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 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 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 Molecular Mechanism of Jinchan Oral Liquid in the Treatment of Children with Respiratory Syncytial Virus Pneumonia Based on Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Li Shen ◽  
Yiguo Jiang ◽  
Jinmiao Lu ◽  
Guangfei Wang ◽  
Xiaolan Zhang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Respiratory Syncytial Virus ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Network Pharmacology ◽  
Online Database ◽  
The Core ◽  
Oral Liquid ◽  
Syncytial Virus ◽  
Core Genes

Objective. Exploration of the underlying molecular mechanism of Jinchan Oral Liquid (JOL) in treating children with the respiratory syncytial virus (RSV) pneumonia to provide new evidence for the clinical application. Methods. The active components and target genes of JOL were screened by the TCMSP database. The targets of RSV pneumonia were obtained from the GeneCards, OMIM, DrugBank, and PharmGKB database. Then, we constructed the active component-target network and screened the core genes. The overlaps were screened for PPI network analysis, GO analysis, and KEGG analysis. Finally, result validation was performed by molecular docking. Results. According to the screening criteria of the ADME, 74 active compounds of JOL were obtained; after removing redundant targets, we selected 180 potential targets. By screening the online database, 893 RSV pneumonia-related targets were obtained. A total of 82 overlapping genes were chosen by looking for the intersection. The STRING online database was used to acquire PPI relationships, and 16 core genes were obtained. GO and KEGG analyses showed that the main pathways of JOL in treating RSV pneumonia include TNF signaling pathway and IL17 signaling pathway. The molecular docking results showed that the active compounds of JOL had a good affinity with the core genes. Conclusion. In this study, we preliminarily discussed the main active ingredients, related targets, and pathways of JOL and predicted the pharmacodynamic basis and the potential therapeutic mechanisms of RSV pneumonia. In summary, the network pharmacology strategy may be helpful for the discovery of multitarget drugs against complex diseases.

scholarly journals Molecular mechanism underlying the hypolipidemic effect of Shanmei Capsule based on network pharmacology and molecular docking

2021 ◽  
Vol 29 ◽  
pp. 239-256
Author(s):  
Qian Wang ◽  
Lijing Du ◽  
Jiana Hong ◽  
Zhenlin Chen ◽  
Huijian Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Kegg Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Hypolipidemic Effect ◽  
Active Ingredients ◽  
Pathway Enrichment

BACKGROUND: Shanmei Capsule is a famous preparation in China. However, the related mechanism of Shanmei Capsule against hyperlipidemia has yet to be revealed. OBJECTIVE: To elucidate underlying mechanism of Shanmei Capsule against hyperlipidemia through network pharmacology approach and molecular docking. METHODS: Active ingredients, targets of Shanmei Capsule as well as targets for hyperlipidemia were screened based on database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed via Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 database. Ingredient-target-disease-pathway network was visualized utilizing Cytoscape software and molecular docking was performed by Autodock Vina. RESULTS: Seventeen active ingredients in Shanmei Capsule were screened out with a closely connection with 34 hyperlipidemia-related targets. GO analysis revealed 40 biological processes, 5 cellular components and 29 molecular functions. A total of 15 signal pathways were enriched by KEGG pathway enrichment analysis. The docking results indicated that the binding activities of key ingredients for PPAR-α are equivalent to that of the positive drug lifibrate. CONCLUSIONS: The possible molecular mechanism mainly involved PPAR signaling pathway, Bile secretion and TNF signaling pathway via acting on MAPK8, PPARγ, MMP9, PPARα, FABP4 and NOS2 targets.

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 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.

Investigating the Mechanism of Action of Frankincense against Drug-Induced Liver Injury Using Network Pharmacology and Molecular Docking

2021 ◽  
Vol 18 ◽  
Author(s):  
Yu-cheng Liao ◽  
Jing-wen Wang ◽  
Qian Yang ◽  
Wen-jun Wanga ◽  
Chao Zhao ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Liver Injury ◽  
Mechanism Of Action ◽  
Target Genes ◽  
Network Pharmacology ◽  
Active Components ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Pathway Enrichment ◽  
Core Genes

Background: Frankincense has been used as a traditional medicine in many countries. It is an important herb with multiple targets and therapeutic effects including liver protection. However, its mechanism of action in drug-induced liver injury (DILI) remains unknown. Objective: The purpose of this work was to elucidate the active components, core genes, and molecular mechanism of frankincense in DILI through network pharmacology and molecular docking approaches. Method: The active components of frankincense and its target genes were obtained from the BATMAN-TCM database, and the DILI target genes were obtained from the GeneCards and DrugBank databases. Cytoscape was used to create the compound-shared gene target network. STRING and DAVID software were used to analyze key targets and pathway enrichment. Autodock Vina software was used for molecular docking. Results: Network analysis identified 16 compounds in frankincense and 103 target genes that are highly related to DILI. The core genes in the protein-protein interaction network are INS, IL6, TP53, TNF, SRC, PTGS2, IL1B, CAT, IL10, and IGF1. Furthermore, GO and KEGG pathway enrichment analyses indicated that the effect of frankincense on DILI is related to positive regulation of transcription from RNA polymerase II promoter and inflammatory response. Core pathways such as the HIF-1, TNF, FoxO, PI3K-Akt, and the sphingolipid signaling pathway are closely related to DILI. Conclusion: This study revealed the chemical constituents and pharmacological effects of frankincense and unveiled potential DILI healing targets. This study could provide insights for further development of drugs that specifically target DILI.

Exploring the effect of Polyphyllin I on hepatitis B virus-related liver cancer through network pharmacology and in vitro experiments

2021 ◽  
Vol 24 ◽  
Author(s):  
Shuxian Yu ◽  
Wenhui Gao ◽  
Puhua Zeng ◽  
Chenglong Chen ◽  
Zhuo Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Liver Cancer ◽  
Mechanism Of Action ◽  
Active Ingredient ◽  
Vehicle Group ◽  
Network Pharmacology ◽  
Dependent Manner ◽  
In Vitro Experiments ◽  
Concentration Dependent Manner

Aim and Objective: To investigate the effect of Polyphyllin I (PPI) on HBV-related liver cancer through network pharmacology and in vitro experiments, and to explore its mechanism of action. Materials and Methods: Use bioinformatics software to predict the active ingredient target of PPI and the disease target of liver cancer, and perform active ingredient-disease target analysis. The results of network pharmacology through molecular docking and in vitro experiments can be further verified. The HepG2 receptor cells (HepG2. 2. 15) were transfected with HBV plasmid for observation, with the human liver cancer HepG2 being used as the control. Results: Bioinformatics analysis found that PPI had totally 161 protein targets, and the predicted target and liver cancer targets were combined to obtain 13 intersection targets. The results of molecular docking demonstrated that PPI had good affinity with STAT3, PTP1B, IL2, and BCL2L1. The results of the in vitro experiments indicated that the PPI inhibited cell proliferation and metastasis in a concentration-dependent manner (P<0.01). Compared with the vehicle group, the PPI group of 1.5, 3, and 6 μmol/L can promote the apoptosis of liver cancer to different degrees (P<0.01). Conclusion: The present study revealed the mechanism of PPI against liver cancer through network pharmacology and in vitro experiments. Its mechanism of action is related to the inhibition of PPI on the proliferation of HBV-related liver cancer through promoting the apoptosis of liver cancer cells. Additionally, in vitro experiments have also verified that PPI can promote the apoptosis of HepG2 and HepG2.2.15 cells.

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.

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