scholarly journals A Systems Pharmacology Approach for Identifying the Multiple Mechanisms of Action for the Rougui-Fuzi Herb Pair in the Treatment of Cardiocerebral Vascular Diseases

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chun Li ◽  
Xia Du ◽  
Yang Liu ◽  
Qi-Qi Liu ◽  
Wen Bing Zhi ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Chinese Herb ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Chinese Herbs ◽  
Pathway Enrichment Analysis ◽  
High Morbidity ◽  
Active Ingredients ◽  
Active Compounds ◽  
System Pharmacology

Cardiocerebral vascular diseases (CCVDs) are the main reasons for high morbidity and mortality all over the world, including atherosclerosis, hypertension, myocardial infarction, stroke, and so on. Chinese herbs pair of the Cinnamomum cassia Presl (Chinese name, rougui) and the Aconitum carmichaelii Debx (Chinese name, fuzi) can be effective in CCVDs, which is recorded in the ancient classic book Shennong Bencao Jing, Mingyibielu and Thousand Golden Prescriptions. However, the active ingredients and the molecular mechanisms of rougui-fuzi in treatment of CCVDs are still unclear. This study was designed to apply a system pharmacology approach to reveal the molecular mechanisms of the rougui-fuzi anti-CCVDs. The 163 candidate compounds were retrieved from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). And 84 potential active compounds and the corresponding 42 targets were obtained from systematic model. The underlying mechanisms of the therapeutic effect for rougui-fuzi were investigated with gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Then, component-target-disease (C-T-D) and target-pathway (T-P) networks were constructed to further dissect the core pathways, potential targets, and active compounds in treatment of CCVDs for rougui-fuzi. We also constituted protein-protein in interaction (PPI) network by the reflect target protein of the crucial pathways against CCVDs. As a result, 21 key compounds, 8 key targets, and 3 key pathways were obtained for rougui-fuzi. Afterwards, molecular docking was performed to validate the reliability of the interactions between some compounds and their corresponding targets. Finally, UPLC-Q-Exactive-MSE and GC-MS/MS were analyzed to detect the active ingredients of rougui-fuzi. Our results may provide a new approach to clarify the molecular mechanisms of Chinese herb pair in treatment with CCVDs at a systematic level.

scholarly journals Systems Pharmacology-Based Research on the Mechanism of Tusizi-Sangjisheng Herb Pair in the Treatment of Threatened Abortion

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Ming Yang ◽  
Jianghe Luo ◽  
Yan Li ◽  
Limian Xu
Keyword(s):  
Molecular Mechanisms ◽  
Transforming Growth Factor ◽  
Chinese Herb ◽  
Enrichment Analysis ◽  
First Trimester ◽  
Chinese Herbs ◽  
Pathway Enrichment Analysis ◽  
Systems Pharmacology ◽  
Mitogen Activated Protein ◽  
Threatened Abortion

Threatened abortion (TA) is a common complication with high incidence in the first trimester of pregnancy, which will end in miscarriage if not treated properly. The Chinese herbs Cuscutae Semen (Tusizi in Chinese) and Herba Taxilli (Sangjisheng in Chinese) first recorded in the ancient classic medical book Shennong Bencao Jing are effective and widely used as an herb pair for the treatment of TA, while the active ingredients and the functional mechanism of Tusizi-Sangjisheng herb pair treating TA are still unknown. In order to exploit the relationship between those two herbs and TA, systems pharmacology analysis was carried out in this study. A total of 75 ingredients of Tusizi-Sangjisheng were collected from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). 12 bioactive compounds were screened, and 153 directly related targets were predicted by systematic models. Besides, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to systematically explore the potential mechanisms of Tusizi-Sangjisheng treating TA. Meanwhile, Compound-Target (C-T), Target-Disease (T-D), and Target-Pathway (T-P) networks were constructed to further quest the underlying functional mechanisms of Tusizi-Sangjisheng. As a result, 31 targets and 3 key pathways were found to be directly related to TA that includes mitogen-activated protein kinases (MAPKs), phosphatidylinositol-3-kinase/protein kinase B (PI3K-Akt), and transforming growth factor-β (TGF-β) signaling pathways. The results in this study may provide some valuable clues about the molecular mechanisms of the efficient Chinese herb pair Tusizi-Sangjisheng in the treatment of TA.

scholarly journals Analysis of MCM Proteins’ Role as a Potential Target of Statins in Patients with Acute Type A Aortic Dissection through Bioinformatics

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 387
Author(s):  
Zheyong Liang ◽  
Yongjian Zhang ◽  
Qiang Chen ◽  
Junjun Hao ◽  
Haichen Wang ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Molecular Mechanisms ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Type A ◽  
Protective Role ◽  
Gene Expression Omnibus ◽  
Pathway Enrichment Analysis ◽  
Acute Type ◽  
Type A Aortic Dissection

Acute aortic dissection is one of the most severe vascular diseases. The molecular mechanisms of aortic expansion and dissection are unclear. Clinical studies have found that statins play a protective role in aortic dissection development and therapy; however, the mechanism of statins’ effects on the aorta is unknown. The Gene Expression Omnibus (GEO) dataset GSE52093, GSE2450and GSE8686 were analyzed, and genes expressed differentially between aortic dissection samples and normal samples were determined using the Networkanalyst and iDEP tools. Weight gene correlation network analysis (WGCNA), functional annotation, pathway enrichment analysis, and the analysis of the regional variations of genomic features were then performed. We found that the minichromosome maintenance proteins (MCMs), a family of proteins targeted by statins, were upregulated in dissected aortic wall tissues and play a central role in cell-cycle and mitosis regulation in aortic dissection patients. Our results indicate a potential molecular target and mechanism for statins’ effects in patients with acute type A aortic dissection.

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 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.

scholarly journals Network pharmacology-based active compounds and pharmacological mechanisms of ginseng for depression in post-COVID-19

2020 ◽  
Author(s):  
Na Wang ◽  
Xianlei Wang ◽  
Mengjiao He ◽  
Wenxiu Zheng ◽  
Xiaoqing Cai ◽  
...  
Keyword(s):  
Immune Regulation ◽  
Enrichment Analysis ◽  
Sudden Onset ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Life Threatening Illness ◽  
Novel Coronavirus

Abstract Introduction: The novel coronavirus disease 2019 (COVID-19) is in the midst of worldwide panic. Sudden onset of an immediate life-threatening illness, quarantine and unemployment caused by epidemic are all contributors to depression. Ginseng has been reported to be an effective and safe clinical treatment on both immune-regulation and anti-depression. However, the mechanism of its anti-depression effect has not been fully characterized. In order to provide theoretical guidance for further clinical application in post-pandemic, we investigated active compounds and pharmacological mechanisms of ginseng to exert anti-depressant activity using network pharmacology, and discussed the active ingredients with immune-regulation and anti-depression.Methods: Information on compounds in ginseng was obtained from public databases, and genes related to depression were gathered using the GeneCards database. Networks of ginseng-associated targets and depression-related genes were constructed through STRING database. Potential targets and pathway enrichment analysis related to the therapeutic efficacy of ginseng for depression were identified using Cytoscape and Database for Annotation, Visualization and Integrated Discovery (DAVID). Results: Network pharmacological analysis of ginseng in treatment of depression identified 16 active ingredients, 47 potential targets, 32 GO terms, and 8 target gene-regulated major pathways. Among them, kaempferol, beta-sitosterol, stigmasterol, fumarine and frutinone A are bioactive compounds and key chemicals. Core genes in PPI network were AKT1, CASP3, NOS3, TNF, and PPARG. Enrichment results revealed that ginseng could regulate multiple aspects of depression through neuroactive ligand-receptor interaction, HIF-1 signaling pathway, and Serotonergic synapse. More importantly, we found that frutinone A and kaempferol are key ingredients in ginseng with dual activities of immune-regulation and anti-depression. Conclusions: We discovered that the therapeutic activities of ginseng for depression mainly involve neurotransmitters, neurotrophic factors, neurogenesis, HPA axis and inflammatory response. Pharmacological network analysis can help to explain the potential effects of ginseng for treating depression, indicating that ginseng is a preferable herb clinically for immune-regulation and anti-depression in post-pandemic.

scholarly journals Network Pharmacology-Based Investigation For Predicting Active Ingredients And Potential Targets Of Strychnos Nux-Vomica L. In Treating Multiple Myeloma

2020 ◽  
Author(s):  
Yan Zhou ◽  
Jianping Shen ◽  
Keting Jin ◽  
Chenjun Lin ◽  
Zirui Hong ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Molecular Mechanisms ◽  
Chinese Herb ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Topological Parameters ◽  
Pharmacological Potential ◽  
Underlying Mechanisms

Abstract Background: Strychnos nux-vomica L. (SN)，a classic Chinese herb, have long been used for the treatment of cancer for many years, However, the pharmacological mechanisms of SN in treatment of Multiple myeloma L.remain vague.The aim of this study was to examine the network pharmacological potential effects of SN on Multiple myeloma using a systems pharmacology approach.Methods: we collected putative targets of SN based on the Traditional Chinese Medicine System Pharmacology database，and oral bioavailability and drug-likeness was screened using absorption, distribution, metabolism, and excretion (ADME) criteria. the network of the interactions among the putative targets of SN and known therapeutic targets of Multiple myeloma was built by using the STITCH database. Then, topological parameters, “Degree” ,“Closeness” and“Betweenness” were calculated to identify the hub targets in the network. Furthermore, the hub targets were imported to the Database for Annotation, Visualization and Integrated Discovery to perform a pathway enrichment analysis.Results: 60 of the identified potential targets of the SN were also Multiple Myeloma- related targets, including 14 putative targets of SN were observed to be major hubs in terms of topological importance.Additionally,the results of pathway enrichment analysis indicated that targets of SN in treating Multiple Myeloma were mainly clustered into multiple biological processes by activating on several signaling pathways(PI3K-Akt, p38-MAPK, Ras/Raf/MEK/ERK pathways), which implied that these were involved in the underlying mechanisms of SN on Multiple Myeloma. Conclusions: Our works successfully explain the potential effects of SN for Multiple Myeloma treatment via the molecular mechanisms predicted by network pharmacology.Moreover,our present outcomes might shed light on the further clinical application of SN in treating Multiple Myeloma.

scholarly journals Predictive Study of the Active Ingredients and Potential Targets of Codonopsis pilosula for the Treatment of Osteosarcoma via Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yu-Bao Gong ◽  
Shao-Jie Fu ◽  
Zheng-Ren Wei ◽  
Jian-Guo Liu
Keyword(s):  
Therapeutic Effect ◽  
Molecular Mechanisms ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Active Compounds ◽  
Primary Bone Tumor ◽  
Invasion And Migration ◽  
Codonopsis Pilosula

Osteosarcoma (OS) is the most common type of primary bone tumor in children and adults. Dangshen (Codonopsis pilosula) is a traditional Chinese medicine commonly used in the treatment of OS worldwide. However, the molecular mechanisms of Dangshen in OS remain unclear. Hence, in this study, we aimed to systematically explore the underlying mechanisms of Dangshen in the treatment of OS. Our study adopted a network pharmacology approach, focusing on the identification of active ingredients, drug target prediction, gene collection, gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and other network tools. The network analysis identified 15 active compounds in Dangshen that were linked to 48 possible therapeutic targets related to OS. The results of the gene enrichment analysis show that Dangshen produces a therapeutic effect in OS likely by regulating multiple pathways associated with DNA damage, cell proliferation, apoptosis, invasion, and migration. Based on the network pharmacology approach, we successfully predicted the active compounds and their respective targets. In addition, we illustrated the molecular mechanisms that mediate the therapeutic effect of Dangshen in OS. These findings may aid in the development of novel targeted therapies for OS in the future.

scholarly journals A Network Pharmacology Approach to Understanding the Mechanisms of Action of Traditional Medicine: Rheum L. for Diabetic Kidney Disease

2020 ◽  
Author(s):  
Jinli Luo ◽  
Chunli Piao ◽  
De Jin ◽  
Li Wang ◽  
Xiaohua Zhao ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Molecular Mechanisms ◽  
Chinese Herb ◽  
Enrichment Analysis ◽  
Peripheral Circulation ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Diabetic Kidney ◽  
Underlying Mechanisms

Abstract BackgroundRheum L. (Da-huang in pinyin, Radix Rhei Et Rhizome in pharmaceutical name), a classic Chinese herb, has been extensively used to treat diabetic kidney disease in clinical practice in China for many years. However, the pharmacological mechanisms of Rheum L. remain elusive. To decrypt the underlying mechanisms of Rheum L. in the treatment of diabetic kidney disease using a systems pharmacology approach. MethodsA network pharmacology-based strategy was proposed to elucidate the underlying multi-component, multi-target, and multi-pathway mode of action of Rheum L. against diabetic kidney disease. We collected putative targets of Rheum L. and a network of the interactions among the putative targets of Rheum L. and known therapeutic targets of diabetic kidney disease was built. The major hubs were imported to the Database to perform a pathway enrichment analysis. ResultsA total of 6 active ingredients and 271 targets of Rheum L. were picked out. 11 cellular biological processes and 18 pathways of Rheum L. mostly associated with inflammatory response, apoptosis, fibrosis, and peripheral circulation. ConclusionsRheum L. could alleviate diabetic kidney disease via the molecular mechanisms predicted by network pharmacology.

scholarly journals Predicting the Molecular Mechanism of Sini Jia Renshen Decoction in Treating Severe COVID-19 Patients Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (12) ◽  
pp. 1934578X2110592
Author(s):  
Yi Wen Liu ◽  
Ai Xia Yang ◽  
Li Lu ◽  
Tie Hua Huang
Keyword(s):  
Molecular Docking ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interactions ◽  
Active Ingredients ◽  
Active Compounds ◽  
Pathway Network ◽  
Function Enrichment Analysis

Objective: To explore the potential mechanism of Sini jia Renshen Decoction (SJRD) in the treatment of COVID-19 based on network pharmacology and molecular docking. Methods: The active compounds and potential therapeutic targets of SJRD were collected through the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). Then a string database was used to build a protein–protein interactions (PPI) network between proteins, and use the David database to perform gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on core targets. Then we used Cytoscape software to construct an active ingredients-core target-signaling pathway network, and finally the active ingredients of SJRD were molecularly docked with the core targets to predict the mechanism of SJRD in the treatment of COVID-19. Results: A total of 136 active compounds, 51 core targets and 93 signaling pathways were selected. Molecular docking results revealed that quercetin, 3,22-dihydroxy-11-oxo-delta(12)-oleanene-27-alpha-methoxycarbonyl-29-oic acid, 18α-hydroxyglycyrrhetic acid, gomisin B and ignavine had considerable binding ability with ADRB2, PRKACA, DPP4, PIK3CG and IL6. Conclusions: This study preliminarily explored the mechanism of multiple components，multiple targets，and multiple pathways of SJRD in the treatment of COVID-19 by network pharmacology．

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.

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