scholarly journals Explore the Lipid-Lowering and Weight-Reducing Mechanism of Lotus Leaf Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Guangjiao Zhou ◽  
Xuehua Feng ◽  
Ali Tao
Keyword(s):  
Molecular Docking ◽  
Rna Polymerase Ii ◽  
Regulation Of Gene Expression ◽  
Target Protein ◽  
Lipid Lowering ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Positive Regulation ◽  
Gene Expression Response ◽  
Lotus Leaf

Objective. To predict the target of the active ingredient of lotus leaf for lowering fat and losing weight. Explore its multicomponent, multitarget, multipath mechanism. Methods. Screen the main active ingredients of lotus leaves through the TCMSP database, and use the TCMSP database to predict the potential targets of the active ingredients. Obtain obesity-related targets from the human genome annotation (GeneCards) database. Use Venn software to take the intersection of the two to obtain the effect target of the lotus leaf lipid-lowering and weight-reducing effects. Use Cytoscape 3.6.0 software to construct an effective ingredient-target network. Use the STRING database to construct an intersection target protein interaction (PPI) network, visualize it with Cytoscape 3.6.0 software, and perform network topology analysis to obtain the core target. Use the DAVID database to perform gene ontology (GO) and metabolic pathway (KEGG) enrichment analysis for the above targets. Use AutoDockTools software for molecular docking to verify the binding strength. Results. A total of 15 main active ingredients such as quercetin, isorhamnetin, sitosterol, and kaempferol were obtained, which can act on 135 targets related to obesity. These targets are significantly enriched in multiple GO and KEGG entries such as hypoxia response, positive regulation of gene expression, response to toxic substances, aging, and positive regulation of RNA polymerase II promoter transcription. Molecular docking shows that flavonoids such as quercetin have better binding to the target protein Akt1. Conclusion. The lipid-lowering and weight-reducing effects of lotus leaf embody the characteristics of multicomponent, multitarget, and multipathway of traditional Chinese medicine, which provides a certain scientific basis for the screening and in-depth study of the effective ingredients of lotus leaf.

scholarly journals The Study on the Mechanism of Hugan Tablets in Treating Drug-Induced Liver Injury Induced by Atorvastatin

2021 ◽  
Vol 12 ◽  
Author(s):  
Shujing Lv ◽  
Honghong Yu ◽  
Xinyue Liu ◽  
Xiaoyan Gao
Keyword(s):  
Molecular Docking ◽  
Liver Injury ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Lipid Lowering ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Drug Induced ◽  
Literature Research ◽  
Drug Induced Liver Injury

Atorvastatin is a widely used lipid-lowering drug in the clinic. Research shows that taking long-term atorvastatin has the risk of drug-induced liver injury (DILI) in most patients. Hugan tablets, a commonly used drug for liver disease, can effectively lower transaminase and protect the liver. However, the underlying mechanism of Hugan tablets alleviating atorvastatin-induced DILI remains unclear. To address this problem, comprehensive chemical profiling and network pharmacology methods were used in the study. First, the strategy of “compound−single herb−TCM prescription” was applied to characterize the ingredients of Hugan tablets. Then, active ingredients and potential targets of Hugan tablets in DILI treatment were screened using network pharmacology, molecular docking, and literature research. In the end, the mechanism of Hugan tablets in treating atorvastatin-induced DILI was elucidated. The results showed that Hugan tablets can effectively alleviate DILI induced by atorvastatin in model rats, and 71 compounds were characterized from Hugan tablets. Based on these compounds, 271 potential targets for the treatment of DILI were predicted, and 10 key targets were chosen by characterizing protein–protein interactions. Then, 30 potential active ingredients were screened through the molecular docking with these 10 key targets, and their biological activity was explained based on literature research. Finally, the major 19 active ingredients of Hugan tablets were discovered. In addition, further enrichment analysis of 271 targets indicated that the PI3K-Akt, TNF, HIF-1, Rap1, and FoxO signaling pathways may be the primary pathways regulated by Hugan tablets in treating DILI. This study proved that Hugan tablets could alleviate atorvastatin-induced DILI through multiple components, targets, and pathways.

scholarly journals Network pharmacology and molecular docking study on the active ingredients of qidengmingmu capsule for the treatment of diabetic retinopathy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingxu Zhang ◽  
Jiawei Yang ◽  
Xiulan Zhao ◽  
Ying Zhao ◽  
Siquan Zhu
Keyword(s):  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Hypoxia Inducible Factor ◽  
Enrichment Analysis ◽  
Docking Study ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Active Ingredients ◽  
Molecular Docking Study

AbstractDiabetic retinopathy (DR) is a leading cause of irreversible blindness globally. Qidengmingmu Capsule (QC) is a Chinese patent medicine used to treat DR, but the molecular mechanism of the treatment remains unknown. In this study, we identified and validated potential molecular mechanisms involved in the treatment of DR with QC via network pharmacology and molecular docking methods. The results of Ingredient-DR Target Network showed that 134 common targets and 20 active ingredients of QC were involved. According to the results of enrichment analysis, 2307 biological processes and 40 pathways were related to the treatment effects. Most of these processes and pathways were important for cell survival and were associated with many key factors in DR, such as vascular endothelial growth factor-A (VEGFA), hypoxia-inducible factor-1A (HIF-1Α), and tumor necrosis factor-α (TNFα). Based on the results of the PPI network and KEGG enrichment analyses, we selected AKT1, HIF-1α, VEGFA, TNFα and their corresponding active ingredients for molecular docking. According to the molecular docking results, several key targets of DR (including AKT1, HIF-1α, VEGFA, and TNFα) can form stable bonds with the corresponding active ingredients of QC. In conclusion, through network pharmacology methods, we found that potential biological mechanisms involved in the alleviation of DR by QC are related to multiple biological processes and signaling pathways. The molecular docking results also provide us with sound directions for further experiments.

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.

scholarly journals Elucidating the Mechanisms of Hugan Buzure Granule in the Treatment of Liver Fibrosis via Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yi Zhu ◽  
Ming Qiao ◽  
Jianhua Yang ◽  
Junping Hu
Keyword(s):  
Liver Fibrosis ◽  
Rna Polymerase Ii ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Docking Simulation ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Transcription Activator ◽  
Active Ingredients ◽  
Oxidoreductase Activity

Objective. To holistically explore the latent active ingredients, targets, and related mechanisms of Hugan buzure granule (HBG) in the treatment of liver fibrosis (LF) via network pharmacology. Methods. First, we collected the ingredients of HBG by referring the TCMSP server and literature and filtered the active ingredients though the criteria of oral bioavailability ≥30% and drug-likeness index ≥0.18. Second, herb-associated targets were predicted and screened based on the BATMAN-TCM and SwissTargetPrediction platforms. Candidate targets related to LF were collected from the GeneCards and OMIM databases. Furthermore, the overlapping target genes were used to construct the protein-protein interaction network and “drug-compound-target-disease” network. Third, GO and KEGG pathway analyses were carried out to illustrate the latent mechanisms of HBG in the treatment of LF. Finally, the combining activities of hub targets with active ingredients were further verified based on software AutoDock Vina. Results. A total of 25 active ingredients and 115 overlapping target genes of HBG and LF were collected. Besides, GO enrichment analysis exhibited that the overlapping target genes were involved in DNA-binding transcription activator activity, RNA polymerase II-specific, and oxidoreductase activity. Simultaneously, the key molecular mechanisms of HBG against LF were mainly involved in PI3K-AKT, MAPK, HIF-1, and NF-κB signaling pathways. Also, molecular docking simulation demonstrated that the key targets of HBG for antiliver fibrosis were IL6, CASP3, EGFR, VEGF, and MAPK. Conclusion. This work validated and predicted the underlying mechanisms of multicomponent and multitarget about HBG in treating LF and provided a scientific foundation for further research.

Explore the active ingredients and mechanisms in Musa basjoo pseudostem juice against diabetes based on animal experiment, gas chromatography-mass spectrometer and network pharmacology

2021 ◽  
Vol 24 ◽  
Author(s):  
Feng Xu ◽  
Xiangpei Wang ◽  
Xiujuan Wei ◽  
Teng Chen ◽  
Hongmei Wu
Keyword(s):  
Gas Chromatography ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Mass Spectrometer ◽  
Diabetic Rats ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Oral Glucose ◽  
Active Ingredients ◽  
Polar Parts

Background: Musa basjoo pseudostem juice (MBSJ) is a well-known Chinese medicine, and Miao people use MBSJ to treat diabetes. In this work, the active ingredients and molecular mechanism of MBSJ against diabetes were explored. Methods: Anti-diabetic activity of MBSJ was evaluated using diabetic rats, and then the ingredients in the small-polar parts of MBSJ were analyzed by gas chromatography-mass spectrometer (GC-MS). Targets were obtained from several databases to develop the "ingredient-target-disease" network by Cytoscape. A collaborative analysis was carried out using the tools in Cytoscape and R packages, and molecular docking was also performed. Results: MBSJ improved the oral glucose tolerance and insulin tolerance, and reduced fasting blood glucose, glycosylated hemoglobin, total cholesterol, triglyceride, and low-density lipoprotein levels in the serum of diabetic rats. 13 potential compounds were identified by GC-MS for subsequent analysis, including Dibutyl phthalate, Oleamide, Stigmasterol, Stigmast-4-en-3-one, etc. The anti-diabetic effect of MBSJ was related to multiple signaling pathways, including Neuroactive ligand-receptor interaction, Phospholipase D signaling pathway, Endocrine resistance, Rap1 signaling pathway, EGFR tyrosine kinase inhibitor resistance, etc. Molecular docking at least partially verified the screening results of network pharmacology. Conclusion: MBSJ had good anti-diabetic activity. The small-polar parts of MBSJ were rich in anti-diabetic active ingredients. Furthermore, the analysis results showed that the anti-diabetic effect of the small-polar parts of MBSJ may be the result of multiple components, multiple targets, and multiple pathways. The current research results can provide important support for studying the active ingredients and exploring the underlying mechanism of MBSJ against diabetes.

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 Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ping Yang ◽  
Haifeng He ◽  
Shangfu Xu ◽  
Ping Liu ◽  
Xinyu Bai
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Target Prediction ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

scholarly journals A Network Pharmacology-Based Study on Active Ingredients of Corydalis Rhizoma on Coronary Heart Disease

2020 ◽  
Author(s):  
Ying Li ◽  
Guhang Wei ◽  
Zhenkun Zhuang ◽  
Mingtai Chen ◽  
Changjian Yuan ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Signaling Pathway ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Active Components

Abstract BackgroundCorydalis Rhizoma(CR) showed a high efficacy for coronary heart disease (CHD). However, the interaction between the active ingredients of CR and the targets of CHD has not been unequivocally explained in previous researches. To study the active components and potential targets of Corydalis Rhizoma and to determine the mechanism underlying the exact effect of Corydalis Rhizoma on coronary heart disease, a method of network pharmacology was used.Materials and MethodsThe active components of CR and targets corresponding to each component were scanned out from Traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), and target genes of CHD were searched on GeneCards database and Online Mendelian Inheritance in Man(OMIM) database. The active components and common targets of CR and CHD were used to build the “CR-CHD” network through Cytoscape (version 3.2.1) software as well as protein-protein interaction(PPI) network on String database. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis was executed by clusterProfiler(version 3.8) and DOSE(version 3.6) package on R platform.Results49 active ingredients and 394 relevant targets of CR and the 7173 CHD-related genes were retrieved. 40 common genes were selected for subsequent analysis. Crucial biological processes and pathways were obtained and analyzed, including DNA-binding transcription activator activity, RNA polymerase II-specific, RNA polymerase II transcription factor binding, kinase regulator activity, ubiquitin-like protein ligase binding, fluid shear stress and atherosclerosis, TNF signaling pathway, apoptosis, MAPK signaling pathway and PI3K-Akt signaling pathway.ConclusionsOverall, CR could alleviate CHD through the mechanisms predicted by network pharmacology, laying the foundation for future development of new drugs from traditional Chinese medicine on CHD.

scholarly journals Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jing Xie ◽  
Jun Wu ◽  
Sihui Yang ◽  
Huaijun Zhou
Keyword(s):  
Molecular Docking ◽  
Drug Targets ◽  
Aloe Vera ◽  
Beta Carotene ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Molecule Docking

Background. Aloe vera has long been considered an anticancer herb in different parts of the world. Objective. To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. Methods. The active ingredients and corresponding protein targets of aloe vera were identified from the TCMSP database. Targets related to cancer were obtained from GeneCards and OMIM databases. The anticancer targets of aloe vera were obtained by intersecting the drug targets with the disease targets, and the process was presented in the form of a Venn plot. These targets were uploaded to the String database for protein-protein interaction (PPI) analysis, and the result was visualized by Cytoscape software. Go and KEGG enrichment were used to analyze the biological process of the target proteins. Molecular docking was used to verify the relationship between the active ingredients of aloe vera and predicted targets. Results. By screening and analyzing, 8 active ingredients and 174 anticancer targets of aloe vera were obtained. The active ingredient-anticancer target network constructed by Cytoscape software indicated that quercetin, arachidonic acid, aloe-emodin, and beta-carotene, which have more than 4 gene targets, may play crucial roles. In the PPI network, AKT1, TP53, and VEGFA have the top 3 highest values. The anticancer targets of aloe vera were mainly involved in pathways in cancer, prostate cancer, bladder cancer, pancreatic cancer, and non-small-cell lung cancer and the TNF signaling pathway. The results of molecular docking suggested that the binding ability between TP53 and quercetin was the strongest. Conclusion. This study revealed the active ingredients of aloe vera and the potential mechanism underlying its anticancer effect based on network pharmacology and provided ideas for further research.

scholarly journals Myrtenal and β-caryophyllene oxide screened from Liquidambaris Fructus suppress NLRP3 inflammasome components in rheumatoid arthritis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wen-xuan Li ◽  
Ping Qian ◽  
Yi-tong Guo ◽  
Li Gu ◽  
Jessore Jurat ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Nlrp3 Inflammasome ◽  
Network Pharmacology ◽  
Caryophyllene Oxide ◽  
Active Ingredients ◽  
Caspase 1 ◽  
Tnf Α ◽  
Cartilage Erosion ◽  
And Cartilage

Abstract Background Liquidambaris Fructus (LF) is the infructescence of Liquidambar formosana. In Traditional Chinese Medicine, LF has been used to treat joint pain, a common symptom of arthritis and rheumatism; however, a lack of pharmacological evidence has limited its applications in modern clinics. Therefore, this study aims to explore the protective effect of LF on rheumatoid arthritis (RA) and to identify its active ingredients. Methods Rats with adjuvant-induced arthritis (AIA) were divided into 4 groups and administered petroleum ether extract of LF (PEL), ethyl acetate extract of LF (EEL), water extract of LF (WEL), or piroxicam (PIR) respectively for 3 weeks. Two additional groups were used as normal control (NC) and model control (MC) and administered distilled water as a placebo. The clinical scores for arthritis, bone surface, synovial inflammation and cartilage erosion were used to evaluate the therapeutic efficacy of each treatment. The serum IL-1β and TNF-α level and the expression of NLRP3, IL-1β and caspase-1 p20 in the synovial tissue of AIA rats were evaluated by ELISA and Western blot. The active ingredients of LF were investigated using network pharmacology and molecular docking methods, and their inhibition of NLRP3 inflammasome activation was verified in the human rheumatoid arthritis fibroblast-like synovial cells (RA-FLS) model. Results PEL could alleviate paw swelling, bone and joint destruction, synovial inflammation and cartilage erosion in the AIA rats, with significantly superior efficacy to that of EEL and WEL. PEL reduced IL-1β and TNF-α serum levels, and attenuated the upregulation of NLRP3, IL-1β and caspase-1 p20 expression in the synovial tissue of AIA rats. Network pharmacology and molecular docking results indicated that myrtenal and β-caryophyllene oxide were the main two active ingredients of PEL, and these two compounds showed significant inhibition on TNF-α, NLRP3, IL-1β and caspase-1 p20 expression in RA-FLS. Conclusions Myrtenal and β-caryophyllene oxide screened from PEL could suppress the activation of NLRP3 inflammasome, thereby alleviating RA symptoms.

Sign in / Sign up

Export Citation Format

Share Document