scholarly journals Exploring the Mechanisms Underlying the Therapeutic Effect of Salvia Miltiorrhiza Against Diabetic Nephropathy Using Network Pharmacology and Molecular Docking

2020 ◽  
Author(s):  
Li-Li Zhang ◽  
Lin Han ◽  
Xin-Miao Wang ◽  
Yu Wei ◽  
Jing-Hui Zheng ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Molecular Docking ◽  
Therapeutic Effect ◽  
Molecular Mechanisms ◽  
Function Analysis ◽  
Salvia Miltiorrhiza ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Active Ingredients

Abstract BackgroundThe mechanisms underlying the therapeutic effect of Salvia Miltiorrhiza (SM) against diabetic nephropathy (DN) using systematic network pharmacology and molecular docking methods were examined.MethodsTCMSP database was used to screen the active ingredients of SM. Gene targets were obtained using Swiss Target Prediction and TCMSP databases. Related targets of DN were retrieved from the Genecards and DisGeNET databases. Next, a PPI network was constructed using the common targets of SM-DN in the STRING database. The Metascape platform was used for GO function analysis and Cytoscape plug-in ClueGO was used for KEGG pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for mapping the network. ResultsSixty-six active ingredients and 189 targets were screened from SM. Among them, 64 targets overlapped with DN targets. The PPI network diagram revealed that AKT1, VEGFA, IL6, TNF, MAPK1, TP53, EGFR, STAT3, MAPK14, and JUN were the top 10 relevant targets. GO and KEGG analyses mainly focused on advanced glycation end products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that the potential target genes closely related to DN, including TNF, NOS2, and AKT1, were more stable in combination with salvianolic acid B, and their stability was better than that of tanshinone IIA.ConclusionThis study reveals the active components and potential molecular mechanisms involved in the therapeutic effect of SM against DN and provides a reference for the wide application of SM in clinically managing DN.

scholarly journals Exploring the mechanisms underlying the therapeutic effect of Salvia miltiorrhiza on diabetic nephropathy using network pharmacology and molecular docking

2021 ◽  
Author(s):  
Lili Zhang ◽  
Lin Han ◽  
Xinmiao Wang ◽  
Yu Wei ◽  
Jinghui Zheng ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Molecular Docking ◽  
Therapeutic Effect ◽  
Function Analysis ◽  
Salvia Miltiorrhiza ◽  
Tanshinone Iia ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Active Ingredients

The mechanisms underlying the therapeutic effect of Salvia miltiorrhiza (SM) on diabetic nephropathy (DN) were examined using a systematic network pharmacology approach and molecular docking. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to screen active ingredients of SM. Targets were obtained using the SwissTargetPrediction and TCMSP databases. Proteins related to DN were retrieved from the GeneCards and DisGeNET databases. A protein–protein interaction (PPI) network was constructed using common SM/DN targets in the STRING database. The Metascape platform was used for GO function analysis, and the Cytoscape plug-in ClueGO was used for KEGG pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for network mapping. Sixty-six active ingredients and 189 targets of SM were found. Sixty-four targets overlapped with DN-related proteins. The PPI network revealed that AKT1, VEGFA, IL6, TNF, MAPK1, TP53, EGFR, STAT3, MAPK14, and JUN were the 10 most relevant targets. Go and KEGG analyses revealed that the common targets of DN and SM were mainly involved in advanced glycation end products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that potential DN-related targets, includingTNF, NOS2, and AKT1, more stably bound with salvianolic acid B than with tanshinone IIA. In conclusion, this study revealed the active components and potential molecular therapeutic mechanisms of SM in DN and provides a reference for the wide application of SM in clinically managing DN.

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 A Network Pharmacology Approach to Uncover the Mechanisms of Shen-Qi-Di-Huang Decoction against Diabetic Nephropathy

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Sha Di ◽  
Lin Han ◽  
Qing Wang ◽  
Xinkui Liu ◽  
Yingying Yang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Regulation Of Blood Pressure ◽  
Protein Protein Interaction Network

Shen-Qi-Di-Huang decoction (SQDHD), a well-known herbal formula from China, has been widely used in the treatment of diabetic nephropathy (DN). However, the pharmacological mechanisms of SQDHD have not been entirely elucidated. At first, we conducted a comprehensive literature search to identify the active constituents of SQDHD, determined their corresponding targets, and obtained known DN targets from several databases. A protein-protein interaction network was then built to explore the complex relations between SQDHD targets and those known to treat DN. Following the topological feature screening of each node in the network, 400 major targets of SQDHD were obtained. The pathway enrichment analysis results acquired from DAVID showed that the significant bioprocesses and pathways include oxidative stress, response to glucose, regulation of blood pressure, regulation of cell proliferation, cytokine-mediated signaling pathway, and the apoptotic signaling pathway. More interestingly, five key targets of SQDHD, named AKT1, AR, CTNNB1, EGFR, and ESR1, were significant in the regulation of the above bioprocesses and pathways. This study partially verified and predicted the pharmacological and molecular mechanisms of SQDHD on DN from a holistic perspective. This has laid the foundation for further experimental research and has expanded the rational application of SQDHD in clinical practice.

scholarly journals Investigation of Active Ingredients and Mechanism of Sanao Decoction in the Treatment of Chronic Cough by Network Pharmacology

2020 ◽  
Author(s):  
Mengke Sheng ◽  
Xing Liu ◽  
Qingsong Qu ◽  
Xiaowen Wu ◽  
Yuyao Liao ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Chronic Cough ◽  
Fluid Shear Stress ◽  
Oxidant Stress ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Ingredients ◽  
Active Components ◽  
Pathway Network

Abstract Background: Chronic cough significantly affects human health and quality of life. Studies have shown that Sanao Decoction（SAD）can clinically treat chronic cough. To investigate its mechanisms, we used the method of network pharmacology to conduct research at the molecular level.Methods: The active ingredients and their targets were screened by pharmacokinetics parameters from the traditional Chinese medicine system pharmacology analysis platform (TCMSP). The relevant targets of chronic cough were obtained from two databases: GeneCards and DrugBank. Take the intersection to get potential targets of SAD to treat chronic cough and establish the component-target regulatory network by CytoScape3.7.2 and protein-protein interaction (PPI) network by STRING 1.0. The function of the target gene and related pathways were analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) in the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The significant pathways and their relevant targets were obtained and the target-pathway network was established by CytoScape3.7.2. Finally, molecular docking of the core active components and relevant targets was performed.Results: A total of 98 active components, 113 targets were identified. The component-target and target-pathway network of SAD and PPI network were established. Enrichment analysis of DAVID indicated that 2062 terms were in biological processes, 77 in cellular components, 142 in molecular functions and 20 significant pathways. In addition, the molecular docking showed that quercetin and luteolin had a good combination with the corresponding targets.Conclusions: It indicates that the active compounds of SAD, such as quercetin, luteolin, may act on AKT1, MAPK1, RELA, EGFR, BCL2 and regulate PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetic complications and Fluid shear stress and atherosclerosis pathway to exert the effects of anti-inflammatory, anti-airway remodeling, anti-oxidant stress and repair airway damage to treat chronic cough.

scholarly journals Exploration of the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology and molecular docking

2020 ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Postmenopausal Osteoporosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Core Proteins ◽  
Key Genes

Abstract Background: Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease, which poses huge challenges to individuals and society. Ziyin Tongluo Formula (ZYTLF) has been proved effective in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP have not been thoroughly elucidated.Methods: Online databases were used to identify the active ingredients of ZYTLF and corresponding putative targets. Genes associated with PMOP were mined, and then mapped with the putative targets to obtain overlapping genes. Multiple networks were constructed and analyzed, from which the key genes were selected. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analysis. Finally, AutoDock Tools and other software were used for molecular docking of core compounds and key proteins. Results: Ninety-two active compounds of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. Network analysis showed the top 5 active ingredients including quercetin, kaempferol, luteolin, scutellarein, and formononetin., and the top 50 key genes such as VEGFA, MAPK8, AKT1, TNF, ESR1. Enrichment analysis uncovered two significant types of KEGG pathways in PMOP, hormone-related signaling pathways (estrogen , prolactin, and thyroid hormone signaling pathway) and inflammation-related pathways (TNF, PI3K-Akt, and MAPK signaling pathway). Moreover, molecular docking analysis verified that the main active compounds were tightly bound to the core proteins, further confirming the anti-PMOP effects. Conclusions: Based on network pharmacology and molecular docking technology, this study initially revealed the mechanisms of ZYTLF on PMOP, which involves multiple targets and multiple pathways.

scholarly journals Exploring the Mechanisms Underlying the Therapeutic Effect of Xixin Decoction on Alzheimer's Disease Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Zhuo Zhang ◽  
Jiang-lin Xu ◽  
Ming-qing Wei ◽  
Ting Li ◽  
Jing Shi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Therapeutic Effect ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Active Compounds

Abstract Background and objective: Alzheimer’s disease (AD) has been a worldwide problem, not only the treatment but also the prevention. As a commonly used Chinese Herbal Formula, Xixin Decoction (XXD) has significant therapeutic effect on AD but without clear mechanism. This study was aimed to predict the main active compounds and targets of XXD in the treatment of AD and to explore the potential mechanism by using network pharmacology and molecular docking. Methods: The compounds of XXD were searched in the TCMSP and the TCMID database, and the active compounds were screened based on the ADME model and SwissADME platform. SwissTargetPrediction platform was used to search for the primary candidate targets of XXD. The common targets related to AD obtained by two databases (GeneCards and DisGeNET) were determined as candidate proteins involved in AD. To acquire the related targets of XXD in the treatment of AD, the target proteins related to AD were intersected with the predicted targets of XXD. Then these overlapping targets were imported into the STRING database to build PPI network including hub targets; Cytoscape 3.7.2 software was used to construct the topology analysis for the herb-compound-target network diagram while one of it’s plug-in called CytoNCA was used to calculate degree value to screen the main active compounds of XXD. GO and KEGG pathway enrichment analyses were conducted to explore the core mechanism of action and biological pathways associated with the decoction via Metascape platform. We used AutoDock Vina and PyMOL 2.4.0 softwares for molecular docking of hub targets and main compounds.Results: We determined 114 active compounds which meet the conditions of ADME screening, 973 drug targets, and 973 disease targets. However, intersection analysis screened out 208 shared targets. PPI network identified 9 hub targets, including TP53, PIK3CA, MAPK1, MAPK3, STAT3, AKT1, etc. The 10 main active compounds play a major role in treatment of AD by XXD. Hub targets were found to be enriched in 10 KEGG pathways, involving the Pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, Alzheimer's disease, Neuroactive ligand-receptor interaction, Dopaminergic synapse, Serotonergic synapse and MAPK signaling pathway. The docking results indicated that the 8 hub targets exhibit good binding activity with the 9 main active compounds of XXD.Conclusions: We found the advantages of multi-compounds-multi-targets-multi-pathways regulation to reveal the mechanism of XXD for treating AD based on network pharmacology and molecular docking. Our study provided a theorical basis for further clinical application and experimental research of XXD for anti-AD in the future.

scholarly journals Network Pharmacology-Based Systematic Analysis of Molecular Mechanisms of Dingji Fumai Decoction for Ventricular Arrhythmia

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yi Liang ◽  
Bo Liang ◽  
Xin-Rui Wu ◽  
Wen Chen ◽  
Li-Zhi Zhao
Keyword(s):  
Molecular Docking ◽  
Ventricular Arrhythmia ◽  
Molecular Mechanisms ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Systematic Analysis ◽  
Chemical Structures ◽  
Function Modules ◽  
Underlying Mechanisms

Background. Dingji Fumai Decoction (DFD), a traditional herbal mixture, has been widely used to ventricular arrhythmia (VA) in clinical practice in China. However, research on the bioactive components and underlying mechanisms of DFD in VA is still scarce. Methods. Components of DFD were collected from TCMSP, ETCM, and literature. The chemical structures of each component were obtained from PubChem. Next, SwissADME and SwissTargetPrediction were applied for compounds screening and targets prediction of DFD; meanwhile, targets of VA were collected from DrugBank and Online Mendelian Inheritance in Man (OMIM). Then, the H-C-T-D network and the protein-protein interaction (PPI) network were constructed based on the data obtained above. CytoNCA was utilized to filter hub genes and VarElect was used to analyze the relationship between genes and diseases. At last, Metascape was employed for systematic analysis on the potential targets of herbals against VA, and AutoDock was applied for molecular docking to verify the results. Results. A total of 434 components were collected, 168 of which were qualified, and there were 28 shared targets between DFD and VA. Three function modules of DFD were found from the PPI network. Further systematic analysis of shared genes and function modules explained the potential mechanism of DFD in the treatment of VA; molecular docking has verified the interactions. Conclusions. DFD could be employed for VA through mechanisms, including complex interactions between related components and targets, as predicted by network pharmacology and molecular docking. This work confirmed that DFD could apply to the treatment of VA and promoted the explanation of DFD for VA in the molecular mechanisms.

scholarly journals Deciphering the Active Ingredients and Molecular Mechanisms of Tripterygium hypoglaucum (Levl.) Hutch against Rheumatoid Arthritis Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Yunbin Jiang ◽  
Mei Zhong ◽  
Fei Long ◽  
Rongping Yang
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathways ◽  
Molecular Mechanisms ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Clinical Effects ◽  
Overlapping Genes ◽  
Active Ingredients ◽  
Tripterygium Hypoglaucum

Tripterygium hypoglaucum (Levl.) Hutch (THH) shows well clinical effect on rheumatoid arthritis (RA), but the active ingredients and molecular mechanisms remain unclear. This work was designed to explore these issues by network pharmacology. Compounds from THH were gathered by retrieving literatures. Compound-related and RA-related genes were identified using databases, and the overlapping genes were identified by Venn diagram. The active ingredients and genes of THH against RA were confirmed by dissecting interactions between overlapping genes and compounds using Cytoscape. SystemsDock website was used to further verify the combining degree of key genes with active ingredients. Pathway enrichment analysis was performed to decipher the mechanisms of THH against RA by Database for Annotation, Visualization and Integrated Discovery. A total of 123 compounds were collected, and 110 compounds-related and 1871 RA-related genes were identified, including 64 overlapping genes. The target genes and active ingredients of THH against RA comprised 64 genes and 17 compounds, the focus of which was PTGS2, triptolide, and celastrol. SystemsDock website indicated that the combing degree of PTGS2 with triptolide or celastrol was very good. The mechanisms of THH against RA were linked to 31 signaling pathways, and the key mechanism was related to inhibition of inflammation response through inactivating TNF and NF-kappa B signaling pathways. This work firstly explored the active ingredients and mechanisms of THH against RA by network pharmacology and provided evidence to support clinical effects of THH on RA.

scholarly journals A Network Pharmacology Technique to Investigate the Synergistic Mechanisms of Salvia miltiorrhiza and Radix puerariae in Treatment of Cardio-Cerebral Vascular Diseases

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Yang Ma ◽  
Wenjun Wang ◽  
Jiani Yang ◽  
Sha Zhang ◽  
Zhe Li ◽  
...  
Keyword(s):  
Drug Targets ◽  
Salvia Miltiorrhiza ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Radix Puerariae ◽  
Cerebral Vascular

Objective. This study is aimed to analyze the active ingredients, drug targets, and related pathways in the combination of Salvia miltiorrhiza (SM) and Radix puerariae (RP) in the treatment of cardio-cerebral vascular diseases (CCVDs). Method. The ingredients and targets of SM and RP were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the disease targets were obtained from Therapeutic Target Database (TTD), National Center for Biotechnology Information (NCBI), and Online Mendelian Inheritance in Man (OMIM) Database. The synergistic mechanisms of the SM and RP were evaluated by gene ontology (GO) enrichment analyses and Kyoto encyclopedia of genes and genomes (KEGG) path enrichment analyses. Result. A total of 61 active ingredients and 58 common targets were identified in this study. KEGG pathway enrichment analysis results showed that SM- and RP-regulated pathways were mainly inflammatory processes, immunosuppression, and cardiovascular systems. The component-target-pathway network indicated that SM and RP exert a synergistic mechanism for CCVDs through PTGS2 target in PI3k-Akt, TNF, and Jak-STAT signaling pathways. Conclusion. In summary, this study clarified the synergistic mechanisms of SM and RP, which can provide a better understanding of effect in the treatment of CCVDs.

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