scholarly journals Network Pharmacology-Based Analysis of Gegenqinlian Decoction Regulating Intestinal Microbial Activity for the Treatment of Diarrhea

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiaoya Li ◽  
Chenyang Zhang ◽  
Zhoujin Tan ◽  
Jiali Yuan
Keyword(s):  
Molecular Docking ◽  
Microbial Activity ◽  
Herbal Medicines ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
The Core ◽  
Chinese Herbal ◽  
Intestinal Contents ◽  
Heat Syndrome ◽  
Visual Network

Gegenqinlian decoction (GD) has been extensively used for the treatment of diarrhea with intestinal dampness-heat syndrome (IDHS) with a satisfying therapeutic effect. The purpose of this study is to clarify the active ingredients and mechanism of GD in the treatment of diarrhea with IDHS. The TCMSP database was used to screen out the active ingredients of the four Chinese herbal medicines in GD, and the targets of the active ingredients were predicted. We selected the targets related to diarrhea through the DisGeNET database, then used the NCBI database to screen out related targets of lactase and sucrase, and constructed the visual network to search for the active ingredients of GD in the treatment of diarrhea and related mechanisms of the targets. Combined with network pharmacology, we screened out 146 active ingredients in GD corresponding to 252 ingredient targets, combined with 328 disease targets in diarrhea, and obtained 12 lactase targets and 11 sucrase targets. The key active ingredients involved quercetin, formononetin, β-sitosterol kaempferol, and wogonin. Furthermore, molecular docking showed that these five potential active ingredients had good affinities with the core targets PTGS2. The active ingredients in GD (such as quercetin, formononetin, and β-sitosterol) may increase the microbial activity of the intestinal mucosa of mice and reduce the microbial activity of the intestinal contents through multiple targets, thereby achieving the effect of treating diarrhea.

scholarly journals Mechanism of Action of Bu-Fei-Yi-Shen Formula in Treating Chronic Obstructive Pulmonary Disease Based on Network Pharmacology Analysis and Molecular Docking Validation

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Longchuan Wu ◽  
Yu Chen ◽  
Jiao Yi ◽  
Yi Zhuang ◽  
Lei Cui ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Mechanism Of Action ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Chronic Obstructive ◽  
Biological Functions ◽  
Active Ingredients ◽  
Obstructive Pulmonary Disease ◽  
The Core ◽  
Target Network

Objective. To explore the mechanism of action of Bu-Fei-Yi-Shen formula (BFYSF) in treating chronic obstructive pulmonary disease (COPD) based on network pharmacology analysis and molecular docking validation. Methods. First of all, the pharmacologically active ingredients and corresponding targets in BFYSF were mined by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the analysis platform, and literature review. Subsequently, the COPD-related targets (including the pathogenic targets and known therapeutic targets) were identified through the TTD, CTD, DisGeNet, and GeneCards databases. Thereafter, Cytoscape was employed to construct the candidate component-target network of BFYSF in the treatment of COPD. Moreover, the cytoHubba plug-in was utilized to calculate the topological parameters of nodes in the network; then, the core components and core targets of BFYSF in the treatment of COPD were extracted according to the degree value (greater than or equal to the median degree values for all nodes in the network) to construct the core network. Further, the Autodock vina software was adopted for molecular docking study on the core active ingredients and core targets, so as to verify the above-mentioned network pharmacology analysis results. Finally, the Omicshare database was applied in enrichment analysis of the biological functions of core targets and the involved signaling pathways. Results. In the core component-target network of BFYSF in treating COPD, there were 30 active ingredients and 37 core targets. Enrichment analysis suggested that these 37 core targets were mainly involved in the regulation of biological functions, such as response to biological and chemical stimuli, multiple cellular life processes, immunity, and metabolism. Besides, multiple pathways, including IL-17, Toll-like receptor (TLR), TNF, and HIF-1, played certain roles in the effect of BFYSF on treating COPD. Conclusion. BFYSF can treat COPD through the multicomponent, multitarget, and multipathway synergistic network, which provides basic data for intensively exploring the mechanism of action of BFYSF in treating COPD.

scholarly journals Mechanism of Fei-Xian Formula in the Treatment of Pulmonary Fibrosis on the Basis of Network Pharmacology Analysis Combined with Molecular Docking Validation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiao-Li Chen ◽  
Cheng Tang ◽  
Qing-Ling Xiao ◽  
Zhong-Hua Pang ◽  
Dan-Dan Zhou ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virus Infection ◽  
Pulmonary Fibrosis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Molecular Docking Study ◽  
The Core ◽  
Target Network

Objective. This study aimed to clarify the mechanism of Fei-Xian formula (FXF) in the treatment of pulmonary fibrosis based on network pharmacology analysis combined with molecular docking validation. Methods. Firstly, ingredients in FXF with pharmacological activities, together with specific targets, were identified based on the BATMA-TCM and TCMSP databases. Then, targets associated with pulmonary fibrosis, which included pathogenic targets as well as those known therapeutic targets, were screened against the CTD, TTD, GeneCards, and DisGeNet databases. Later, Cytoscape was employed to construct a candidate component-target network of FXF for treating pulmonary fibrosis. In addition, for nodes within the as-constructed network, topological parameters were calculated using CytoHubba plug-in, and the degree value (twice as high as the median degree value for all the nodes) was adopted to select core components as well as core targets of FXF for treating pulmonary fibrosis, which were subsequently utilized for constructing the core network. Furthermore, molecular docking study was carried out on those core active ingredients together with the core targets using AutoDock Vina for verifying results of network pharmacology analysis. At last, OmicShare was employed for enrichment analysis of the core targets. Results. Altogether 12 active ingredients along with 13 core targets were identified from our constructed core component-target network of FXF for the treatment of pulmonary fibrosis. As revealed by enrichment analysis, the 13 core targets mostly concentrated in regulating biological functions, like response to external stimulus (from oxidative stress, radiation, UV, chemical substances, and virus infection), apoptosis, cell cycle, aging, immune process, and protein metabolism. In addition, several pathways, like IL-17, AGE-RAGE, TNF, HIF-1, PI3K-AKT, NOD-like receptor, T/B cell receptor, and virus infection-related pathways, exerted vital parts in FXF in the treatment of pulmonary fibrosis. Conclusions. FXF can treat pulmonary fibrosis through a “multicomponent, multitarget, and multipathway” mean. Findings in this work lay foundation for further exploration of the FXF mechanism in the treatment of pulmonary fibrosis.

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

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

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

scholarly journals Uncovering the Mechanism of the Effects of Pien-Tze-Huang on Liver Cancer Using Network Pharmacology and Molecular Docking

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Shanghui Liu ◽  
Run Wang ◽  
Yan Lou ◽  
Jia Liu
Keyword(s):  
Molecular Docking ◽  
Liver Cancer ◽  
Molecular Mechanism ◽  
Mechanism Of Action ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
The Core ◽  
Molecular Mechanism Of Action ◽  
Pien Tze Huang ◽  
Core Genes

Pien-Tze-Huang (PTH) has a long history in the treatment of liver cancer. However, its molecular mechanism of action remains unclear. TCMSP and TCM were used to collect the active ingredients. Bioactive compounds targets were predicted by reverse pharmacophore models. The antiliver cancer targets of PTH were selected by gene comparison of liver cancer in the GEO database. Molecular docking was used to verify the binding activity of the targets and the active ingredients. The DAVID was used to analyze the gene function and signal pathway. A model was built with Cytoscape. The core genes were obtained by PPI network. We screened the 4 main medicinal ingredients of PTH to obtain 16 active ingredient, 190 potential targets, and 6 core genes. We found that active small molecules exert anticancer effects by multiple pathways. The core genes were involved in multiple biological processes. We also found that eight chemical components play a greater role in inhibiting liver cancer. PTH achieves the effect of inhibiting liver cancer through the synergistic effect of multiple components, multiple targets, and multiple pathways. This study provides a potential scientific basis for further elucidating the molecular mechanism of action of PTH against liver cancer.

scholarly journals Exploring The Mechanism of Action of Herbal Medicine (Gan-Mai-Da-Zao Decoction) For Post-Stroke Depression Based On Network Pharmacology And Molecular Docking

2021 ◽  
Author(s):  
Zhi-Cong Ding ◽  
Fang-Fang Xu ◽  
Qi-Di Sun ◽  
Bin Li ◽  
Neng-Xing Liang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Drug Treatment ◽  
Mechanism Of Action ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Active Components ◽  
Composite Target ◽  
Post Stroke ◽  
The Core ◽  
Post Stroke Depression

Abstract Backgrounds: Post-stroke depression is the most common and serious neuropsychiatric complication occurring after cerebrovascular accidents, seriously endangering human health while also imposing a heavy burden on society. Even so, it is difficult to have drugs to contain the progression of the disease. It’s reported that Gan-Mai-Da-Zao decoction was effective to PSD, but it is unknown on its mechanism of action for PSD. In this study, we aimed to explore the possible mechanisms of action of Gan-Mai-Da-Zao decoction in the treatment of PSD using network pharmacology and molecular docking.Material and methods: We obtained the active components and their targets of all drugs from the public database TCMSP and published articles. Then, we collected the PSD-related targets from GeneCards and OMIM databases. Cytoscape 3.8.2 was applied to construct PPI and composite target disease networks. In parallel, the DAVID database was used to perform GO and KEGG enrichment analysis to obtain the biological processes involved in drug treatment diseases in vivo. Finally, molecular docking was used to verify the association between the main active ingredients and the targets.Results: The network pharmacological analysis of Gan-Mai-Da-Zao decoction for PSD identified 107 active ingredients with important biological effects, including quercetin, luteolin, kaempferol, naringenin, isorhamnetin, etc. A total of 203 potential targets for drug treatment of diseases were screened, including STAT3, JUN, TNF, TPT53, AKT1, EGFR, etc. They were found to be widely enriched in a series of signaling pathways such as TNF, HIF-1, and the Toll-Like receptor. Meanwhile, molecular docking analysis showed that the core active components were tightly bound to the core targets, further confirming their anti-PSD effects.Conclusion: This is a prospective study based on the integration and analysis of large data, using the technology of network pharmacology to explore the feasibility of Gan-Mai-Da-Zao decoction for the treatment of PSD, and successfully validated by molecular docking. It reflects the multi-component and multi-target characteristics of Chinese medicine, and more importantly, it also brings hope to the clinical treatment of PSD.

scholarly journals A Network Pharmacology Approach and Molecular Docking Technology to Uncover the Potential Molecular Mechanism of Astragalus -Scorpion on Prostate Cancer

2021 ◽  
Author(s):  
Litong Wu ◽  
Ying Chen ◽  
Mingjing Chen ◽  
Yueqin Yang ◽  
Zuzhao Che ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Docking ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Disease Network ◽  
The Core ◽  
Target Disease ◽  
The Common

Abstract Objective: To investigate the molecular mechanism of Astragalus-Scorpion in the treatment of prostate cancer by network pharmacology and molecular docking technology.Methods: Using TCMSP, BATMAN-TCM, TCMID and Swiss TargetPrediction Databases to retrieve the active ingredients and corresponding targets of Astragalus-Scorpion. The targets related to prostate cancer were retrieved through GeneCards, so as to obtain the common targets of Astragalus-Scorpion and prostate cancer. The common targets were input into the STRING database for protein interaction analysis. Cytoscape software was used to construct the active “ingredient-target-disease” network, and GO and KEGG enrichment analysis were performed on the common targets. To screen the core ingredients and targets that play therapeutic roles, Autodock software was used for molecular docking verification. Results: 27 active ingredients, 340 potential targets related to active ingredients, 898 targets related to disease and 122 common targets were screened from Astragalus-Scorpion totally. The core targets of PPI network were JUN, AKT1, IL6, MAPK1 and RELA, while the core active ingredients in the active ingredient-target-disease network were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin.762 GO entries and 154 pathways were obtained by enrichment analysis totally. The molecular docking results showed that quercetin binds to AKT1 and RELA, kaempferol to AKT1, and formononetin to RELA, all of which were stable. Conclusion: Quercetin, kaempferol and others in the Astragalus-Scorpion can regulate multiple signaling pathways such as PI3K-Akt signaling pathway by binding to targets such as AKT1 related to prostate cancer, inhibit the proliferation of tumor to play a role for prostate cancer.

scholarly journals Exploring the Biological Mechanism of Huang Yam in Treating Tumors and Preventing Antitumor Drug-Induced Cardiotoxicity Using Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hui Zhang ◽  
Wenchao Dan ◽  
Qingyong He ◽  
Jianbo Guo ◽  
Shuang Dai ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Antitumor Drugs ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Ingredients ◽  
Drug Induced ◽  
Anticancer Properties ◽  
The Core

Drugs for the treatment of tumors could result in cardiotoxicity and cardiovascular diseases. We aimed to explore the anticancer properties of Huang yam as well as its cardioprotective properties using network pharmacology and molecular docking technology. The cardiovascular targets of the major chemical components of Huang yam were obtained from the following databases: TCMSP, ETCM, and BATMAN-TCM. The active ingredients of Huang yam were obtained from SwissADME. The cardiovascular targets of antitumor drugs were obtained using GeneCards, OMIM, DrugBank, DisGeNET, and SwissTargetPrediction databases. The drug-disease intersection genes were used to construct a drug-compound-target network using Cytoscape 3.7.1. A protein-protein interaction network was constructed using Cytoscape’s BisoGenet, and the core targets of Huang yam were screened to determine their antitumor properties and identify the cardiovascular targets based on topological parameters. Potential targets were imported into the Metascape platform for GO and KEGG analysis. The results were saved and visualized using R software. The components with higher median values in the network were molecularly docked with the core targets. The network contained 10 compounds, including daucosterol, delusive, dioxin, panthogenin-B, and 124 targets, such as TP53, RPS27A, and UBC. The GO function enrichment analysis showed that there were 478 items in total. KEGG enrichment analysis showed a total of 140 main pathways associated with abnormal transcription of cancer, PI3K-Akt signaling pathway, cell cycle, cancer pathway, ubiquitination-mediated proteolysis, and other pathways. Molecular docking results showed that daucosterol, delusive, dioxin, and panthogenin-B had the highest affinity for TP53, RPS27A, and UBC. The treatment of diseases using traditional Chinese medicine encompasses multiple active ingredients, targets, and pathways. Huang yam has the potential to treat cardiotoxicity caused by antitumor drugs.

scholarly journals The Potential Effect of Rhizoma coptidis on Polycystic Ovary Syndrome Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Liyun Duan ◽  
De Jin ◽  
Xuedong An ◽  
Yuehong Zhang ◽  
Shenghui Zhao ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Polycystic Ovary ◽  
Enrichment Analysis ◽  
Potential Effect ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Core Network ◽  
Active Ingredients ◽  
Rhizoma Coptidis ◽  
The Core

Background. Rhizoma coptidis (RC) showed a significant effect on PCOS, but its mechanism in PCOS remains unclear. Methods. The components of RC were searched by TCMSP. The Smiles number of the active ingredients was queried through PubChem, and the predicted targets were obtained from the SwissTargetPrediction database. The DrugBank, GeneCards, and DisGeNET databases were retrieved to acquire the related targets of PCOS. Then, the network of compound-target was constructed. The core targets were analyzed using protein-protein interaction (PPI) analysis, and the binding activities were verified by molecular docking. The enriched pathways of key targets were examined by GO and KEGG. Results. 13 components and 250 targets of RC on PCOS were screened. The core network was filtered based on topological parameters, and the key components were palmatine, berberine, berberrubine, quercetin, and epiberberine. The key targets included DRD2, SLC6A4, CDK2, DPP4, ESR1, AKT2, PGR, and AKT1. Molecular docking displayed that the active ingredients of RC had good binding activities with potential targets of PCOS. After enrichment analysis, 30 functional pathways were obtained, including neuroactive ligand-receptor interaction, dopaminergic synapse, and cAMP signaling pathway. Conclusion. In summary, this study clarified the potential effect of RC on PCOS, which is helpful to provide references for clinical practice. It is also conducive to the secondary development of RC and its monomer components.

scholarly journals A Network Pharmacology Approach and Molecular Docking Technology to Uncover the Potential Molecular Mechanism of Astragalus -Scorpion on Prostate Cancer

2021 ◽  
Author(s):  
Litong Wu ◽  
Ying Chen ◽  
Minjing Chen ◽  
Yueqin Yang ◽  
Zuzhao Che ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Docking ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Disease Network ◽  
The Core ◽  
Target Disease ◽  
The Common

Abstract Objective: To investigate the molecular mechanism of Astragalus-Scorpion in the treatment of prostate cancer by network pharmacology and molecular docking technology. Methods: Using TCMSP, BATMAN-TCM, TCMID and Swiss TargetPrediction Databases to retrieve the active ingredients and corresponding targets of Astragalus-Scorpion. The targets related to prostate cancer were retrieved through GeneCards, so as to obtain the common targets of Astragalus-Scorpion and prostate cancer. The common targets were input into the STRING database for protein interaction analysis. Cytoscape software was used to construct the active “ingredient-target-disease” network, and GO and KEGG enrichment analysis were performed on the common targets. To screen the core ingredients and targets that play therapeutic roles, Autodock software was used for molecular docking verification. Results: 27 active ingredients, 340 potential targets related to active ingredients, 898 targets related to disease and 122 common targets were screened from Astragalus-Scorpion totally. The core targets of PPI network were JUN, AKT1, IL6, MAPK1 and RELA, while the core active ingredients in the active ingredient-target-disease network were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin.762 GO entries and 154 pathways were obtained by enrichment analysis totally. The molecular docking results showed that quercetin binds to AKT1 and RELA, kaempferol to AKT1, and formononetin to RELA, all of which were stable. Conclusion: Quercetin, kaempferol and others in the Astragalus-Scorpion can regulate multiple signaling pathways such as PI3K-Akt signaling pathway by binding to targets such as AKT1 related to prostate cancer, inhibit the proliferation of tumor to play a role for prostate cancer.

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.

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