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.

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 Exploration of underlying molecular mechanism of Lycii Cortex in Treating Type 2 Diabetes Mellitus Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 233 ◽  
pp. 02007
Author(s):  
Dongjun Li ◽  
Denghui Wang ◽  
Shikai Yan
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Kegg Pathway Analysis ◽  
Go Enrichment ◽  
Core Components ◽  
Receptor Signaling Pathway ◽  
Go Enrichment Analysis

Objective: To explore the potential molecular mechanism of Lycii Cortex in treating type 2 diabetes mellitus (T2DM) by virtue of network pharmacology and molecular docking method. Methods: Ingredients of Lycii Cortex were collected from TCMSP and BATMAN-TCM databases, and the corresponding targets and T2DM-related targets were obtained respectively from SwissTargetPrediction and GenCards databases. Venn diagram was applied to derive the potential active components and effect targets of Lycii Cortex in the treatment of T2DM. GO enrichment analysis and KEGG pathway analysis were performed in the database of DAVID. Cytoscape 3.6.1 was used to produce the “core components-core targets” network. The molecular docking between core components and core targets was implemented through Autodock Vina. Results: Six core components and twelve core targets of Lycii Cortex in treating T2DM were identified. GO enrichment analysis and KEGG pathway analysis suggested the following signaling pathways and biological processes were involved in the treatment of T2DM by Lycii Cortex: PI3K-Akt signaling pathway, TNF signaling pathway, HIF-1 signaling pathway, Toll-like receptor signaling pathway, NOD-like receptor signaling pathway, and peptidyl-threonine phosphorylation, the positive regulation of cyclase activity, the positive regulation of genetic expression, and lipoprotein translocation. The binding results demonstrated a relatively high affinity between core components of Lycii Cortex, including kulactone, hederagenin, scopolin, etc., and core targets, containing IL6, PPARγ, TNF, and mTOR, indicating the efficacy of Lycii Cortex in treating T2DM. Conclusion: Lycii Cortex plays a role in the treatment of T2DM with its ingredients such as kulactone, linarin, hederagenin, and scopolin regulating glycometabolism, affecting cell apoptosis and weakening inflammatory response through targets like IL6, PPARγ, TNF, and mTOR.

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 The Underlying Mechanism of Chinese Herb of Regulating Marrow in the Treatment of  Osteonecrosis of the Femoral Head Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xiaojian Wang ◽  
Rui Wang ◽  
Ting Xu ◽  
Hongting Jin ◽  
Peijian Tong ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Active Components ◽  
Pathway Enrichment

Abstract Background The lesion of marrow is a crucial factor in orthopedic diseases, which is recognized by orthopedics-traumatology expert from "Zhe-School of Chinese Medicine". The Chinese herbs of regulating marrow has been widely used to treat osteonecrosis of the femoral head (ONFH) in China, while the interaction mechanisms were still elucidated. Thus, we conducted this study to explore the underlying mechanism of the five highest-frequency Chinese herbs of regulating marrow(HF-CHRM) in the treatment of ONFH with the aid of network pharmacology(NP) and molecular docking(MD). Methods The active components and potential targets of HF-CHRM were obtained through several online databases, such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), UniProt database. The gene targets related to ONFH were collected with the help of the OMIM and GeneCards disease-related databases. The "drug- component-target-disease" network and protein-protein interaction(PPI) network of the drug and disease intersecting targets were constructed by using Cytoscape software and the STRING database. R software was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The MD of critical components and targets was carried out using Autodock Vina and Pymol to validate the binding affinity. Results A total of 54 active components, 1074 drug targets and 195 gene targets were obtained. There were 1219 ONFH related targets. 39 drug and disease intersection targets(representative genes: IL6, TP53, VEGFA, ESR1, IL1B) were obtained and considered potential therapeutic targets. 1619 items were obtained by the GO enrichment analysis, including 1517 biological processes, 10 cellular components and 92 molecular functions, which is mainly related to angiogenesis, bone and lipid metabolism and inflammatory reaction. The KEGG pathway enrichment analysis revealed 119 pathways, including AGE-RAGE signaling pathway, PI3K-Akt signaling pathway and IL-17 signaling pathway. MD results showed that quercetin, wogonin, and kaempferol active components had good affinity with IL6, TP53, and VEGFA core proteins. Conclusion The HF-CHRM can treat ONFH by multi-component, multi-target, and multi-pathway comprehensive action.

scholarly journals Ganghuo Kanggan Decoction in Influenza: Integrating Network Pharmacology and In Vivo Pharmacological Evaluation

2020 ◽  
Vol 11 ◽  
Author(s):  
Yanni Lai ◽  
Qiong Zhang ◽  
Haishan Long ◽  
Tiantian Han ◽  
Geng Li ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Influenza A ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
New Drugs ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Compound Screening

Background: Ganghuo Kanggan decoction (GHKGD) is a clinical experience prescription used for the treatment of viral pneumonia in the Lingnan area of China, and its clinical effect is remarkable. However, the mechanism of GHKGD in influenza is still unclear.Objective: To predict the active components and signaling pathway of GHKGD and to explore its therapeutic mechanism in influenza and to verified it in vivo using network pharmacology.Methods: The potential active components and therapeutic targets of GHKGD in the treatment of influenza were hypothesized through a series of network pharmacological strategies, including compound screening, target prediction and pathway enrichment analysis. Based on the target network and enrichment results, a mouse model of influenza A virus (IAV) infection was established to evaluate the therapeutic effect of GHKGD on influenza and to verify the possible molecular mechanism predicted by network pharmacology.Results: A total of 116 candidate active compounds and 17 potential targets were identified. The results of the potential target enrichment analysis suggested GHKGD may involve the RLR signaling pathway to reduce inflammation in the lungs. In vivo experiments showed that GHKGD had a protective effect on pneumonia caused by IAV-infected mice. Compared with the untreated group, the weight loss in the GHKGD group in the BALB/c mice decreased, and the inflammatory pathological changes in lung tissue were reduced (p < 0.05). The expression of NP protein and the virus titers in lung were significantly decreased (p < 0.05). The protein expression of RIG-I, NF-kB, and STAT1 and the level of MAVS and IRF3/7 mRNA were remarkably inhibited in GHKGD group (p < 0.05). After the treatment with GHKGD, the level of Th1 cytokines (IFN-γ, TNF-α, IL-2) was increased, while the expression of Th2 (IL-5, IL4) cytokines was reduced (p < 0.05).Conclusion: Through a network pharmacology strategy and in vivo experiments, the multi-target and multi-component pharmacological characteristics of GHKGD in the treatment of influenza were revealed, and regulation of the RLR signaling pathway during the anti-influenza process was confirmed. This study provides a theoretical basis for the research and development of new drugs from GHKGD.

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.

scholarly journals Study on the Mechanism of Acori Graminei Rhizoma in the Treatment of Alzheimer’s Disease Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yi Kuan Du ◽  
Yue Xiao ◽  
Shao Min Zhong ◽  
Yi Xing Huang ◽  
Qian Wen Chen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
The Elderly ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Active Components

Alzheimer’s disease is a common neurodegenerative disease in the elderly. This study explored the curative effect and possible mechanism of Acori graminei rhizoma on Alzheimer’s disease. In this paper, 8 active components of Acori graminei rhizoma were collected by consulting literature and using the TCMSP database, and 272 targets were screened using the PubChem and Swiss Target Prediction databases. Introduce it into the software of Cytoscape 3.7.2 and establish the graph of “drug-active ingredient-ingredient target.” A total of 276 AD targets were obtained from OMIM, Gene Cards, and DisGeNET databases. Import the intersection targets of drugs and diseases into STRING database for enrichment analysis, and build PPI network in the Cytoscape 3.7.2 software, whose core targets involve APP, AMPK, NOS3, etc. GO analysis and KEGG analysis showed that there were 195 GO items and 30 AD-related pathways, including Alzheimer’s disease pathway, serotonin synapse, estrogen signaling pathway, dopaminergic synapse, and PI3K-Akt signaling pathway. Finally, molecular docking was carried out to verify the binding ability between Acori graminei rhizoma and core genes. Our results predict that Acori graminei rhizoma can treat AD mainly by mediating Alzheimer’s signal pathway, thus reducing the production of Aβ, inhibiting the hyperphosphorylation of tau protein, regulating neurotrophic factors, and regulating the activity of kinase to change the function of the receptor.

scholarly journals A Study on the Mechanism of Milkvetch Root in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Chunli Piao ◽  
Qi Zhang ◽  
De Jin ◽  
Li Wang ◽  
Cheng Tang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Systems Pharmacology ◽  
Active Components ◽  
Kegg Pathways

Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. Owing to its complicated pathogenesis, no satisfactory treatment strategies for DN are available. Milkvetch Root is a common traditional Chinese medicine (TCM) and has been extensively used to treat DN in clinical practice in China for many years. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of Milkvetch Root in treating DN has not been completely elucidated. The aim of this study was to explore the active components and potential mechanism of Milkvetch Root by using a systems pharmacology approach. First, the components and targets of Milkvetch Root were analyzed by using the Traditional Chinese Medicine Systems Pharmacology database. We found the common targets of Milkvetch Root and DN constructed a protein-protein interaction (PPI) network using STRING and screened the key targets via topological analysis. Enrichment of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. Subsequently, major hubs were identified and imported to the Database for Annotation, Visualization and Integrated Discovery for pathway enrichment analysis. The binding activity and targets of the active components of Milkvetch Root were verified by using the molecular docking software SYBYL. Finally, we found 20 active components in Milkvetch Root. Moreover, the enrichment analysis of GO and KEGG pathways suggested that AGE-RAGE signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway might be the key pathways for the treatment of DN; more importantly, 10 putative targets of Milkvetch Root (AKT1, VEGFA, IL-6, PPARG, CCL2, NOS3, SERPINE1, CRP, ICAM1, and SLC2A) were identified to be of great significance in regulating these biological processes and pathways. This study provides an important scientific basis for further elucidating the mechanism of Milkvetch Root in treating DN.

scholarly journals Network Pharmacology Analysis of the active components and anticancer targets of Rhubarb

2021 ◽  
Author(s):  
Hu Junrui ◽  
Duan Yongqiang ◽  
Cui Gongning ◽  
Luo Qiang ◽  
Xi Shanshan ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Drug Targets ◽  
Target Genes ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds ◽  
Cellular Targets ◽  
Kegg Pathway Analysis

AbstractTo investigate the mechanisms and active components governing the anticancer activity of rhubarb.The TCMSP database was screened to identify the active components of rhubarb and Swiss target predictions were generated to predict their cellular targets. TTD and OMIM databases were used to predict tumor-related target genes. "Cytoscape" was used to construct drug targets. PPI network analysis, GO enrichment analysis and KEGG pathway analysis of the key targets were investigated using String and David databases. A total of 33 components and 116 corresponding targets were screened. Amongst them, the key active compounds in rhubarb included emodin, aloe emodin, β-sitosterol, emodin methyl ether and rhein, which were predicted to target TP53, AKT1, STAT3, PIK3CA, HRAS, and VEGFA. GO analysis revealed that the cellular targets clustered into 159 biological processes, including those involved in cellular composition (n=24) and molecular functions (n=42, P<0.01). KEGG pathway analysis revealed 85 (P < 0.01) pathways related to cancer. The active compounds in rhubarb target TP53, AKT1 and PIK3CA. Rhubarb therefore regulates cancer development through an array of biological pathways.

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