基于蛋白互作和关键作用靶点的网络药理学研究当归四逆汤治疗腰椎间盘突出症的作用机理

基于网络药理学探求当归四逆汤作用于腰椎间盘突出症的作用机理.系统检索中药系统药理学技术平台(TCMSP)、中药潜在靶点数据库(TCM-PTD)获取当归四逆汤药物的有效活性成分45个,作用靶点132个,并将得到的靶点与通用蛋白数据库(Uniprot)中载入的基因名称简称进行匹配.通过检索人类基因数据库(GeneCards...     

基于网络药理学和实验验证探讨光甘草定治疗去势抵抗性前列腺癌的作用机制

本研究结合网络药理学、分子对接和体外细胞实验探讨光甘草定治疗去势抵抗性前列腺癌的作用机制。利用中药数据库HERB、TCMIO、TCMSP、PharmMapper和BATMAN-TCM、Swiss Target Prediction数据库共筛选出248个药物靶点,利用DisGeNET数据库收集到683个疾病靶点,通过韦恩图工具获取药物-疾病靶点55个。通过PPI分析以及拓扑学分析得到AKT1、TP53、ESR1、EGFR等10个核心靶点蛋白。使用R studio软件的“clusterProfiler”包进行GO功能富集分析和KEGG通路富集分析,GO富集分析分析得到847个条目(P<0.01),涉及对类固醇激素的反应、蛋白激酶B信号、对营养水平的反应等,KEGG富集分析得到PI3K/AKT信号通路、蛋白聚糖在癌症中的作用、前列腺癌等105个相关信号通路(P<0.01)。运用AutoDock软件进行分子对接,结果表明光甘草定与核心靶点具有较好的结合性。CCK8法检测细胞增殖发现光甘草定可抑制PC-3细胞增殖(P<0.05),流式细胞术和DAPI染色镜下观察发现光甘草定可促...     

基于网络药理学和分子对接探讨苓桂术甘汤治疗冠心病的作用机制

苓桂术甘汤是出自伤寒论的经典名方,临床上对治疗冠心病(coronary heart disease,CHD)具有显著疗效。由于苓桂术甘汤复杂的分子组成和多样的药学活性,且关于其治疗CHD的基础理论研究较少,目前苓桂术甘汤治疗CHD的作用机制和靶点尚未完全阐明。本文采用网络药理学的研究方法探索苓桂术甘汤治疗CHD的作用机制,并利用分子对接验证药物效应分子与靶点间的相互作用。本文通过TCMSP数据库获取苓桂术甘汤中103个有相关靶点信息的活性成分及对应靶点,通过GeneCards数据库和DisGeNET数据库获取4 618个CHD相关靶点蛋白。将苓桂术甘汤与CHD的交集靶点导入到Cytoscape3.9.1软件中构建“苓桂术甘汤-活性成分-CHD作用靶点”网络,并利用STRING数据库获取交集靶点相互作用关系,筛选出AKT1、TP53、STAT3等核心靶点并绘制PPI网络。利用交集靶点在David数据库中进行GO和KEGG富集分析发现,苓桂术甘汤通过调控细胞凋亡、细胞增殖、血管生成、胆固醇代谢、炎症反应以及对脂多糖、缺氧、肿瘤坏死因子的响应等生物学过程和AGE-RAGE、脂质与动脉粥样硬化...     

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...     

基于网络药理学与分子对接技术探讨红花治疗视网膜静脉阻塞的作用机制研究

本文旨在通过网络药理学和分子对接技术探讨红花治疗视网膜静脉阻塞(RVO)的分子作用机制。首先,通过中药系统药理学数据库与分析平台(TCMSP)获取红花的活性成分和潜在作用靶点。然后,利用GeneCards数据库和OMIM数据库收集RVO相关疾病靶点,借助R 3.6.3软件运行R语言获取红花-RVO交集靶点数据集,通过FunRich 3.1.3软件绘制Venn图和Cytoscape 3.7.0软件构建疾病-成分-靶点网络。利用String数据库和Cytoscape 3.7.0软件绘制蛋白互作(PPI)网络。利用Metascape数据库进行GO和KEGG富集分析。最后,利用AutoDock Vina 1.1.2软件对红花主要活性成分与对应关键靶点进行分子对接验证。本研究共筛选得到红花22个活性成分、186个潜在作用靶点及1 842个RVO相关疾病靶点,最终得到128个红花-RVO交集靶点。PPI网络分析表明,AKT1、JUN、IL6、MAPK1、MAPK8、EGF、CXCL8、MMP9等可能是治疗RVO的核心靶点。GO富集分析,共得到生物过程(BP)条目2 000个,分子功能(MF)条目1...     

网络药理学和分子对接技术研究桑黄类真菌对疾病的潜在作用机制

桑黄类真菌是一类极具研究价值的药用真菌。近年来,对于桑黄类真菌的研究,多集中于对某一个物种的成分及药理活性的研究,系统比较桑黄类真菌中成分及药理活性的研究较少。本研究利用网络药理学和分子对接技术从理论上初步探讨了5种桑黄类真菌中化合物与疾病之间的分子作用机制。研究结果表明5种桑黄类真菌(栎木桑黄Sanghuangporus quercicola、鲍姆桑黄Sanghuangporus baumii、粗毛纤孔菌Inonotus hispidus、裂蹄木层孔菌Tropicorus linteus、黑盖木层孔菌Phellinus nigrians)中的39种有效成分,对应潜在靶点588个。KEGG通路富集筛选得到165条通路,分析结果发现这39种化合物的靶点主要分布在与炎症、糖尿病、肝癌、阿尔茨海默病和衰老相关的信号通路上。筛选出桑黄类真菌中抗病的潜在靶点共486个,构建抗病靶点的蛋白互作(PPI)网络,并筛选出LCK、STAT3、PTPN11、STAT1、STAT5B、MAPK1、JAK1、MAPK3、JAK3和JAK2作为关键靶点,构建5种桑黄类真菌-化合物-关键靶点-5种疾病的网络互作图,并进行分子对接验证。筛选出的桑黄类真菌中的12个有效成分均可与这些关键靶点产生相互作用,其中酚类化合物居多,此外二萜类化合物异海松酸与MAPK1结合能力最强。因此,5种桑黄类真菌可以通过多种化合物、多种靶点和多种途径起到抗病的作用,本研究为探索桑黄类真菌治疗和预防疾病潜在机制提供了理论基础。     

基于网络药理学与分子对接探究黄芩有效成分对酒精性肝病的作用机制及效果验证

通过网络药理学和分子对接技术探究中药黄芩治疗酒精性肝病的作用机制,并通过体外细胞实验验证黄芩有效成分对酒精性肝病的治疗效果。在TCMSP、Swiss ADME和Swiss Target Prediction数据库中检索获得黄芩有效成分及其作用靶点;在GeneCards、OMIM、DisGeNET、TTD和PharmGKB数据库中检索获得酒精性肝病相关的疾病靶点;利用String数据库构建靶点相互作用网络;通过Metascape数据库对关键靶点进行京都基因与基因组百科全书(KEGG)通路富集分析、基因本体(GO)富集分析。采用Cytoscape 3.8.0软件构建黄芩治疗酒精性肝病的“有效成分-靶点-通路”互作网络,并筛选出黄芩有效成分和关键靶点进行分子对接。基于网络药理学和分子对接结果,采用体外细胞实验初步验证预测结果。将黄芩有效成分进行ADME筛选后共获得27个,且这27个有效成分可以通过257个基因靶点对酒精性肝病起到治疗作用,其中关键核心靶点有SRC、AKT1、PIK3R1、STAT3、PIK3CA等。KEGG信号通路富集分析结果显示,黄芩治疗酒精性肝病的主要信号通路包括癌症的途...     

基于网络药理学及实验验证探讨益气温阳活血利水中药组分配伍防治慢性心力衰竭作用机制CSCD

利用网络药理学及分子对接预测益气温阳活血利水中药组分配伍防治慢性心力衰竭(chronic heart failure)潜在靶向作用机制。通过文献检索及课题组前期经验,确定黄芪、桂枝、丹参、葶苈子四味益气温阳活血利水代表药物。采用TCMSP、BATMAN-TCM平台筛选四种药物的活性成分并预测相关作用靶点;利用GeneCards、OMIM、TTD数据库筛选CHF相关靶点;通过String数据库构建蛋白互作PPI网络;利用DAVID数据库进行GO分析和KEGG通路分析;通过Cytoscape 3.8.0软件构建网络关系图;通过Autodock vina进行分子对接。共收集得到化合物21个,CHF靶点共10759个,其中黄芪总皂苷、丹参总酚酸、葶苈子水提物及桂皮醛与疾病的交集靶点分别为75、56、163、27个,根据degree值筛选核心靶点40个;GO分析和KEGG通路分析分别将排名靠前的条目可视化;分子对接结果显示四种中药活性成分与核心靶点结合能稳定。动物实验结果显示,组分配伍能改善心功能,降低血浆中B型钠尿肽前体(NT-proBNP)、心肌肌钙蛋白I(cTnI)、升高血清中超氧化物歧化酶(SOD)、降低丙二醛(MDA),改善心肌细胞凋亡。本研究初步揭示了黄芪总皂苷、丹参总酚酸、桂皮醛与葶苈子水提物组分配伍多成分、多靶点、多途径治疗CHF的机制,作用机制可能与细胞凋亡、氧化应激、炎症反应及能量代谢有关。     

基于网络药理学、分子对接及实验验证探讨黄柏治疗痛风的作用机制CSCD

采用网络药理学、分子对接和体外细胞实验探讨黄柏抗痛风(gout)的物质基础与潜在作用机制。首先通过TCMSP数据库获得黄柏主要活性成分及其对应作用靶点信息;通过GeneCards、OMIM、TTD数据库获得痛风相关疾病靶点;将黄柏有效成分对应靶点与痛风靶点取交集,借助STRING平台及Cytoscape3.9.0软件,绘制交集基因蛋白互作(PPI)网络图;利用基因注释与分析平台(Metascape)数据库对核心靶点进行基因本体(GO)功能及京都基因与基因组百科全书(KEGG)通路富集分析,通过微生信云平台对富集结果可视化;借助AutoDock Tools软件对核心成分及关键靶点基因进行分子对接,并对核心化学成分抗痛风炎症作用进行实验验证。共筛选出25个黄柏抗痛风活性成分和70个关键交集靶点,PPI网络分析获得5个关键靶点包括蛋白激酶B1(AKT1)、肿瘤坏死因子(TNF)、过氧化物酶体增生激活受体γ(PPARγ)、白介素6(IL-6)、前列腺素内过氧化物合酶(PTGS 2);GO功能和KEGG通路富集显示,黄柏作用于细胞迁移的正向调控、细胞分化的负调控、炎症反应等生物学过程,调控PI3K-Akt、MAPK等信号通路,进而发挥抗痛风作用。分子对接结果显示,黄柏的5个主要活性成分与关键靶点间存在分子结合位点且结合能较强,均小于-5 kcal/mol;体外实验显示核心化学成分对尿酸钠诱导的炎症反应有较好的抑制作用,本研究初步揭示了黄柏具有多种潜在的抗痛风活性成分,其作用机理可能是通过作用于多靶点和多通路来实现的。     

基于网络药理学和分子对接技术分析六味地黄丸治疗骨质疏松症的作用机制

基于网络药理学和分子对接技术分析六味地黄丸治疗骨质疏松症(osteoporosis,OP)的作用机制.通过TC-MSP数据库进行六味地黄丸潜在化学成分获取和靶点预测,运用TTD、Disgenet、GeneCards数据库预测筛选与骨质疏松症相关的基因,利用Cytoscape 3.7.0软件建立中药-化合物-靶点-疾病可...     

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.     

基于网络药理学探讨丹参-丹皮配伍抗脑缺血损伤的作用机制

本文旨在通过网络药理学和分子对接方法探讨丹参-丹皮活性成分治疗脑卒中的潜在分子机制.首先基于中药系统药理学分析平台筛选丹参、丹皮的活性成分及其作用靶点,利用CTD、TTD和GeneCards数据库收集脑卒中相关靶点.然后将药物和疾病靶点取交集,借助STRING数据库获取靶点间相互作用关系,利用R语言的Cluster-P...     

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.     

Chemical constituents and synergistic anti-gout studies on Eurycoma longifolia and potential mechanisms evaluation based on systemic analysis approach

37 compounds mainly including triterpenoids with the quassinoid skeleton and β-carboline alkaloids have been isolated from the roots of Eurycoma longifolia Jack (EL), which has been used as traditional medicine for a long history. It has been demonstrated that the total extracts from EL could significantly inhibit the joint swelling in MSU-induced acute gout arthritis rat model at middle and high doses (P < 0.05, P < 0.01), as meanwhile, better performance than that of positive control (P < 0.05, P < 0.01) has been observed at the dose of 10 g/kg. Aiming to search potential compounds and probable mechanisms, network pharmacology, molecular docking and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were adopted, leading to the hypothesis of 17 targets related to different pathogenesis of gout and 5 potential compounds (C36, C107, C124, C125 and C130) among 156 selected compounds, playing synergetic role with multiple targets. Instead of the guiding ideology of “a gene, a drug, a disease”, varieties of compounds but not a single one from EL display holistic performance through multiple pathways with multi-targets. It was noteworthy that Xanthine dehydrogenase/oxidase (XDH), Prostaglandin G/H synthase 2 (PTGS2), Fatty acid-binding protein, liver (FABP1), Purine nucleoside phosphorylase (PNP), and Peroxisome proliferator activated receptor alpha (PPARA) were the key targets with intensely interaction. Furthermore, the functional enrichment analysis indicated that EL probably produced the gout protection effects by synergistic regulation in multiple biological pathways, including Toll-like receptor signaling pathway, MAPK signaling pathway, and NOD-like receptor signaling pathway, etc.     

Network pharmacology based anti-diabetic attributes of bioactive compounds from Ocimum gratissimum L. through computational approach

The present research was framed to determine the key compounds present in the plant Ocimum gratissimum L. targeting protein molecules of Diabetes Mellitus (DM) by employing In-silico approaches. Phytochemicals previously reported to be present in this herb were collated through literature survey and public phytochemical databases, and their probable targets were anticipated using BindingDB (p ≥ 0.7). STRING and KEGG pathway databases were employed for pathway enrichment analysis. Homology modelling was executed to elucidate the structures of therapeutic targets. Further, Phytocompounds from O. gratissimum were subjected for docking with four therapeutic targets of DM by using AutoDock vina through POAP pipeline implementation. 30 compounds were predicted to target 136 protein molecules including aldose reductase, DPP4, alpha-amylase, and alpha-glucosidase. Neuroactive ligand-receptor interaction, MAPK, PI3K-Akt, starch and insulin resistance were predicted to have potentially modulation by phytocompounds. Based on the phytocompound’s binding score with the four targets of DM, Rutin scored the lowest binding energy (-11 kcal/mol) with Aldose reductase by forming 17 intermolecular interactions. In conclusion, based on the network and binding score, phytocompounds from O. gratissimum have a synergistic and considerable effect in the management of DM via multi-compound, multi-target, and multi-pathway mechanisms.     

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.     

基于网络药理学的大黄治疗阿尔茨海默病作用机制研究

基于网络药理学探讨大黄治疗阿尔茨海默病(AD)的作用机制.借助TCMSP数据库及Uniprot数据库筛选出大黄有效成分及靶点基因.通过Drugbank、Dis Ge NET和TTD数据库筛选出阿尔茨海默病的靶点基因;成分靶点与疾病靶点映射后使用Cytoscape 3.7.1软件构建药物有效成分-靶点蛋白相互作用网络,使...     

Analysis of metabolic network based on conservation of molecular structure

Recent work has revealed much about chemical reactions inside hundreds of organisms as well as universal characteristics of metabolic networks, which shed light on the evolution of the networks. However, characteristics of individual metabolites have been neglected. For example, some carbohydrates have structures that are decomposed into small molecules by metabolic reactions, but coenzymes such as ATP are mostly preserved. Such differences in metabolite characteristics are important for understanding the universal characteristics of metabolic networks. To quantify the structure conservation of metabolites, we defined the "structure conservation index" (SCI) for each metabolite as the fraction of metabolite atoms restored to their original positions through metabolic reactions. As expected, coenzymes and coenzyme-like metabolites that have reaction loops in the network show a higher SCI. Using the index, we found that the sum of metabolic fluxes is negatively correlated with the structure preservation of metabolite. Also, we found that each reaction path around high SCI metabolites changes independently, while changes in reaction paths involving low SCI metabolites coincide through evolution processes. These correlations may provide a clue to universal properties of metabolic networks.