基于网络药理学和分子对接探讨藏麻黄挥发性成分对支气管炎的作用机制

麻黄(Ephedrae Herba)具有发汗散寒、宣肺平喘、利水消肿的功效。现代研究表明麻黄对治疗支气管、哮喘有疗效。藏麻黄(Ephedra saxatilis)为西藏特有的麻黄属植物,其根、茎具有特殊香气,且目前其挥发性成分未有报道。为评价挥发性成分对支气管炎作用,用气质联用仪测定分析藏麻黄根、茎挥发性成分,并结合网络药理学和分子对接方法分析挥发性成分治疗支气管炎的关键靶点。分析检测到67个挥发性化合物,茎中含有挥发性主要成分为2,3,5,6-四甲基吡嗪(10.92%)、Z-9-十五烯醇(9.15%)、二羟基苯乙酮(7.92%);根含有的挥发性主要成分为亚油酸(7.81%)、红没药醇(7.1%)、Z-9-十五烯醇(5.98%)。有34个挥发性成分能够作用32个支气管炎疾病靶点。蛋白互作网络分析预测IL6、TNF、PTGS2、CXCL8为藏麻黄挥发性成分治疗支气管可能的潜在靶点。这些靶点与挥发性成分丁子香酚、月桂酸、反式法尼醇、α-萜品醇、榄香醇和棕榈酸6种化合物靶点相互结合程度高,且分子对接效果好。本研究推测藏麻黄挥发性成分对支气管炎的治疗作用机制可能是通过抑菌作用参与炎症反应,并通过抑制TNF、IL-17、Toll样受体等炎症与免疫信号通路中IL6、TNF、PTGS2、CXCL8的表达,从而起到治疗支气管炎的作用。研究结果为挖掘藏麻黄挥发性成分中治疗支气管炎靶标分子及其产品开发提供重要参考依据。     

基于网络药理学和分子对接技术探究清震汤治疗偏头痛的作用机制

基于网络药理学及分子对接技术探究清震汤治疗偏头痛的作用机制。利用中药系统药理学平台,结合文献报道,获取清震汤中3味中药的活性成分和作用靶点,借助UniProt数据库对靶点蛋白名称进行规范。通过DrugBank、GeneCards等数据库获取偏头痛相关靶点。运用在线Venny作图平台,得到清震汤治疗偏头痛的潜在作用靶点。通过STRING平台构建潜在靶点PPI网络,将所得蛋白互作信息导入Cytoscape 3.7.1进行图像优化及提取核心基因,运用DAVID数据库对潜在作用靶点进行富集分析,采用Cytoscape 3.7.1构建“中药-化合物-靶点-通路”调控网络并进行拓扑分析,使用Autodock软件进行分子对接验证。网络药理学分析结果显示,清震汤中治疗偏头痛可能与槲皮素、山奈酚、豆甾醇等40个化学成分有关,IL6、CXCL8、TNF、PTGS2等为关键靶点。富集分析得到GO条目436条,KEGG通路92条,主要涉及TNF信号通路,神经信号传递通路等。分子对接结果显示,上述活性成分与相关靶点具有较好的结合活性。该研究初步表明,清震汤中多种活性成分通过作用于IL6、CXCL8、TNF、PT...     

基于网络药理学探讨“黄芪-白术-熟地黄”组方防治肾病综合征的作用机制

本研究旨在通过网络药理学方法和分子对接技术探讨黄芪-白术-熟地黄组方(HBS)治疗肾病综合征的作用机制.通过多个数据库获取肾病综合征基因并进行功能模块分解,找出肾病综合征基因参与的主要生物学过程.通过文献以及数据库查找HBS活性成分和基因靶点,筛选出HBS治疗肾病综合征的有效靶点.通过有效靶点的KEGG和GO富集分析,...     

Exploring the mechanism of ellagic acid against gastric cancer based on bioinformatics analysis and network pharmacology

Ellagic acid (EA) is a natural polyphenolic compound. Recent studies have shown that EA has potential anticancer properties against gastric cancer (GC). This study aims to reveal the potential targets and mechanisms of EA against GC. This study adopted methods of bioinformatics analysis and network pharmacology, including the weighted gene co-expression network analysis (WGCNA), construction of protein–protein interaction (PPI) network, receiver operating characteristic (ROC) and Kaplan–Meier (KM) survival curve analysis, Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, molecular docking and molecular dynamics simulations (MDS). A total of 540 EA targets were obtained. Through WGCNA, we obtained a total of 2914 GC clinical module genes, combined with the disease database for screening, a total of 606 GC-related targets and 79 intersection targets of EA and GC were obtained by constructing Venn diagram. PPI network was constructed to identify 14 core candidate targets; TP53, JUN, CASP3, HSP90AA1, VEGFA, HRAS, CDH1, MAPK3, CDKN1A, SRC, CYCS, BCL2L1 and CDK4 were identified as the key targets of EA regulation of GC by ROC and KM curve analysis. The enrichment analysis of GO and KEGG pathways of key targets was performed, and they were mainly enriched in p53 signalling pathway, PI3K-Akt signalling pathway. The results of molecular docking and MDS showed that EA could effectively bind to 13 key targets to form stable protein–ligand complexes. This study revealed the key targets and molecular mechanisms of EA against GC and provided a theoretical basis for further study of the pharmacological mechanism of EA against GC.     

基于网络药理学与分子对接技术的清瘟护肺颗粒防治新型冠状病毒肺炎(COVID-19)的潜在药效物质研究

本文通过网络药理学和分子对接技术探讨清瘟护肺颗粒防治新型冠状病毒肺炎(COVID-19)的潜在药效物质.首先,通过TCMSP数据库,BATMAN-TCM数据库及TCMIP数据库检索清瘟护肺颗粒中十六味药的化学成分及作用靶点,利用GeneCards和OMIM数据库检索COVID-19的相关疾病靶点.然后,通过venny2...     

Molecular mechanism of Ferula asafoetida for the treatment of asthma: Network pharmacology and molecular docking approach

Asthma is a significant health-care burden that has great impact on the quality of life of patients and their families. The limited amount of previously reported data and complicated pathophysiology of asthma make it a difficult to treat and significant economic burden on public healthcare systems. Ferula asafoetida is an herbaceous, monoecious, perennial plant of the Umbelliferae family. In Asia, F. asafoetida is used to treat a range of diseases and disorders, including asthma. Several in vitro studies demonstrated the therapeutic efficacy of F. asafoetida against asthma. Nevertheless, the precise molecular mechanism is yet to be discovered. In the framework of current study, network pharmacology approach was used to identify the bioactive compounds of F. asafoetida in order to better understand its molecular mechanism for the treatment of asthma. In present work, we explored a compound-target-pathway network and discovered that assafoetidin, cynaroside, farnesiferol-B, farnesiferol-C, galbanic-acid, and luteolin significantly influenced the development of asthma by targeting MAPK3, AKT1 and TNF genes. Later, docking analysis revealed that active constituents of F. asafoetida bind stably with three target proteins and function as asthma repressor by regulating the expression of MAPK3, AKT1 and TNF genes. Thus, integration of network pharmacology with molecular docking revealed that F. asafoetida prevent asthma by modulating asthma-related signaling pathways. This study lays the basis for establishing the efficacy of multi-component, multi-target compound formulae, as well as investigating new therapeutic targets for asthma.     

Network pharmacology for the identification of phytochemicals in traditional Chinese medicine for COVID-19 that may regulate interleukin-6

Objective: ´Three formulas and three medicines,’ namely, Jinhua Qinggan Granule, Lianhua Qingwen Capsule, Xuebijing Injection, Qingfei Paidu Decoction, HuaShi BaiDu Formula, and XuanFei BaiDu Granule, were proven to be effective for coronavirus disease 2019 (COVID-19) treatment. The present study aimed to identify the active chemical constituents of this traditional Chinese medicine (TCM) and investigate their mechanisms through interleukin-6 (IL-6) integrating network pharmacological approaches.Methods: We collected the compounds from all herbal ingredients of the previously mentioned TCM, but those that could down-regulate IL-6 were screened through the network pharmacology approach. Then, we modeled molecular docking to evaluate the binding affinity between compounds and IL-6. Furthermore, we analyzed the biological processes and pathways of compounds. Finally, we screened out the core genes of compounds through the construction of the protein–protein interaction network and the excavation of gene clusters of compounds.Results: The network pharmacology research showed that TCM could decrease IL-6 using several compounds, such as quercetin, ursolic acid, luteolin, and rutin. Molecular docking results showed that the molecular binding affinity with IL-6 of all compounds except γ-aminobutyric acid was < −5.0 kJ/mol, indicating the potential of numerous active compounds in TCM to directly interact with IL-6, leading to an anti-inflammation effect. Finally, Cytoscape 3.7.2 was used to topologize the biological processes and pathways of compounds, revealing potential mechanisms for COVID-19 treatment.Conclusion: These results indicated the positive effect of TCM on the prevention and rehabilitation of COVID-19 in at-risk people. Quercetin, ursolic acid, luteolin, and rutin could inhibit COVID-19 by down-regulating IL-6.     

Virtual screening of active compounds from Artemisia argyi and potential targets against gastric ulcer based on Network pharmacology

Artemisia argyi (AA) is one of the renowned herbs in China often used in the treatment of gastric ulcer (GU). Aiming to predict the active compounds and systematically investigate the mechanisms of Artemisia argyi for GU treatment, the approach of network pharmacology, molecular docking, gene ontology (GO) analysis, and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were adopted, respectively, in present study. A total of 13 predicted targets of the 103 compounds in Artemisia argyi were obtained. Sorted by pathogenic mechanisms of targets and structure types of compounds, it was revealed that flavonoids and sesquiterpenes had better performance than monoterpenes. The network analysis showed that Phospholipase a2 (PA21B), Sulfotransferase family cytosolic 2b member 1 (ST2B1), Nitric-oxide synthase, endothelial (NOS3), Gastrin (GAST), neutrophil collagenase (MMP-8), Leukotriene A-4 hydrolase (LKHA4), Urease maturation factor HypB (HYPB), and Periplasmic serine endoprotease DegP (HtrA) were the key targets with intensely interaction. The functional enrichment analysis indicated that AA probably produced the gastric mucosa protection effects by synergistically regulating many biological pathways, such as NF-κB signaling pathway, HIF-1 signaling pathway, TNF signaling pathway, VEGF signaling pathway, and Toll-like receptor signaling pathway, etc. In addition, C73 and C15 might be promising leading compounds with good molecular docking score. As a consequence, this study holistically illuminates the active constituents and mechanisms based on data analysis, which contributes to searching for leading compounds and the development of new drugs for gastric ulcer.     

Anti-Diabetic Effects and Molecular Mechanisms of Amide Alkaloids from Piper longum Based on Network Pharmacology Integrated with Cellular Assays

Piper longum is a well-known spice and traditional medicine. It was revealed to possess anti-diabetic activity, but few information about its active component and underlying mechanism could be available. In this study, retrofractamides A ( 1 ) and C ( 2 ) isolated from P. longum showed potent inhibitory activity against PTP1B. Therefore, the potential mechanism was predicted by network pharmacology and molecular docking. PI3K/AKT was obtained as the most remarkable pathway against type 2 diabetes mellitus (T2DM), and AKT1 and GSK3β were yielded as the top two core targets of retrofractamides A ( 1 ) and C ( 2 ). Molecular docking of compounds with AKT1 and GSK3β showed strong binding affinity between them. Additionally, cellular experiments with a L6 cell model was conducted to further verify the above predictions. Results indicated that retrofractamides A ( 1 ) and C ( 2 ) exerted anti-diabetic effect via activating PI3K/AKT pathway, and they promoted glucose consumption, glucose uptake, glycogen synthesis and glycolysis.     

基于网络药理学及分子对接的浙贝母花-枇杷花药对止咳化痰作用机制研究

采用网络药理学及分子对接阐明浙贝母花—枇杷花药对的止咳化痰作用机制.以口服生物利用度≥30％和类药性≥0.18筛选成分,Swiss Target Prediction数据库进行靶点预测,GenCLiP 3和Drugbank数据库进行疾病靶点分析.以STRING和Cytoscape软件构建成分—靶点互作图,并进行GO、K...     

基于网络药理学和分子对接技术探讨冬虫夏草治疗肾纤维化的潜在作用机制

为了探究冬虫夏草治疗肾纤维化的分子机制,本研究运用网络药理学方法筛选出冬虫夏草抗肾纤维化的活性成分、潜在作用靶点及相关信号通路,并对关键的化合物和靶点进行分子对接。结果表明,冬虫夏草共有22个化合物和364个潜在靶点参与治疗肾纤维化,蛋白互作（PPI）分析出IL-6、TNF-α、MAPK3、EGFR、SRC、CASP3和MAPK1等关键潜在靶点,KEGG通路富集筛选得到163条信号通路。分子对接结果显示,冬虫夏草治疗肾纤维化过程中,其核心化合物金色酰胺醇酯、啤酒甾醇、酒渣碱、花生四烯酸、11,14-二十碳二烯酸分别与PIK3CA、PIK3CB、PIK3CD、MAPK1、MAPK3、RELA等具有良好的结合性能。分析结果显示,冬虫夏草具有通过多成分、多靶点、多通路减缓肾纤维化的潜力,为其抗肾纤维化临床使用提供了一定的依据。     

Exploration of the molecular targets and mechanisms of suxiao xintong dropping pills for myocardial infarction by network pharmacology method

Background: Suxiao Xintong dropping pills (SXXTDP), a traditional Chinese medicine, is widely applied for treating myocardial infarction (MI). However, its therapy mechanisms are still unclear. Therefore, this research is designed to explore the molecular mechanisms of SXXTDP in treating MI.Methods: The active ingredients of SXXTDP and their corresponding genes of the active ingredients were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. MI-related genes were identified via analyzing the expression profiling data (accession number: {"type":"entrez-geo","attrs":{"text":"GSE97320","term_id":"97320"}}GSE97320). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to study the shared genes of drug and disease. Through protein–protein interaction (PPI) network and the Cytoscape plugin cytoHubba, the hub genes were screened out. The compounds and hub targets binding were simulated through molecular docking method.Results: We obtained 21 active compounds and 253 corresponding target genes from TCMSP database. 1833 MI-related genes were identified according to P<0.05 and |log₂FC| ≥ 0.5. 27 overlapping genes between drug and disease were acquired. GO analysis indicated that overlapping genes were mainly enriched in MAP kinase activity and antioxidant activity. KEGG analysis indicated that overlapping genes were mainly enriched in IL-17 signaling pathway and TNF signaling pathway. We obtained 10 hub genes via cytoHubba plugin. Six of the 10 hub genes, including PTGS2, MAPK14, MMP9, MAPK1, NFKBIA, and CASP8, were acted on molecular docking verification with their corresponding compounds of SXXTDP.Conclusion: SXXTDP may exert cardioprotection effect through regulating multiple targets and multiple pathways in MI.     

基于网络药理学和分子对接探索桑白皮治疗糖尿病周围神经病变的潜在机制

本研究运用网络药理学和分子对接方法对中药桑白皮治疗糖尿病周围神经病变(DPN)的活性成分、潜在作用靶点和信号通路进行研究,探索桑白皮治疗DPN的可能作用机制。首先从中药系统药理学数据库(TCMSP)筛选出桑白皮的活性成分及靶点基因。通过GeneCards数据库及OMIM数据库筛选出DPN的疾病靶点基因,并用Cytoscape软件构建"药物-有效成分-靶基因-疾病"中药调控网络图。将有效成分靶标与疾病靶标上传到STRING数据库,构建蛋白互作网络图(PPI),并使用R语言对得到的PPI进行核心基因的筛选。运用R语言对关键靶点进行GO富集分析和KEGG通路富集分析。其次从活性成分及靶点基因中根据degree值筛选出前3个关键成分,并将该网络中的基因靶点以degree值高低进行排序,选择前3个核心靶点,然后从RCSB数据库下载相关蛋白的结构,使用Pymol软件去除溶剂分子与配体,使用AutoDock软件进行分子对接。最后通过酶联免疫吸附实验和荧光光谱实验验证网络药理学富集分析的结果。最终预测到31个桑白皮活性成分,312个活性成分相关靶点,120个桑白皮-糖尿病周围神经病变共同有效靶点。活性...     

基于网络药理学和分子对接探讨银杏叶治疗高血压病潜在作用机制

通过网络药理学和分子对接技术探讨银杏叶治疗高血压的潜在作用机制.首先,通过TCMSP、Swiss Target Prediction、Uniprot等数据库获取银杏叶的化学成分与对应靶点;运用OMIM、DrugBank及Gencards疾病数据库搜索高血压相关靶点.然后,取银杏叶对应靶点与高血压相关靶点的交集即可得到银...     

Mechanisms of Gynostemma pentaphyllum against non‐alcoholic fibre liver disease based on network pharmacology and molecular docking

As a progressive chronic disease, the effective treatment for non‐alcoholic fibre liver disease (NAFLD) has not yet been thoroughly explored at the moment. The widespread use of Gynostemma pentaphyllum (Thunb) for its anti‐insulin resistance effect indicates that potential therapeutic value may be found in Thunb for NAFLD. Hence, this research aims to discover the latent mechanism of Thunb for NAFLD treatment. To achieve the goal of discovering the latent mechanism of Thunb for NAFLD treatment, molecular docking strategy integrated a network phamacology was adopted in the exploration. We acquire Thunb compounds with activeness from TCMSP database. We collect the putative targets of Thunb and NAFLD to generate the network. Key targets and mechanism are screened by PPI analysis, GO and KEGG pathway enrichment analyses. Molecular docking simulation is introduced into the study as assessment method. Through network analysis and virtual screening based on molecular docking, 2 targets (AKT 1 and GSK3B) are identified as key therapeutic targets with satisfying binding affinity. Main mechanism is believed to be the biological process and pathway related to insulin resistance according to the enrichment analyses outcomes. Particularly, the P13K–AKT signalling pathway is recognized as a key pathway of the mechanism. In conclusion, the study shows that Thunb could be a potential treatment against NAFLD and may suppress insulin resistance through the P13K–AKT signalling pathway. The result of the exploration provides a novel perspective for approaching experimental exploration.     

Mechanism of the Anti-Influenza Functions of Guizhi Granules Based on Network Pharmacology,Molecular Docking,and in Vitro Experiments

Guizhi granules mainly treat colds and improve overall health. They are widely used in clinical practice, but their protective effect and anti-inflammatory mechanism against influenza are unclear. In this study, the therapeutic effect of Guizhi granules on influenza was verified in vitro. The active compounds, targets, and cellular pathways of Guizhi granules against influenza were predicted using network pharmacology. The protein-protein interaction and component-target networks identified 5 core targets (JUN, TNF-α, RELA, AKT1, and MAPK1) and components (dihydrocapsaicin, kumatakenin, calycosin, licochalcone A, and berberine). GO and KEGG enrichment analyses revealed the anti-influenza pathways of Guizhi granules as antiviral and anti-inflammatory pathways. Molecular docking further verified that the core targets and components have good or strong binding activity. Therefore, the active ingredients, targets, and molecular mechanisms of Guizhi granules involved in influenza treatment were elucidated.     

Network pharmacology and pharmacokinetics integrated strategy to investigate the pharmacological mechanism of Xianglian pill on ulcerative colitis

BackgroundUlcerative colitis (UC) is a chronic inflammatory bowel disease with high morbidity, which leads to poor quality of life. The Xianglian pill (XLP) is a classical Chinese patent medicine and has been clinically proven to be an effective treatment for UC.PurposeThe pharmacological mechanism of the key bioactive ingredients of XLP for the treatment of UC was investigated by a network pharmacology and pharmacokinetics integrated strategy.Study design and methodsNetwork pharmacology was used to analyze the treatment effect of nine quantified XLP ingredients on UC. Key pathways were enriched and analyzed by protein-protein interaction and Kyoto Encyclopedia of Genes and Genomes analyses. The effect of XLP on Th17 cell differentiation was validated using a mouse model of UC. The binding of nine compounds with JAk2, STAT3, HIF-1α, and HSP90AB1 was assessed using molecular docking. A simple and reliable ultra-high-performance liquid chromatography-tandem mass spectrometry method was developed for the simultaneous quantification of nine ingredients from XLP in plasma and applied to a pharmacokinetic study following oral administration.ResultsNine compounds of XLP, including coptisine, berberine, magnoflorine,berberrubine, jatrorrhizine, palmatine, evodiamine, rutaecarpine, and dehydrocostus lactone, were detected. Network pharmacology revealed 50 crossover genes between the nine compoundsand UC. XLP treats UC mainly by regulating key pathways of the immune system, including Th17 cell differentiation, Jak-Stat, and PI3K-Akt signaling pathways. An in vivo validation in mice found that XLP inhibits Th17 cell differentiation by suppressing the Jak2-Stat3 pathway, which alleviates mucosal inflammation in UC. Molecular docking confirmed that eight compounds are capable of binding with JAk2, HIF-1α, and HSP90AB1, further confirming the inhibitory effect of XLP on the Jak2-Stat3 pathway. Moreover, apharmacokinetic study revealed that the nine ingredients of XLP are exposed in the plasma and colon tissue, which demonstrates its pharmacological effect on UC.ConclusionThis study evaluates the clinical treatment efficacy of XLP for UC. The network pharmacology and pharmacokinetics integrated strategy evaluation paradigm is efficient in discovering the key pharmacological mechanism of herbal formulae.     

基于网络药理学的益母草治疗产后腹痛的潜在分子机制研究

本文通过网络药理学方法探讨益母草治疗产后腹痛的潜在分子机制。首先根据TCMSP数据库和文献挖掘益母草的活性成分,在TCMSP、Swiss Target Prediction、Similarity ensemble approach平台上检索活性成分靶点,在OMIM、GeneCards上检索产后腹痛靶点,得到益母草-产后腹痛交集靶点。利用STRING数据库构建蛋白互作(PPI)网络,接着利用Cytoscape软件对PPI网络进行拓扑分析,并对拓扑分析筛选出的核心靶点进行基因本体论(Gene Ontology,GO)分析和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路分析。最后利用免疫组化实验验证益母草对流产大鼠模型子宫组织中PGF2αR、MMP9、TIMP1、VEGFA、VEGFR2蛋白表达水平的影响。最终得到益母草活性成分10种,与产后腹痛相关靶点144个;通过PPI网络分析筛选出118个靶点,进一步拓扑分析后得到98个节点;然后对这98个节点进行GO和KEGG注释。GO分析得到1151个生物过程(BP)条目,97个细胞组成(CC)条目,122个分子功能(MF)条目;KEGG分析得到41条通路,主要涉及雌激素、PI3K-Akt、MAPK、HIF-1信号通路等。最后免疫组化实验证明益母草可显著抑制流产模型大鼠子宫组织中PGF2αR、MMP9蛋白上调和TIMP1、VEGFR2蛋白下调。本研究通过网络药理学和免疫组化实验验证,显示益母草治疗产后腹痛是多成分、多靶点、多途径相互作用的结果,为益母草的临床应用提供了一定的理论依据。     

基于网络药理学、分子对接和实验验证探讨朱茯苓用于失眠的作用机制

为探讨朱茯苓治疗失眠的可能作用机制,通过TCMSP、BAT-MAN、TCMID和STITCH数据库以及文献挖掘筛选朱茯苓的活性成分及潜在靶点,利用TTD、OMIM、GeneCards和CTD数据库获取失眠类疾病的相关靶点,采用Cyto-scape软件和String数据库构建活性成分-靶点网络和靶点蛋白相互作用网络,通过...