scholarly journals Network Pharmacology-Based Identification of the Mechanisms of Shen-Qi Compound Formula in Treating Diabetes Mellitus

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Zhipeng Hu ◽  
Maoyi Yang ◽  
Liangjun Yang ◽  
Chunguang Xie ◽  
Hong Gao ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Components ◽  
Protein Protein Interaction ◽  
Go Enrichment ◽  
System Pharmacology ◽  
Target Network ◽  
Integrated Pathway ◽  
Go Enrichment Analysis

Aim. The purpose of this research is to identify the mechanisms of Shen-Qi compound formula (SQC), a traditional Chinese medicine (TCM), for treating diabetes mellitus (DM) using system pharmacology. Methods. The active components and therapeutic targets were identified, and these targets were analyzed using gene ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) analysis. Finally, an integrated pathway was constructed to show the mechanisms of SQC. Results. A total of 282 active components and 195 targets were identified through a database search. The component-target network was constructed, and the key components were screened out according to their degree. Through the GO, PPI, and KEGG analyses, the mechanism network of SQC treating DM was constructed. Conclusions. This study shows that the mechanisms of SQC treating DM are related to various pathways and targets. This study provides a good foundation and basis for further in-depth verification and clinical application.

scholarly journals Network pharmacology and molecular docking analysis on molecular targets and mechanisms of Angelicae Pubescentis Radix in the treatment of rheumatoid arthritis

2021 ◽  
Author(s):  
yanni yang ◽  
yirixiati aihaiti ◽  
peng xu ◽  
haishi zheng
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Active Components ◽  
Target Proteins ◽  
Go Enrichment ◽  
Go Enrichment Analysis

Abstract Purpose:To explore the potential target proteins underlying the effect of Angelicae Pubescentis Radix(APR) on rheumatoid arthritis (RA) using a network pharmacology and molecular docking approach .Methods:First, the active components and target proteins of APR and RA related disease targets were obtained from the TCMSP, Gene Card,OMIM,DisGeNET and STRING databases. Then the active ingredient target in the RA network diagram was drawn using Cytoscape 3.7.1 software. Protein-protein interaction analysis, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analyses were carried out using the STRING and David databases. The crystal structures of RA related targets were retrieved from the RCSB PDB database. Finally, the potential active compounds and their related targets were validated using molecular docking technology.Results: Five active components of Angelicae Pubescentis Radix(APR) were screened out, including ammidin, isoimperatorin, beta-sitosterol, O-acetylcolumbianetin and angelicone and 80 key targets including MAPK8,EGFR,PTGS2,CASPASE3,MTOR,SRC,KDR,MAPK1,NOS3 and MAPK14, etc were obtained. GO enrichment analysis showed that 222 biological processes, 34 cell components and 72 molecular functions were identified; KEGG analysis showed that the targets of APR in the treatment of RA were significantly enriched in pathways in cancer, the PI3K−Akt signaling pathway, Proteoglycans in cancer, osteoclast differentiation, neuroactive ligand−receptor interaction, tuberculosis,TNF signaling pathway, serotonergic synapse, Rap1 signaling pathway,cAMP signaling pathway. The results of molecular docking showed that ammidin, isoimperatorin, beta-sitosterol, O-acetylcolumbianetin and angelicone had strong affinity for PTGS2, EGFR and MAPK8.Conclusion: APR treats RA through the characteristics of multi-component, multi-target and multi-pathway regulation.

scholarly journals Network Pharmacology-based Strategy for Studying the Mechanism of Gegen Qinlian Decoction for the Treatment of Acute Colitis

2020 ◽  
Author(s):  
Tingting Wang ◽  
Yanwen Xu ◽  
Wanli Ji ◽  
Rui An
Keyword(s):  
Signaling Pathway ◽  
Biological Process ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Components ◽  
Acute Colitis ◽  
Rat Serum ◽  
Kegg Pathway Analysis ◽  
Go Enrichment ◽  
Go Enrichment Analysis

Abstract Background: Gegen Qinlian Decoction(GQD) has been used to treat acute colitis (AC) for several years in China and it has shown good efficacy. However, the active components and target proteins of its anti-AC effects remains to be deciphered. Methods: In this study, serum pharmacochemistry and network pharmacology strategy were integrated to identify the constituents in blood and the mechanism of GQD for the treatment of AC. Ultra-performance liquid chromatography and LTQ-Orbitrap mass spectrometry(UPLC-LTQ-Orbitrap-MS) was used to identify the absorbed components of GQD in rat serum; molecular docking and compound-target network analysis were used to predict candidate targets and critical components in GQD responsible for efficacy; In addition, the Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis and Gene Ontology(GO) enrichment analysis were used to predict the related pathways and biological process respectively; Finally, the model rats with acute colitis were induced by DSS(Dextran Sulfact Sodium) in order to verify the effects and potential mechanism of baicalein, which is an important component of GQD. Results: Based on our comprehensive systematic approach, 23 components were successfully identified in rat serum after oral administration of GQD. The predicted results of molecular docking indicated that these 23 active components closely interacted with 41 protein targets associated with inflammation, immunity and enteric mucos. Among the 23 compounds identified, baicalin, baicalein, wogonoside , liquiritin and daidzin may be the most important components of GQD. Futhermore, according to GO enrichment analysis, the 41 candidate targets identified were mainly involved in two biological process, immune system process and inflammatory response. The KEGG pathway analysis revealed that 41 candidate targets were associated with 62 biological pathways, including HIF-1 signaling pathway and PI3K/Akt signaling pathway. Animal experiments found that baicalein could inhibit the activation of PI3K/Akt/HIF-1 signaling pathway and significantly reduce pro-inflammatory cytokines, such as IL-1β, IL-6, IL-8 and TNF-α to alleviate intestinal mucosal damage and achieve a therapeutic effect on AC. Conclusion: This research not only provides a novel and scientific strategy to better understand the complex mechanism of GQD, but also offers a new perspective to identify and/or discover novel active ingredients of TCM drugs.

Discussing the Mechanism of Dahuang Huanglian Xiexin Decoction in the Treatment of Type 2 Diabetes Mellitus via Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xi Cen ◽  
Yan Wang ◽  
LeiLei Zhang ◽  
XiaoXiao Xue ◽  
Yan Wang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Potential Mechanism ◽  
Active Components ◽  
The Core ◽  
Core Genes

Abstract BackgroundType 2 diabetes mellitus (T2DM) is regarded as Pi Dan disease in traditional Chinese medicine (TCM). Dahuang Huanglian Xiexin Decoction (DHXD), a classical TCM formula, has been used for treating Pi Dan disease in clinic, its pharmacological mechanism has not been elucidated. MethodsThis study used network pharmacological analysis and molecular docking approach to explore the mechanism of DHXD on T2DM. Firstly, the compounds in DHXD were obtained from TCMSP and TCMID databases, the potential targets were determined based on TCMSP and UniProt databases. Next, Genecards, Digenet and UniProt databases were used to identify the targets of T2DM. Then, the protein-protein interaction (PPI) network was established with overlapping genes of T2DM and compounds, and the core targets in the network were identified and analyzed. Then, the David database was used for GO and KEGG enrichment analysis. Finally, the target genes were selected and the molecular docking was completed by Autodock software to observe the binding level of active components with target genes.ResultsA total of 397 related components and 128 overlapping genes were identified. After enrichment analysis, it was found that HIF-1, TNF, IL-17 and other signaling pathways, as well as DNA transcription, gene expression, apoptosis and other cellular biological processes had the strongest correlation with the treatment of T2DM by DHXD, and most of them occurred in the extracellular space, plasma membrane and other places, which were related to enzyme binding and protein binding. In addition, 42 core genes of DHXD, such as VEGFA, TP53 and MAPK1, were considered as potential therapeutic targets, indicating the potential mechanism of DHXD on T2DM. Finally, the results of molecular docking showed that HIF-1 pathway had strong correlation with the target genes INSR and GLUT4, quercetin and berberine had the strongest binding power with them respectively.ConclusionThis study summarized the main components of DHXD in the treatment of T2DM, identified the core genes and pathways, and systematically analyzed the interaction of related targets, trying to lay the foundation for clarifying the potential mechanism of DHXD on T2DM, so as to carry out further research in the future.

scholarly journals Mining Featured Biomarkers Linked with Epithelial Ovarian Cancer Based on Bioinformatics

Diagnostics ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 39
Author(s):  
◽  
Chanabasayya Vastrad ◽  
◽  
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Target Gene ◽  
Enrichment Analysis ◽  
Microrna Target ◽  
Pathway Enrichment ◽  
Protein Protein Interaction ◽  
Go Enrichment ◽  
Gene Regulatory ◽  
Go Enrichment Analysis

: Epithelial ovarian cancer (EOC) is the18th most common cancer worldwide and the 8th most common in women. The aim of this study was to diagnose the potential importance of, as well as novel genes linked with, EOC and to provide valid biological information for further research. The gene expression profiles of E-MTAB-3706 which contained four high-grade ovarian epithelial cancer samples, four normal fallopian tube samples and four normal ovarian epithelium samples were downloaded from the ArrayExpress database. Pathway enrichment and Gene Ontology (GO) enrichment analysis of differentially expressed genes (DEGs) were performed, and protein-protein interaction (PPI) network, microRNA-target gene regulatory network and TFs (transcription factors ) -target gene regulatory network for up- and down-regulated were analyzed using Cytoscape. In total, 552 DEGs were found, including 276 up-regulated and 276 down-regulated DEGs. Pathway enrichment analysis demonstrated that most DEGs were significantly enriched in chemical carcinogenesis, urea cycle, cell adhesion molecules and creatine biosynthesis. GO enrichment analysis showed that most DEGs were significantly enriched in translation, nucleosome, extracellular matrix organization and extracellular matrix. From protein-protein interaction network (PPI) analysis, modules, microRNA-target gene regulatory network and TFs-target gene regulatory network for up- and down-regulated, and the top hub genes such as E2F4, SRPK2, A2M, CDH1, MAP1LC3A, UCHL1, HLA-C (major histocompatibility complex, class I, C) , VAT1, ECM1 and SNRPN (small nuclear ribonucleoprotein polypeptide N) were associated in pathogenesis of EOC. The high expression levels of the hub genes such as CEBPD (CCAAT enhancer binding protein delta) and MID2 in stages 3 and 4 were validated in the TCGA (The Cancer Genome Atlas) database. CEBPD andMID2 were associated with the worst overall survival rates in EOC. In conclusion, the current study diagnosed DEGs between normal and EOC samples, which could improve our understanding of the molecular mechanisms in the progression of EOC. These new key biomarkers might be used as therapeutic targets for EOC.

scholarly journals A Network Pharmacology Approach to Explore the Pharmacological Mechanism of Xiaoyao Powder on Anovulatory Infertility

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Huiping Liu ◽  
Liuting Zeng ◽  
Kailin Yang ◽  
Guomin Zhang
Keyword(s):  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Compounds ◽  
Pharmacological Mechanism ◽  
Go Enrichment ◽  
Human Proteins ◽  
Network Pictures ◽  
Go Enrichment Analysis ◽  
Anovulatory Infertility

Aim.To explore the pharmacological mechanism of Xiaoyao powder (XYP) on anovulatory infertility by a network pharmacology approach.Method.Collect XYP’s active compounds by traditional Chinese medicine (TCM) databases, and input them into PharmMapper to get their targets. Then note these targets by Kyoto Encyclopedia of Genes and Genomes (KEGG) and filter out targets that can be noted by human signal pathway. Get the information of modern pharmacology of active compounds and recipe’s traditional effects through databases. Acquire infertility targets by Therapeutic Target Database (TTD). Collect the interactions of all the targets and other human proteins via String and INACT. Put all the targets into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to do GO enrichment analysis. Finally, draw the network by Cytoscape by the information above.Result.Six network pictures and two GO enrichment analysis pictures are visualized.Conclusion.According to this network pharmacology approach some signal pathways of XYP acting on infertility are found for the first time. Some biological processes can also be identified as XYP’s effects on anovulatory infertility. We believe that evaluating the efficacy of TCM recipes and uncovering the pharmacological mechanism on a systematic level will be a significant method for future studies.

scholarly journals A Network Pharmacology Perspective Investigation of the Pharmacological Mechanisms of the Herbal Drug FDY003 in Gastric Cancer

2022 ◽  
Vol 17 (1) ◽  
pp. 1934578X2110730
Author(s):  
Ho-Sung Lee ◽  
In-Hee Lee ◽  
Kyungrae Kang ◽  
Sang-In Park ◽  
Minho Jung ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cellular Proliferation ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Herbal Drug ◽  
Cellular Processes ◽  
Go Enrichment ◽  
Phytochemical Compounds ◽  
Go Enrichment Analysis

Gastric cancer (GC) is one of the most common and deadly malignant tumors worldwide. While the application of herbal drugs for GC treatment is increasing, the multicompound–multitarget pharmacological mechanisms involved are yet to be elucidated. By adopting a network pharmacology strategy, we investigated the properties of the anticancer herbal drug FDY003 against GC. We found that FDY003 reduced the viability of human GC cells and enhanced their chemosensitivity. We also identified 8 active phytochemical compounds in FDY003 that target 70 GC-associated genes and proteins. Gene ontology (GO) enrichment analysis suggested that the targets of FDY003 are involved in various cellular processes, such as cellular proliferation, survival, and death. We further identified various major FDY003 target GC-associated pathways, including PIK3-Akt, MAPK, Ras, HIF-1, ErbB, and p53 pathways. Taken together, the overall analysis presents insight at the systems level into the pharmacological activity of FDY003 against GC.

Virtual Screening of Potential Anti-fatigue Mechanism of Polygonati Rhizoma Based on Network Pharmacology

2020 ◽  
Vol 22 (9) ◽  
pp. 612-624 ◽  
Author(s):  
Ze-Feng Wang ◽  
Ye-Qing Hu ◽  
Qi-Guo Wu ◽  
Rui Zhang
Keyword(s):  
Virtual Screening ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Vital Role ◽  
Network Pharmacology ◽  
Pathway Network ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Protein Protein Interaction Network ◽  
Fatigue Mechanism

Background and Objective: A large number of people are facing the danger of fatigue due to the fast-paced lifestyle. Fatigue is common in some diseases, such as cancer. The mechanism of fatigue is not definite. Traditional Chinese medicine is often used for fatigue, but the potential mechanism of Polygonati Rhizoma (PR) is still not clear. This study attempts to explore the potential anti-fatigue mechanism of Polygonati Rhizoma through virtual screening based on network pharmacology. Methods: The candidate compounds of PR and the known targets of fatigue are obtained from multiple professional databases. PharmMapper Server is designed to identify potential targets for the candidate compounds. We developed a Herbal medicine-Compound-Disease-Target network and analyzed the interactions. Protein-protein interaction network is developed through the Cytoscape software and analyzed by topological methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment are carried out by DAVID Database. Finally, we develop Compound-Target-Pathway network to illustrate the anti-fatigue mechanism of PR. Results: This approach identified 12 active compounds and 156 candidate targets of PR. The top 10 annotation terms for GO and KEGG were obtained by enrichment analysis with 35 key targets. The interaction between E2F1 and PI3K-AKT plays a vital role in the anti-fatigue effect of PR due to this study. Conclusions: This study demonstrates that PR has multi-component, multi-target and multipathway effects.

Mechanism of Shuang-Huang-Lian Oral Liquid for Treatment of Mycoplasmal Pneumonia in Children on Network Pharmacology

2020 ◽  
Vol 23 (9) ◽  
pp. 955-971 ◽  
Author(s):  
Ling Shi ◽  
Qi-Guo Wu ◽  
Ju-Cheng Zhang ◽  
Guang-Ming Yang ◽  
Wei Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Acute Bronchitis ◽  
Network Pharmacology ◽  
Upper Respiratory Tract ◽  
Protein Protein Interaction ◽  
System Pharmacology ◽  
Oral Liquid ◽  
Mycoplasmal Pneumonia

Background and Objective: Mycoplasmal pneumonia (MP) can lead to inflammation, multiple system immune damage, and mixed infection in children. The pathogenesis is still unclear. Shuang-Huang-Lian (SHL) oral liquid can treat acute upper respiratory tract infection, acute bronchitis and light pneumonia. However, our current understanding of the molecular mechanisms supporting its clinical application still lags behind due to the lack of researches. It is difficult to understand the overall sensitization mechanism of SHL oral liquid. The purpose is to explain the mechanism of action of drugs in this study, which is useful to ensure the safety of medication for children. Methods: The therapeutic mechanism of SHL oral liquid was investigated by a system pharmacology approach integrating drug-likeness evaluation, oral bioavailability prediction, ADMET, protein-protein interaction worknet, Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes database pathway performance, C-T-P network construction and molecular docking. Results: A total of 18 active ingredients contained in SHL oral liquid and 53 major proteins were screened out as effective players in the treatment of M. pneumoniae disease through some related pathways and molecular docking. The majority of targets, hubs and pathways were highly related to anti-mycoplasma therapy, immunity and inflammation process. Conclusions: This study shows that the anti-bacterial effect of SHL oral liquid has multicomponent, multi-target and multi-pathway phenomena. The proposed approach may provide a feasible tool to clarify the mechanism of traditional Chinese medicines and further develop their therapeutic potentials.

scholarly journals Reveals of New Candidate Active Components in Hemerocallis Radix and Its Anti-Depression Action of Mechanism Based on Network Pharmacology Approach

2020 ◽  
Vol 21 (5) ◽  
pp. 1868 ◽  
Author(s):  
Hsin-Yi Lin ◽  
Jen-Chieh Tsai ◽  
Lung-Yuan Wu ◽  
Wen-Huang Peng
Keyword(s):  
Network Pharmacology ◽  
Antidepressant Effect ◽  
Depression Symptoms ◽  
Active Components ◽  
Protein Protein Interaction ◽  
Pharmacological Mechanism ◽  
Go Enrichment ◽  
Therapeutic Mechanism ◽  
And Cluster Analysis ◽  
Depression Disorder

The global depression population is showing a significant increase. Hemerocallis fulva L. is a common Traditional Chinese Medicine (TCM). Its flower buds are known to have ability to clear away heat and dampness, detoxify, and relieve depression. Ancient TCM literature shows that its roots have a beneficial effect in calming the spirit and even the temper in order to reduce the feeling of melancholy. Therefore, it is inferred that the root of Hemerocallis fulva L. can be used as a therapeutic medicine for depression. This study aims to uncover the pharmacological mechanism of the antidepressant effect of Hemerocallis Radix (HR) through network pharmacology method. During the analysis, 11 active components were obtained and screened using ADME—absorption, distribution, metabolism, and excretion— method. Furthermore, 267 HR targets and 740 depressive disorder (DD) targets were gathered from various databases. Then protein–protein interaction (PPI) network of HR and DD targets were constructed and cluster analysis was applied to further explore the connection between the targets. In addition, gene ontology (GO) enrichment and pathway analysis was applied to further verify that the biological process related to the target protein is associated with the occurrence of depression disorder. In conclusion, the most important bioactive components—anthraquinone, kaempferol, and vanillic acid—can alleviate depression symptoms by regulating MAOA, MAOB, and ESR1. The proposed network pharmacology strategy provides an integrating method to explore the therapeutic mechanism of multi-component drugs on a systematic level.

scholarly journals A Network Pharmacology Approach to Uncover the Potential Mechanism of Yinchensini Decoction

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Guoming Chen ◽  
Chuyao Huang ◽  
Yunyun Liu ◽  
Tengyu Chen ◽  
Ruilan Huang ◽  
...  
Keyword(s):  
Rna Polymerase Ii ◽  
Enrichment Analysis ◽  
Drug Binding ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Potential Mechanism ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
System Pharmacology

Objective. To predict and explore the potential mechanism of Yinchensini decoction (YCSND) based on systemic pharmacology. Method. TCMSP database was searched for the active constituents and related target proteins of YCSND. Cytoscape 3.5.1 was used to construct the active ingredient-target interaction of YCSND and network topology analysis, with STRING online database for protein-protein interaction (PPI) network construction and analysis; and collection from the UniProt database of target protein gene name, with the DAVID database for the gene ontology (GO) functional analysis, KEGG pathway enrichment analysis mechanism and targets of YCSND. Results. The results indicate the core compounds of YCSND, namely, kaempferol, 7-Methoxy-2-methyl isoflavone, and formononetin. And its core targets are prostaglandin G/H synthase 2, estrogen receptor, Calmodulin, heat shock protein HSP 90, etc. PPI network analysis shows that the key components of the active ingredients of YCSND are JUN, TP53, MARK1, RELA, MYC, and so on. The results of the GO analysis demonstrate that extracellular space, cytosol, and plasma membrane are the main cellular components of YCSND. Its molecular functions are mainly acting on enzyme binding, protein heterodimerization activity, and drug binding. The biological process of YCSND is focused on response to drug, positive regulation of transcription from RNA polymerase II promoter, the response to ethanol, etc. KEGG results suggest that the pathways, including pathways in cancer, hepatitis B, and pancreatic cancer, play a key role in YCSND. Conclusion. YCSND exerts its drug effect through various signaling pathways and acts on kinds of targets. By system pharmacology, the potential role of drugs and the mechanism of action can be well predicted.

Sign in / Sign up

Export Citation Format

Share Document