scholarly journals Integrating Network Pharmacology and Experimental Validation to Investigate the Mechanisms of Huazhuojiedu Decoction to Treat Chronic Atrophic Gastritis

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xinyu Hao ◽  
Yu Liu ◽  
Pingping Zhou ◽  
Qian Jiang ◽  
Zeqi Yang ◽  
...  
Keyword(s):  
Atrophic Gastritis ◽  
Experimental Validation ◽  
Precancerous Lesions ◽  
Animal Experiments ◽  
Interaction Network ◽  
Chronic Atrophic Gastritis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Egfr Expression

Background. Chronic atrophic gastritis (CAG) is an important stage in the normal gastric mucosa’s transformation into gastric cancer. Huazhuojiedu decoction (HZJD), a Chinese herbal preparation, has proven clinically effective to treat CAG. However, few studies have explored the mechanism of HZJD in CAG treatment. Purpose. This study aimed to shed light on the mechanisms underlying HZJD decoction CAG treatment using a network pharmacology approach and experimental validation. Methods. The active components of HZJD decoction were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. Their targets were predicted through the SwissTargetPrediction database. Disease targets were screened using the GeneCards database. The disease and drug prediction targets were intersected to select the common potential therapeutic targets, which then were input into the Search Tool for the Retrieval of Interacting Genes to build a protein-protein interaction network. The “herb-compound-target-disease” and the “herb-target-pathway” network diagrams were constructed in Cytoscape 3.3.0. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of effective targets were performed using the Database for Annotation, Visualization, and Integrated Discovery. Finally, the core targets were preliminarily verified by CAG rat model. The gastric mucosa’s histopathological changes were observed via hematoxylin-eosin staining. The expressions of MAPK1, AKT1, TNF, VEGFA, and EGFR were detected by western blot and quantitative real-time reverse transcription-polymerase chain reaction. Results. A total of 155 nodes, including 20 putative targets of HZJD decoction, were selected as core hubs based on topological importance and were closely associated with the regulation of cell proliferation, apoptotic process, and cancer-related pathways (AKT1, TNF, VEGFA, and EGFR) in CAG. Further animal experiments showed that the expression of AKT1 in CAG rats was significantly increased, which was suppressed by HZJD decoction. TNF and VEGFA expression increased in the model group, but did not change in the HZJD group. MAPK1 and EGFR expression showed no significant differences among control, model, and HZJD groups. Conclusion. Taken together, the results suggest that the components of HZJD decoction can alleviate and prevent the severity of gastric precancerous lesions via AKT1 inhibition in CAG.

scholarly journals Screening and Identification of Molecular Targets Involved in Preventing Gastric Precancerous Lesions in Chronic Atrophic Gastritis by Qilianshupi Decoction

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Yameng Zhang ◽  
Chao Li ◽  
Shanmei Sun ◽  
Zhiqun Cao ◽  
Jian Chen ◽  
...  
Keyword(s):  
Atrophic Gastritis ◽  
Telomere Length ◽  
Precancerous Lesions ◽  
Animal Experiments ◽  
Molecular Targets ◽  
Chronic Atrophic Gastritis ◽  
Telomerase Activity ◽  
Network Pharmacology ◽  
Screening And Identification ◽  
Tract Disease

Chronic atrophic gastritis (CAG) is a common and possibly precancerous digestive tract disease. Development of drugs with effect of preventing precancerous lesions draws the eyes of global researchers. Qilianshupi decoction (QLSP) is a Traditional Chinese Medicine (TCM) that is commonly used to treat CAG, but few studies have explored the mechanism of QLSP on treating CAG. This study investigated the molecular targets of the component herbs of QLSP in preventing precancerous lesions based on network pharmacology. Network pharmacology analysis revealed that the 6 herbs regulated multiple CAG-related genes, among which the most important were cancer-related pathway (apoptosis, p53, and VEGF) and epithelial cell signaling in Helicobacter pylori infection. Further animal experiments showed that the expression of survivin and p53 in precancerous lesions of CAG rats was significantly increased which was suppressed by QLSP. Moreover, telomerase activity was inhibited in precancerous lesions of CAG rats, and telomere length of gastric mucosa was increased, which was reversed by QLSP. Our results suggest that the components of QLSP prevents gastric precancerous lesions through decreasing the expression of survivin and p53 and regulating telomerase activity and telomere length in CAG.

Mechanism of E Lian Granule Reversing Chronic Atrophic Gastritis With Intestinal Metaplasia Based on Integrated Pharmacology and GEO Gene Chip

2021 ◽  
Author(s):  
Sizhen Gu ◽  
Yan Xue ◽  
Shigui Xue ◽  
Yini Tang ◽  
Zhehao Hu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Atrophic Gastritis ◽  
Intestinal Metaplasia ◽  
Precancerous Lesions ◽  
Chronic Atrophic Gastritis ◽  
Network Computing ◽  
Active Components ◽  
Gene Chips

Abstract Background: This study aimed to explore the main components and targets of E-Lian granule through which it reversed chronic atrophic gastritis with intestinal metaplasia, based on the traditional Chinese Medicine Integrated Pharmacology Network Computing Research Platform V2.0 (TCMIP V2.0) combined with GEO gene chips. It also aimed to construct various networks to predict and analyze the mechanism of E-Lian granule in treating gastric precancerous lesions. Methods: The effective traditional Chinese medicine components and targets of E-Lian granule prescription were obtained using TCMIP V2.0. The disease targets were collected using the TCMIP V2.0 platform and the verified gene chips in the GEO database, and the “drug components–targets” network, “compound–targets protein interaction network,” and “core compound targets–pathways network” were constructed using Cytoscape 3.6.1. The reliability of the predicted components and targets was verified using Pymol 1.7.2.1 and Autodock Vina 1.1.2 reverse molecular docking. Results: A total of 262 unique active components and 680 potential active targets of E-Lian granule were obtained. Moreover, 2247 unique disease targets of chronic atrophic gastritis with intestinal metaplasia were obtained by searching the “Disease/Symptom Target Database” combined with the GEO chip (GSE78523) and GeneCard database. Further, 178 complex targets and 38 complex core targets were obtained using Venn and Filter, respectively, such as ALB, TNF, PTGS2, RHOA, ESR1, HRAS, JUN, FOS, CASP3 and so forth. The GO and KEGG nrichment analyses showed that E-Lian granule reversed gastric precancerous lesions not only through the direct intervention of the cancer pathway, gastric cancer pathway, and epithelial signal transduction in Helicobacter pylori infection but also through PI3K/AKT, VEGF, MAPK, cAMP, cGMP, Th1/Th2,and other pathways. It also had a significant correlation with cholinergic, 5-hydroxytryptamine, dopaminergic, and other gastrointestinal hormone-related signals. Finally, the core target verified in the GSE78523 chip was successfully used to dock with the active components of E-Lian granules. The reliability of the prediction was also verified. Conclusions: The components and molecular mechanism of E-Lian granule in reversing chronic atrophic gastritis with intestinal metaplasia were predicted by integrated pharmacology, GEO chip, and reverse molecular docking, providing an important theoretical basis for further study of the effective substances and mechanism of E-Lian granule in treating chronic atrophic gastritis.

scholarly journals Systematic Analysis of the Multiple Bioactivities of Green Tea through a Network Pharmacology Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Shoude Zhang ◽  
Lei Shan ◽  
Qiao Li ◽  
Xia Wang ◽  
Shiliang Li ◽  
...  
Keyword(s):  
Green Tea ◽  
Homo Sapiens ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Biologically Active ◽  
Network Pharmacology ◽  
Literature Mining ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Systematic Analysis

During the past decades, a number of studies have demonstrated multiple beneficial health effects of green tea. Polyphenolics are the most biologically active components of green tea. Many targets can be targeted or affected by polyphenolics. In this study, we excavated all of the targets of green tea polyphenolics (GTPs) though literature mining and target calculation and analyzed the multiple pharmacology actions of green tea comprehensively through a network pharmacology approach. In the end, a total of 200Homo sapienstargets were identified for fifteen GTPs. These targets were classified into six groups according to their related disease, which included cancer, diabetes, neurodegenerative disease, cardiovascular disease, muscular disease, and inflammation. Moreover, these targets mapped into 143 KEGG pathways, 26 of which were more enriched, as determined though pathway enrichment analysis and target-pathway network analysis. Among the identified pathways, 20 pathways were selected for analyzing the mechanisms of green tea in these diseases. Overall, this study systematically illustrated the mechanisms of the pleiotropic activity of green tea by analyzing the corresponding “drug-target-pathway-disease” interaction network.

scholarly journals Exploring the Possible Mechanism and Drug Targets of Huang-Qi-Gui-Zhi-Wu-Wu Decoction for the Treatment of Chemotherapy-Induced Peripheral Neuropathy on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Jia-lin Gu ◽  
Guo-li Wei ◽  
Yu-zhu Ma ◽  
Jin-zhi Zhang ◽  
Yi Ji ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Inflammatory Response ◽  
Nerve Injury ◽  
Drug Targets ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Common Side Effect ◽  
Pathway Enrichment Analysis ◽  
Herbal Formula ◽  
Active Components

Chemotherapy-induced peripheral neuropathy (CIPN) is a common side effect of anticancer treatment, which may influence its successful completion. The Huang-Qi-Gui-Zhi-Wu-Wu decoction (HQGZWWD) has been widely used to treat CIPN in China although the pharmacological mechanisms involved have not been clarified. Using the network pharmacology approach, this study investigated the potential pathogenesis of CIPN and the therapeutic mechanisms exerted by the HQGZWWD herbal formula in CIPN. The targets of HQGZWWD were identified using traditional Chinese medicine (TCM) databases (TCMSP and ETCM) and prediction platforms (PharmMapper and TargetNet), and the genes of CIPN were collected by DisGeNET, GeneCards, and literature search. The common target interaction network between herbal formula and diseases was constructed by using Cytoscape. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to reveal the mechanism and efficacy of HQGZWWD in the treatment of CIPN. A total of 153 CIPN-related genes were screened, and a protein-protein interaction (PPI) network with 96 nodes and 424 edges was constructed. Sixty-three active components were retrieved from HQGZWWD, with a herb-composite compound-target network including 748 nodes and 5448 edges. Forty-one targets belong to the above two networks. The analysis of network results and literature review shows that the main pathological processes of CIPN may be the inflammatory response and nerve injury, and HQGZWWD plays a therapeutic role in CIPN by regulating inflammatory response and repairing nerve injury, thus verifying the reliable efficacy of this herbal formula. In addition, we found two new potential therapeutic targets (CDK7 and GSTM2) warranting further investigation. This study fully illustrates that TCM has the characteristics of a multicompound, multitarget, and multipathway treatment, which is of great significance to study the curative effect of herbal formulations.

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

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110167
Author(s):  
Xing-Pan Wu ◽  
Tian-Shun Wang ◽  
Zi-Xin Yuan ◽  
Yan-Fang Yang ◽  
He-Zhen Wu
Keyword(s):  
Molecular Docking ◽  
Target Prediction ◽  
Interaction Network ◽  
Scientific Basis ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Discovery Studio ◽  
The Core ◽  
Pathway Annotation

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.

scholarly journals Network Pharmacology and Molecular Docking Suggest the Mechanism for Biological Activity of Rosmarinic Acid

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Minglong Guan ◽  
Lan Guo ◽  
Hengli Ma ◽  
Huimei Wu ◽  
Xiaoyun Fan
Keyword(s):  
Biological Activity ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Rosmarinic Acid ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis

Rosmarinic acid (RosA) is a natural phenolic acid compound, which is mainly extracted from Labiatae and Arnebia. At present, there is no systematic analysis of its mechanism. Therefore, we used the method of network pharmacology to analyze the mechanism of RosA. In our study, PubChem database was used to search for the chemical formula and the Chemical Abstracts Service (CAS) number of RosA. Then, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to evaluate the pharmacodynamics of RosA, and the Comparative Toxicogenomics Database (CTD) was used to identify the potential target genes of RosA. In addition, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes were carried out by using the web-based gene set analysis toolkit (WebGestalt). At the same time, we uploaded the targets to the STRING database to obtain the protein interaction network. Then, we carried out a molecular docking about targets and RosA. Finally, we used Cytoscape to establish a visual protein-protein interaction network and drug-target-pathway network and analyze these networks. Our data showed that RosA has good biological activity and drug utilization. There are 55 target genes that have been identified. Then, the bioinformatics analysis and network analysis found that these target genes are closely related to inflammatory response, tumor occurrence and development, and other biological processes. These results demonstrated that RosA can act on a variety of proteins and pathways to form a systematic pharmacological network, which has good value in drug development and utilization.

Network pharmacology to unveil the mechanism of Moluodan in the treatment of chronic atrophic gastritis

Phytomedicine ◽  
2021 ◽  
pp. 153837
Author(s):  
Wuai Zhou ◽  
Huan Zhang ◽  
Xin Wang ◽  
Jun Kang ◽  
Wuyan Guo ◽  
...  
Keyword(s):  
Atrophic Gastritis ◽  
Chronic Atrophic Gastritis ◽  
Network Pharmacology

scholarly journals A Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Jiayan Wu ◽  
Shengkun Hong ◽  
Xiankuan Xie ◽  
Wangmi Liu
Keyword(s):  
Lung Cancer ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds

Objective. Dipsaci Radix (DR) has been used to treat fracture and osteoporosis. Recent reports have shown that myeloid cells from bone marrow can promote the proliferation of lung cancer. However, the action and mechanism of DR has not been well defined in lung cancer. The aim of the present study was to define molecular mechanisms of DR as a potential therapeutic approach to treat lung cancer. Methods. Active compounds of DR with oral bioavailability ≥30% and drug-likeness index ≥0.18 were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform. The potential target genes of the active compounds and bone were identified by PharmMapper and GeneCards, respectively. The compound-target network and protein-protein interaction network were built by Cytoscape software and Search Tool for the Retrieval of Interacting Genes webserver, respectively. GO analysis and pathway enrichment analysis were performed using R software. Results. Our study demonstrated that DR had 6 active compounds, including gentisin, sitosterol, Sylvestroside III, 3,5-Di-O-caffeoylquinic acid, cauloside A, and japonine. There were 254 target genes related to these active compounds as well as to bone. SRC, AKT1, and GRB2 were the top 3 hub genes. Metabolisms and signaling pathways associated with these hub genes were significantly enriched. Conclusions. This study indicated that DR could exhibit the anti-lung cancer effect by affecting multiple targets and multiple pathways. It reflects the traditional Chinese medicine characterized by multicomponents and multitargets. DR could be considered as a candidate for clinical anticancer therapy by regulating bone physiological functions.

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 &lt; 0.05). The expression of NP protein and the virus titers in lung were significantly decreased (p &lt; 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 &lt; 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 &lt; 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.

Sign in / Sign up

Export Citation Format

Share Document