scholarly journals Network Pharmacology Analysis of the Identification of Phytochemicals and Therapeutic Mechanisms of Paeoniae Radix Alba for the Treatment of Asthma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jingwei Wang ◽  
Ling Peng ◽  
Lu Jin ◽  
Huiying Fu ◽  
Qiyang Shou
Keyword(s):  
Enrichment Analysis ◽  
Biological Information ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Clinical Effects ◽  
Active Ingredients ◽  
Annotation Database ◽  
Kegg Pathways ◽  
Therapeutic Mechanisms ◽  
Paeoniae Radix

Background. Paeoniae Radix Alba (PRA), the root of the plant Paeonia lactiflora Pall., has been suggested to play an important role for the treatment of asthma. A biochemical understanding of the clinical effects of Paeoniae Radix Alba is needed. Here, we explore the phytochemicals and therapeutic mechanisms via a systematic and comprehensive network pharmacology analysis. Methods. Through TCMSP, PubChem, GeneCards database, and SwissTargetPrediction online tools, potential targets of active ingredients from PRA for the treatment of asthma were obtained. Cytoscape 3.7.2 was used to determine the target of active ingredients of PRA. Target protein interaction (PPI) network was constructed through the STRING database. The Gene Ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genes (KEGG) pathway enrichment analysis were analyzed through the biological information annotation database (DAVID). Results. Our results indicate that PRA contains 21 candidate active ingredients with the potential to treat asthma. The enrichment analysis of GO and KEGG pathways found that the treatment of asthma by PRA may be related to the process of TNF (tumor necrosis factor) release, which can regulate and inhibit multiple signaling pathways such as ceramide signaling. Conclusions. Our work provides a phytochemical basis and therapeutic mechanisms of PRA for the treatment of asthma, which provides new insights on further research on PRA.

scholarly journals Network Pharmacology Analysis on the Mechanism of Huangqi Sijunzi Decoction in Treating Cancer-Related Fatigue

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yixin Cui ◽  
Haiming Wang ◽  
Decai Wang ◽  
Jiwei Mi ◽  
Gege Chen ◽  
...  
Keyword(s):  
Topological Analysis ◽  
Enrichment Analysis ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Cancer Related Fatigue ◽  
Tumor Gene Expression

Objective. This study aimed to determine the active ingredients of Huangqi Sijunzi Decoction (HQSJZD) and the targets in treating cancer-related fatigue (CRF) so as to investigate the treatment mechanism of HQSJZD for CRF. Methods. This study adopted the method of network pharmacology. The active ingredients and targets of HQSJZD were retrieved, and the targets of HQSJZD in treating CRF were obtained using a Venn diagram. Next, a protein-protein interaction (PPI) network was constructed using the String database. The core targets of HQSJZD in treating CRF were identified through topological analysis, and functional annotation analysis and pathway enrichment analysis were carried out. Subsequently, a compound-disease-target regulatory network was constructed using Cystoscape 3.8.0 software. Results. A total of 250 targets of HQSJZD ingredients, 1447 CRF-related genes, and 144 common targets were obtained. Through topological analysis, 61 core targets were screened. Bioinformatics annotation of these genes identified 2366 gene ontology (GO) terms and 172 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Conclusion. The active ingredients in HQSJZD, that is, quercetin, luteolin, kaempferol, and naringenin, may act on AKT1, IL-6, VEGFA, MAPK3, CASP3, JUN, and EGFR to regulate the PI3K-Akt, TNF, and IL-17 signaling pathways, thereby suppressing inflammatory response, tumor gene expression, and tumor angiogenesis to treat CRF. This study investigated the pharmacological basis and mechanism of HQSJZD in the treatment of CRF using systematic pharmacology, which provides an important reference for further elucidation of the anti-CRF mechanism and clinical applications of HQSJZD, and also provides a method protocol for similar studies in the future.

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 Study on the Mechanism of Milkvetch Root in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Chunli Piao ◽  
Qi Zhang ◽  
De Jin ◽  
Li Wang ◽  
Cheng Tang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Systems Pharmacology ◽  
Active Components ◽  
Kegg Pathways

Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. Owing to its complicated pathogenesis, no satisfactory treatment strategies for DN are available. Milkvetch Root is a common traditional Chinese medicine (TCM) and has been extensively used to treat DN in clinical practice in China for many years. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of Milkvetch Root in treating DN has not been completely elucidated. The aim of this study was to explore the active components and potential mechanism of Milkvetch Root by using a systems pharmacology approach. First, the components and targets of Milkvetch Root were analyzed by using the Traditional Chinese Medicine Systems Pharmacology database. We found the common targets of Milkvetch Root and DN constructed a protein-protein interaction (PPI) network using STRING and screened the key targets via topological analysis. Enrichment of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. Subsequently, major hubs were identified and imported to the Database for Annotation, Visualization and Integrated Discovery for pathway enrichment analysis. The binding activity and targets of the active components of Milkvetch Root were verified by using the molecular docking software SYBYL. Finally, we found 20 active components in Milkvetch Root. Moreover, the enrichment analysis of GO and KEGG pathways suggested that AGE-RAGE signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway might be the key pathways for the treatment of DN; more importantly, 10 putative targets of Milkvetch Root (AKT1, VEGFA, IL-6, PPARG, CCL2, NOS3, SERPINE1, CRP, ICAM1, and SLC2A) were identified to be of great significance in regulating these biological processes and pathways. This study provides an important scientific basis for further elucidating the mechanism of Milkvetch Root in treating DN.

scholarly journals Network Pharmacology-based Investigation of the Underlying Mechanism of Panax notoginseng Treatment of Diabetic Retinopathy

2020 ◽  
Vol 23 (4) ◽  
pp. 334-344
Author(s):  
Chunli Piao ◽  
Zheyu Sun ◽  
De Jin ◽  
Han Wang ◽  
Xuemin Wu ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Molecular Mechanisms ◽  
Topological Analysis ◽  
Enrichment Analysis ◽  
Panax Notoginseng ◽  
Diabetic Microangiopathy ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Annotation Database ◽  
Cox 2

Background: Panax notoginseng, a Chinese herbal medicine, has been widely used to treat vascular diseases. Diabetic retinopathy (DR) is one of the complications of diabetic microangiopathy. According to recent studies, the application of Panax notoginseng extract and related Chinese patent medicine preparations can significantly improve DR. However, the pharmacological mechanisms remain unclear. Therefore, the purpose of this study was to decipher the potential mechanism of Panax notoginseng treatment of DR using network pharmacology. Methods: We evaluated and screened the active compounds of Panax notoginseng using the Traditional Chinese Medicine Systems Pharmacology database and collected potential targets of the compounds by target fishing. A multi-source database was also used to organize targets of DR. The potential targets as the treatment of DR with Panax notoginseng were then obtained by matching the compound targets with the DR targets. Using protein-protein interaction networks and topological analysis, interactions between potential targets were identified. In addition, we also performed gene ontology-biological process and pathway enrichment analysis for the potential targets by using the Biological Information Annotation Database. Results: Eight active ingredients of Panax notoginseng and 31 potential targets for the treatment of DR were identified. The screening and enrichment analysis revealed that the treatment of DR using Panax notoginseng primarily involved 28 biological processes and 10 related pathways. Further analyses indicated that angiogenesis, inflammatory reactions, and apoptosis may be the main processes involved in the treatment of DR with Panax notoginseng. In addition, we determined that the mechanism of intervention of Panax notoginseng in treating DR may involve five core targets, VEGFA, MMP-9, MMP-2, FGF2, and COX-2. Conclusion: Panax notoginseng may treat diabetic retinopathy through the mechanism of network pharmacological analysis. The underlying molecular mechanisms were closely related to the intervention of angiogenesis, inflammation, and apoptosis with VEGFA, MMP-9, MMP-2, FGF2, and COX-2 being possible targets.

scholarly journals Identification of the Active Constituents and Significant Pathways of Cangfu Daotan Decoction for the Treatment of PCOS Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Wenting Xu ◽  
Mengyu Tang ◽  
Jiahui Wang ◽  
Lihong Wang
Keyword(s):  
Clinical Symptoms ◽  
Polycystic Ovary ◽  
Endocrine Resistance ◽  
Enrichment Analysis ◽  
Signalling Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Significant Pathway

Background. Polycystic ovary syndrome (PCOS) is the most common female endocrine disease. Cangfu Daotan Decoction (CDD) can effectively relieve the clinical symptoms of PCOS patients. Methods. To explore the active ingredients and related pathways of CDD for treating PCOS, a network pharmacology-based analysis was carried out. The active ingredients of CDD and their potential targets were obtained from the TCM system pharmacology analysis platform. The obtained PCOS-related genes from OMIM and GeneCards were imported to establish protein-protein interaction networks in STRING. Finally, GO analysis and significant pathway analysis were conducted with the RStudio (Bioconductor) database. Results. A total of 111 active compounds were obtained from 1433 ingredients present in the CDD, related to 118 protein targets. In addition, 736 genes were found to be closely related to PCOS, of which 44 overlapped with CDD and were thus considered therapeutically relevant. Pathway enrichment analysis identified the AGE-RAGE signalling pathway in diabetic complications, endocrine resistance, the IL-17 signalling pathway, the prolactin signalling pathway, and the HIF-1 signalling pathway. Moreover, PI3K-Akt, insulin resistance, Toll-like receptor, MAPK, and AGE-RAGE were related to PCOS and treatment. Conclusions. CDD can effectively improve the symptoms of PCOS, and our network pharmacological analysis lays the foundation for future clinical research.

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 Approach to Explore the Potential Mechanisms of Yifei Sanjie Formula in Treating Pulmonary Fibrosis

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Bo Qiao ◽  
Yueying Wu ◽  
Xiaoya Li ◽  
Zhenyuan Xu ◽  
Weigang Duan ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Cell Receptor ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Kegg Pathways ◽  
Th17 Cell Differentiation ◽  
Associated Proteins ◽  
Cellular Components

Objective. Yifei Sanjie Formula (YFSJF) is an effective formula on pulmonary fibrosis (PF), which has been used in clinic for more than 30 years. In order to investigate the molecular mechanism of YFSJF in treating PF, network pharmacology was used to predict the cooperative ingredients and associated pathways. Methods. Firstly, we collected potential active ingredients of YFSJF by TCMSP databases. Secondly, we obtained PF-associated targets through OMIM and Genecards database. Finally, metascape was applied for the analysis of GO terms and KEGG pathways. Results. We screened out 76 potential active ingredients and 98 associated proteins. A total of 5715 items were obtained by GO enrichment analysis ( P < 0.05 ), including 4632 biological processes, 444 cellular components, and 639 molecular functions. A total of 143 related KEGG pathways were enriched ( P < 0.05 ), including IL-17 signaling pathway, T cell receptor signaling pathway, TNF signaling pathway, calcium signaling pathway, TH17 cell differentiation, HIF-1 signaling pathway, and PI3K-Akt signaling pathway. Conclusion. YFSJF can interfere with immune and inflammatory response through multiple targets and pathways, which has a certain role in the treatment of PF. This study lays a foundation for future experimental research.

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 Investigation on the Mechanism of Qubi Formula in Treating Psoriasis Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Lin Zhou ◽  
Lingyun Zhang ◽  
Disheng Tao
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Cellular Response ◽  
Nuclear Translocation ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Core Network ◽  
Active Ingredients ◽  
Pharmacologically Active

Objective. To elucidate the pharmacological mechanisms of Qubi Formula (QBF), a traditional Chinese medicine (TCM) formula which has been demonstrated as an effective therapy for psoriasis in China. Methods. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, BATMAN-TCM database, and literature search were used to excavate the pharmacologically active ingredients of QBF and to predict the potential targets. Psoriasis-related targets were obtained from Therapeutic Target Database (TTD), DrugBank database (DBD), MalaCards database, and DisGeNET database. Then, we established the network concerning the interactions of potential targets of QBF with well-known psoriasis-related targets by using protein-protein interaction (PPI) data in String database. Afterwards, topological parameters (including DNMC, Degree, Closeness, and Betweenness) were calculated to excavate the core targets of Qubi Formula in treating psoriasis (main targets in the PPI network). Cytoscape was used to construct the ingredients-targets core network for Qubi Formula in treating psoriasis, and ClueGO was used to perform GO-BP and KEGG pathway enrichment analysis on these core targets. Results. The ingredient-target-disease core network of QBF in treating psoriasis was screened to contain 175 active ingredients, which corresponded to 27 core targets. Additionally, enrichment analysis suggested that targets of QBF in treating psoriasis were mainly clustered into multiple biological processes (associated with nuclear translocation of proteins, cellular response to multiple stimuli (immunoinflammatory factors, oxidative stress, and nutrient substance), lymphocyte activation, regulation of cyclase activity, cell-cell adhesion, and cell death) and related pathways (VEGF, JAK-STAT, TLRs, NF-κB, and lymphocyte differentiation-related pathways), indicating the underlying mechanisms of QBF on psoriasis. Conclusion. In this work, we have successfully illuminated that Qubi Formula could relieve a wide variety of pathological factors (such as inflammatory infiltration and abnormal angiogenesis) of psoriasis in a “multicompound, multitarget, and multipathway” manner by using network pharmacology. Moreover, our present outcomes might shed light on the further clinical application of QBF on psoriasis treatment.

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