese Medicine Prescriptions for Treating Male Infertility

2021 ◽  
Author(s):  
Xue Bai ◽  
Yibo Tang ◽  
Qiang Li ◽  
Guimin Liu ◽  
Dan Liu ◽  
...  
Keyword(s):  
Data Mining ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Male Infertility ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Oxidant Stress ◽  
Estrogen Signaling ◽  
Network Pharmacology

Abstract Background: Male infertility (MI) affects almost 5% adult men worldwide, and 75% of these cases are unexplained idiopathic. There are limitations in the current treatment due to the unclear mechanism of MI, which highlight the urgent need for a more effective strategy or drug. Traditional Chinese Medicine (TCM) prescriptions have been used to treat MI for thousands of years, but their molecular mechanism is not well defined. Methods: Aiming at revealing the molecular mechanism of TCM prescriptions on MI, a comprehensive strategy integrating data mining, network pharmacology, and molecular docking verification was performed. Firstly, we collected 289 TCM prescriptions for treating MI from National Institute of TCM Constitution and Preventive Medicine for 6 years. Then, Core Chinese Materia Medica (CCMM), the crucial combination of TCM prescriptions, was obtained by the TCM Inheritance Support System from China Academy of Chinese Medical Sciences. Next, the components and targets of CCMM in TCM prescriptions and MI-related targets were collected and analyzed through network pharmacology approach.Results: The results showed that the molecular mechanism of TCM prescriptions for treating MI are regulating hormone, inhibiting apoptosis, oxidant stress and inflammatory. Estrogen signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway, and TNF signaling pathway are the most important signaling pathways. Molecular docking experiments were used to further validate network pharmacology results. Conclusions: This study not only discovers CCMM and the molecular mechanism of TCM prescriptions for treating MI, but may be helpful for the popularization and application of TCM treatment.

scholarly journals Exploring the mechanism of Astragalus membranaceus against uterine fibroids based on network pharmacology

2021 ◽  
Author(s):  
qiu tiantian ◽  
Li DongHua ◽  
Liu Yu ◽  
Gao LiFang ◽  
Wei Chao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Mechanism Of Action ◽  
Regulatory Network ◽  
Drug Targets ◽  
Target Genes ◽  
Uterine Fibroids ◽  
Network Pharmacology ◽  
Ppi Network

Abstract Backgroud: Uterine fibroids (ULs) are the most common benign tumors of the reproductive tract in gynecology and their clinical presentations include menorrhagia, pelvic pressure, dysmenorrhea, and anemia. Surgical resection and the hormonal drug administration are the primary treatment. The plant Astragalus membranaceus (astragalus) has a long history of use in traditional Chinese medicine and studies have shown that it has antitumor effects. However, the role and mechanism of astragalus in ULs are not completely clear. The present study aimed to investigate the astragalus mechanism of action against ULs based on network pharmacology approach, in order to provid insights for the development of a safe and effective drug for the ULs treatment.Methods: The astragalus active ingredients and the potential drug targets were screened by the Traditional Chinese Medicine System Pharmacology Database and Analytical Platform (TCMSP). The gene expression profiles of ULs were obtained from Gene Expression Omnibus (GEO). The intersection of astragalus components target genes and differentially expressed genes between UL and normal patients were obtained using Perl software to provide the astragalus-ULs drug regulatory network. The protein–protein interaction (PPI) network was established using the STRING online database and Cytoscape software, followed by the topological properties analysis of the PPI networks. GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses were conducted by R software. The KEGG relational network was constructed using Cytoscape software. Results: A total of 21 astragalus active ingredients and 406 drug targets were obtained from the TCMSP. Seventeen of these targets overlap with ULs disease targets and were considered potential targets for the ULs treatment by astragalus. The analysis of the regulatory network showed that the astragalus active components with the most targets are quercetin, kaempferol, mangiferin, tetrodotoxin and isorhamnetin. Target genes with the highest Dgree values obtained from the PPI network analysis are estrogen receptor 1 (ESR1), tumor suppressor factor p53 (TP53), neurotrophic tyrosine kinase receptor 1 (NTRK1) and E3 ubiquitin ligase protein (CUL3). GO and KEGG enrichment analyses indicate that these targets are mainly involved in biological processes related to cellular response to reactive oxygen species, oxidative stress and response to lipopolysaccharides. The main signal transduction pathways involved include the IL-17 and TNF signaling pathways, the AGE-RAGE signaling pathway in diabetic complications and proteoglycans in cancer.Conclusions: The present study demonstrates that the astragalus therapeutic use against ULs have multicomponent and multi-target properties, providing a novel approach to further investigate the astragalus mechanism of action in the treatment of ULs.

scholarly journals Network Pharmacology-Based Strategy for Predicting Therapy Targets of Tripterygium wilfordii on Acute Myeloid Leukemia

2020 ◽  
Author(s):  
Tingting Fang ◽  
Lanqin Liu ◽  
wenjun liu
Keyword(s):  
Acute Myeloid Leukemia ◽  
Chinese Medicine ◽  
Signaling Pathway ◽  
Myeloid Leukemia ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Tripterygium Wilfordii ◽  
Active Ingredients ◽  
Acute Myeloid

Abstract Background. Acute myeloid leukemia (AML) is a common malignant tumor of the hematopoietic system. How to extend the survival time of AML patients and improve their prognosis is still a major medical problem. Chinese medicine has a long history in treating AML. Tripterygium wilfordii (TW) is a traditional Chinese medicine. With the deepening of pharmacological research of traditional Chinese medicine, triptolide, one of its active ingredients, has been proven to have a positive effect on the treatment of AML. Therefore，this study aimed on studying the potential therapeutic targets and pharmacological mechanism of TW in Acute myeloid leukemia (AML) based on network pharmacology.Methods. The active components of TW were obtained by network pharmacology through oral bioavailability, drug-likeness filtration. Comparative analysis was used to study the overlapping genes between active ingredient’s targets and AML treatment-related targets. Using STRING database to analyze interactions between overlapping genes. KEGG pathway analysis and Gene Ontology enrichment analysis were conducted in DAVID. These genes were analyzed for survival in OncoLnc database.Key findings. We screened 53 active ingredients, the results of comparative analysis showed that 8 active ingredients had an effect on AML treatment. Based on the active ingredients and overlapping genes, we constructed the Drug-Compounds-Genes-Disease Network. Survival analysis of overlapping genes indicated that some targets possess a significant influence on patients’ survival and prognosis. The enrichment analysis showed that the main pathways of targets are Toll-like receptor signaling pathway, NF-kappa B signaling pathway and HIF-1 signaling pathway.Conclusion. This study, using a network pharmacologic approach, provides another strategy that can help us to understand the mechanisms by which TW treats AML comprehensively.

scholarly journals Network pharmacology-based strategy to investigate pharmacological mechanisms of Qiaoshao formula for treatment of premature ejaculation

2020 ◽  
Author(s):  
Ming Wang ◽  
Qi Wang ◽  
Yongqiang Du ◽  
Xiansheng Zhang
Keyword(s):  
Nitric Oxide ◽  
Chinese Medicine ◽  
Premature Ejaculation ◽  
Biological Process ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Drugbank Database

Abstract Background Qiaoshao (QS) formula, a traditional Chinese medicine (TCM) comprising seven herbs, has been clinically proven to have a favorable treatment effect on premature ejaculation (PE). However, its underlying pharmacological mechanisms in the treatment of PE need to be further clarified. Methods In the present study, a network pharmacology-based strategy was adopted. The active compounds of QS formula were obtained from the Chinese medicine database, and the potential targets of these compounds were collected from the DrugBank database to construct compound-compound targets network. PE-related targets were identified from human disease databases and used to construct the protein-protein interaction (PPI) networks. Compound-disease target PPI network was constructed by merging the PPI network of disease-targets and compound-targets. Cluster and enrichment analyses were performed on the PPI network of disease targets and compound-disease targets. Results Four primary pharmacological network of QS formula were constructed, including the compound-compound targets network, PPI network of PE-related targets and compounds-disease targets, and the QS-PE mechanism network. The module and pathway enrichment analyses revealed that the QS formula had the potential to affect varieties of biological process and pathways, such as nitric oxide biosynthetic process, oxytocin, thyroid hormone, TNF, PI3K-Akt, and the HIF-1 signaling pathway, that play an important role in the pathogenesis of PE. Conclusion This study preliminarily discovered the potential targets and pathways of QS formula in the treatment of PE, which laid a good foundation for further experimental research.

scholarly journals Network Pharmacology Study of Heat-Clearing and Detoxifying Traditional Chinese Medicine for Alzheimer's Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hongxing Li ◽  
Xinyue Zhang ◽  
Lili Gu ◽  
Ningzi Wu ◽  
Lingxi Zhang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Chlorogenic Acid ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis

This study aims to explore the possible homologous mechanism of 7 frequently‐used herbs for heat-clearing and detoxification in traditional Chinese medicine (HDTCM) for treating Alzheimer's disease (AD), one of the most common types of dementia, based on network pharmacology. Herbs that satisfied the criteria of containing chlorogenic acid, relating to AD and aligning with HDTCM, were simultaneously collected to determine whether they have anti-AD effect based on a survey of the literature. Herb-ingredient-target-disease networks were constructed by collecting information from the TCMSP and GeneCards public databases. The common targets of the herbs and AD were identified for conducting a Gene Ontology (GO) analyses and a Reactome pathway enrichment analysis. The results showed that PTGS1, IL-6, CASP3, and VEGFA were the predicted key gene targets. The IL-4 and IL-13 signaling pathway, the ESR-mediated signaling pathway, and the extranuclear estrogen signaling pathway were the significant pathways associated with the 7 herbs. This study revealed that the analogous anti-AD mechanism of the 7 herbs of HDTCM may be associated with anti-inflammation, which is a common effect of the chlorogenic acid and quercetin components.

scholarly journals Network Pharmacology Strategy to Investigate the Pharmacological Mechanism of Siwu Decoction on Primary Dysmenorrhea and Molecular Docking Verification

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dandan Jiang ◽  
Xiaoyan Wang ◽  
Lijun Tian ◽  
Yufeng Zhang
Keyword(s):  
Molecular Docking ◽  
Target Genes ◽  
Network Pharmacology ◽  
Primary Dysmenorrhea ◽  
Ppi Network ◽  
Active Compounds ◽  
Docking Simulations ◽  
Active Target ◽  
Target Network ◽  
Compound Target

Objective. To study the pharmacological mechanisms of Siwu decoction (SWD) on primary dysmenorrhea (PDM) and verify with molecular docking. Methods. The  Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to acquire the active compounds and their corresponding target genes. The GeneCards database was utilized in the search for target genes that were associated with PDM. The intersection genes from the active target genes of SWD and those associated with PDM represented the active target genes of SWD that act on PDM. The Gene Ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were both carried out by RGUI 3.6.1 and Cytoscape 3.6.0 software. Cytoscape was also utilized for creating a compound-target network, and a protein-protein interaction (PPI) network was created through the STRING database. Molecular docking simulations of the macromolecular protein target receptors and their corresponding compounds were performed using AutoDockTool 1.5.6 and AutoDock Vina software. Results. We identified 14 active compounds as well as 97 active target genes of SWD by using the TCMSP. We compared the 97 active target genes of SWD to the 299 target genes related to PDM, and 23 active target genes for SWD that act on PDM which correlated with 11 active compounds were detected. The compound-target network as well as the PPI network were created, in addition to selecting the most essential compounds and their targets in order to create a key compound-target network. The most essential compounds were kaempferol, beta-sitosterol, stigmasterol, and myricanone. The key targets were AKT1, PTGS2, ESR1, AHR, CASP3, and PGR. Lastly, molecular docking was used to confirm binding of the target with its corresponding compound. Conclusion. The pharmacological mechanisms of SWD that act on PDM were investigated, and the active compounds in the SWD for treating PDM were further verified.

scholarly journals Identifying the molecular targets of Salvia miltiorrhiza (SM) in ox-LDL induced macrophage-derived foam cells based on the integration of metabolomics and network pharmacology

RSC Advances ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. 3760-3767 ◽  
Author(s):  
W. J. Xu ◽  
L. M. Chen ◽  
Z. Y. Wei ◽  
P. Q. Wang ◽  
J. Liu ◽  
...  
Keyword(s):  
Drug Targets ◽  
Salvia Miltiorrhiza ◽  
Molecular Targets ◽  
Foam Cells ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Compounds

The discovery of drug targets and the specific regulatory manner of active compounds based on a PPI network.

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