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杏叶治疗高血压病的有效靶点,使用STRING数据库对交集靶点进行蛋白相互作用(PPI)网络预测,筛选发挥治疗作用的关键成分与关键靶点。最后利用DAVID数据库对关键靶点进行GO和KEGG富集分析,揭示银杏叶治疗高血压病的作用机制。对筛选出的关键成分与治疗高血压关键靶点进行分子对接验证。共筛选出银杏叶治疗高血压病的活性成分21个,靶点190个。PPI网络分析结果显示,银杏叶治疗高血压关键成分有槲皮素、山柰酚、木犀草素、异鼠李素、金圣草黄素5个,关键靶点有PTGS2、AKTI、EGFR、TNF等20个。GO和KEGG分析结果显示,银杏叶治疗高血压病的靶点显著富集于乙型肝炎、TNF信号通路、Toll样受体信号通路、HIF-1通路、MAPK信号通路等通路。分子作用结果显示,木犀草素、金圣草黄素、异鼠李素等与PTGS2、AKTI、EFGR具有较强的亲和力。该研究初步揭示了银杏叶具有多成分、多靶点、多通路治疗高血压的潜在作用机制,为银杏叶治疗高血压物质基础及作用机制的进一步研究奠定基础。     

Network Pharmacology and Molecular Docking Reveal the Mechanism of Corydalis saxicola Bunting Total Alkaloids in Treating Radiation-Induced Oral Mucositis

The study aims to explore the effect and mechanism of total alkaloids of Corydalis saxicola Bunting (CSBTA) in the treatment of radiation induced oral mucositis (RIOM) through network pharmacology and molecular docking. The components and corresponding targets of Corydalis saxicola Bunting were screened by literature review. RIOM related targets were obtained in GeneCards. Cytoscape software was used to construct the component-target-pathway network. Protein-Protein Interaction (PPI) networks was constructed by String database. GO and KEGG enrichment analyses were performed by Metascape. AutoDock Vina 4.2 software was used for molecular docking. There were 26 components of CSBTA targeting 61 genes related to RIOM. Through Cytoscape and PPI analysis, 15 core target genes of CSBTA for treating RIOM were identified. GO functional analysis indicated that CSBTA might play a role through kinase binding and protein kinase activation. KEGG pathway analysis showed that the core targets of CSBTA were mainly focused on cancer and reactive oxygen species (ROS) pathway. The results of molecular docking showed that CSBTA had strong binding energy with target protein including SRC, AKT and EGFR. The study demonstrates that CSBTA may treat RIOM by affecting SRC, AKT and EGFR through ROS pathway.     

Network Pharmacology and Molecular Docking Combined to Analyze the Molecular and Pharmacological Mechanism of Pinellia ternata in the Treatment of Hypertension

Hypertension is a cardiovascular disease that causes great harm to health and life, affecting the function of important organs and accompanied by a variety of secondary diseases, which need to be treated with drugs for a long time. P. ternata alone or combination with western medicine has played an important role in traditional Chinese medicine. Although P. ternata is used clinically to treat hypertension, its functional molecular mechanism and pharmacological mechanism have not been elucidated. Therefore, in this study, the potentially effective components, and targets of P. ternata in the treatment of hypertension were screened by the method of network pharmacology, and the mechanism of P. ternata in the treatment of hypertension was analyzed by constructing a component-target relationship network, PPI interaction network, targets’ function analysis, and molecular docking. In the study, 12 potentially effective components and 88 targets were screened, and 3 potential protein modules were found and analyzed after constructing a PPI network using targets. In addition, 10 targets were selected as core targets of the PPI network. After that, the targets were analyzed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, the molecular docking method is used to study the interaction between the targets and the active components. The above evidence shows that the mechanism of P. ternata in the treatment of hypertension is complicated, as it acts in many ways, mainly by affecting nerve signal transmission, cell proliferation, and apoptosis, calcium channels, and so on. The binding between targets and active components mainly depends on Pi bonds and hydrogen bonds. Using the method of network pharmacology and molecular docking to analyze the mechanism of P. ternata in the treatment of hypertension will help to provide a better scientific basis for the combined use of traditional Chinese medicine and western medicine, and will better help to improve the quality of P. ternata and point out its direction.     

甘草抗动脉粥样硬化机制的网络药理学研究

利用网络药理学方法探讨甘草在抗动脉粥样硬化中的分子机制。本研究利用中医药系统药理学数据库和分析平台(traditional Chinese medicine systems pharmacology database and analysis platform,TCMSP)分析甘草中的有效活性成分,并获得有效成分的作用靶点。通过Cytoscape软件构建可视化靶点互相作用网络,对网络中的关键靶点进行基因本体(GO)富集分析和KEGG通路富集分析。结果显示甘草中40种有效活性成分的预测靶点共97个,47个靶点与动脉粥样硬化(AS)相关,其中18个是血管保护药物和脂质修饰药物的作用靶点,表明甘草可作为调控AS发展的药物。基于97个预测靶点的GO富集分析,发现甘草可参与多种生物学过程,尤其是应对外源性刺激,以及参与细胞凋亡等过程。通过构建甘草靶点与AS疾病靶点相互作用网络(PPI),确定了AKT1、MAPK3、MAPK1、JUN和CASP3等关键靶点,并对关键靶点进行KEGG富集分析,结果表明甘草主要影响调控细胞增殖、生存以及凋亡的细胞信号转导相关通路,并激活先天免疫相关信号通路,调节炎性细胞因子释放,从而发挥抗动脉粥样硬化作用。甘草具有多成分、多靶点、多途径的作用特点,主要通过PI3K-AKT信号途径、MAPK信号途径、NOD样受体信号通路调控细胞增殖和凋亡,同时发挥免疫调控作用,从而影响动脉粥样硬化的发展,由此可见,甘草可作为动脉粥样硬化疾病治疗的候选中草药。     

LncRNAs related key pathways and genes in ischemic stroke by weighted gene co-expression network analysis (WGCNA)

BackgroundIschemic stroke (IS) was a significant public health concern and long-chain noncoding RNAs (lncRNAs) were gaining particular importance in stroke biology, however, the potential mechanism of lncRNAs in IS was not fully understood.MethodsIn this study, three diagnosed patients with IS and three controls were selected to establish the lncRNA library. Weighted gene co-expression network analysis (WGCNA) was applied to screen key lncRNA modules associated with IS. The key lncRNAs were identified by module membership (MM) and gene significance (GS). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to identify the key pathways and protein-protein interaction (PPI) network method was used to identify the key genes.ResultsA total of 3627 lncRNAs were investigated, followed by an analysis of 17 modules, and only one module was highly associated with the IS. The top 10 lncRNAs were identified based on GS and MM. KEGG pathways analysis revealed the top two pathways of the Human T cell Lymphotropic Virus-1 (HTLV-1) infection and the mTOR signaling pathway might influence the progress of IS. Further, genes meeting the top two degree (AKT1 and MAPK14) were selected as the hub genes in the PPI network.ConclusionTo summarize, this study identified the key pathways and genes, which might serve as biomarkers and targets for precise diagnosis and treatment of IS in the future.     

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...     

基于转录组的肝豆状核变性调控网络的构建和分析

本研究旨在利用生物信息学方法构建经铜诱导的ATP7B基因敲除HepG2细胞系的转录调控网络。探讨关键转录因子在肝豆状核变性发生、发展中的潜在作用机制。收集公共基因表达数据库(gene expression omnibus, GEO)中包含野生型、ATP7B基因敲除型、铜诱导的野生型和铜诱导的ATP7B基因敲除型HepG2细胞系数据。筛选由铜诱导产生的差异表达基因(differentially expressed genes,DEGs)后进行基因本体论(gene ontology,GO)、京都基因和基因组百科全书(Kyoto encyclopedia of genes and genomes, KEGG)富集分析。基于蛋白相互作用网络,识别疾病关键基因和功能模块,并对关键功能模块中的基因进行富集分析。最后,构建转录调控网络,筛选核心转录因子。共筛选出1 034个差异表达基因,其中上调525个,下调509个。上、下调关键功能模块分别包括了3785个和3931个基因。关键功能模块中的基因主要定位于细胞-基质连接、染色体、剪接复合体、核糖体等区域,共同参与了mRNA加工、组蛋白修饰、RNA剪切...     

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venny2.1.0获取清瘟护肺颗粒防治COVID-19的潜在靶点,利用R语言对潜在靶点进行GO功能和KEGG通路富集分析,并结合文献对富集所得通路进行分析。最后,利用Cytoscape3.7.1软件构建网络图,采用AutoDock4.2.1软件评价清瘟护肺颗粒中潜在药效成分和新型冠状病毒SARS-CoV-23CL水解酶、血管紧张素转化酶II(ACE2)和RNA依赖的RNA聚合酶(RdRp)的结合作用。网络药理学得到清瘟护肺颗粒防治COVID-19的473个活性成分和123个靶点,KEGG结果及文献分析预测到清瘟护肺颗粒可通过调控MAPK、小细胞肺癌、肺结核、PI3K-AKT等多条信号通路而发挥作用,分子对接结果显示清瘟护肺颗粒中潜在药效成分和SARS-CoV-23CL水解酶、ACE2及RdRp具有良好的亲和性。本研究较为全面揭示了清瘟护肺颗粒治疗COVID-19“多成分、多靶点、多通路”的特点,为深入探讨清瘟护肺颗粒治疗COVID-19的作用机制提供参考依据。     

Network pharmacology,molecular docking integrated surface plasmon resonance technology reveals the mechanism of Toujie Quwen Granules against coronavirus disease 2019 pneumonia

BackgroundThe Coronavirus disease 2019 pneumonia broke out in 2019 (COVID-19) and spread rapidly, which causes serious harm to the health of people and a huge economic burden around the world.PurposeIn this study, the network pharmacology, molecular docking and surface plasmon resonance technology (SPR) were used to explore the potential compounds and interaction mechanism in the Toujie Quwen Granules (TQG) for the treatment of coronavirus pneumonia 2019.Study designThe chemical constituents and compound targets of Lonicerae Japonicae Flos, Pseudostellariae Radix, Artemisia Annua L, Peucedani Radix, Forsythiae Fructus, Scutellariae Radix, Hedysarum Multijugum Maxim, Isatidis Folium, Radix Bupleuri, Fritiliariae Irrhosae Bulbus, Cicadae Periostracum, Poria Cocos Wolf, Pseudobulbus Cremastrae Seu Pleiones, Mume Fructus, Figwort Root and Fritillariae Thunbrgii Bulbus in TQG were searched. The target name was translated to gene name using the UniProt database and then the Chinese medicine-compound-target network was constructed. Protein-protein interaction network (PPI), Gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the core targets were performed in the Metascape to predict its mechanism. The top 34 compounds in the Chinese medicine-compound-target network were docked with SARS-CoV-2 3CL enzyme and SARS-­CoV­-2 RNA-dependent RNA polymerase (RdRp) and then the 13 compounds with lowest affinity score were docked with angiotensin-converting enzyme 2 (ACE2), SARS-CoV-2 Spike protein and interleukin 6 to explore its interaction mechanism. Lastly, SPR experiments were done using the quercetin, astragaloside IV, rutin and isoquercitrin, which were screened from the Chinese medicine-compound-target network and molecular docking.ResultsThe Chinese medicine-compound-target network includes 16 medicinal materials, 111 compounds and 298 targets, in which the degree of PTGS2, TNF and IL­6 is higher compared with other targets and which are the disease target exactly. The result of GO function enrichment analysis included the response to the molecule of bacterial origin, positive regulation of cell death, apoptotic signaling pathway, cytokine-mediated signaling pathway, cytokine receptor binding and so on. KEGG pathway analysis enrichment revealed two pathways: signaling pathway­ IL-17 and signaling pathway­ TNF. The result of molecular docking showed that the affinity score of compounds including quercetin, isoquercitrin, astragaloside IV and rutin is higher than other compounds. In addition, the SPR experiments revealed that the quercetin and isoquercitrin were combined with SARS-CoV-2 Spike protein rather than Angiotensin-converting enzyme 2, while astragaloside IV and rutin were combined with ACE2 rather than SARS-CoV-2 Spike protein.ConclusionTQG may have therapeutic effects on COVID-19 by regulating viral infection, immune and inflammation related targets and pathways, in the way of multi-component, multi-target and multi-pathway.     

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。     

Bioactive constituents and the molecular mechanism of Curcumae Rhizoma in the treatment of primary dysmenorrhea based on network pharmacology and molecular docking

BackgroundCurcumae Rhizoma (CR) has a clinical efficacy in activating blood circulation to dissipate blood stasis and has been used for the clinical treatment of qi stagnation and blood stasis (QSBS) primary dysmenorrhea for many years. However, its molecular mechanism is unknown.ObjectiveThe present study aimed to demonstrate the multicomponent, multitarget and multipathway regulatory molecular mechanisms of CR in the treatment of QSBS primary dysmenorrhea.MethodsObservations of pathological changes in uterine tissues and biochemical assays were used to confirm that a rat model was successfully established and that CR was effective in the treatment of QSBS primary dysmenorrhea. The main active components of CR in rat plasma were identified and screened by ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UPLC-Q/TOF-MS). The component-target-disease network and protein-protein interaction (PPI) network of CR were constructed by a network pharmacology approach. Then, we performed Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was adopted to verify the interactions between the core components and targets of CR to confirm the accuracy of the network pharmacology prediction results. Furthermore, we evaluated the bioactive constituents of CR and molecular mechanism of by which CR promote blood circulation and remove blood stasis via platelet tests in vivo and in vitro and Western blot analysis.ResultsThe results of HE staining and biochemical assays of PGF2α, TXB2 and Ca²⁺ showed that CR was effective in the treatment of QSBS primary dysmenorrhea. A total of 36 active components were identified in CR, and 329 common targets were obtained and used to construct the networks. Of these, 14 core components and 10 core targets of CR in the treatment of primary dysmenorrhea were identified. The GO and KEGG enrichment analyses revealed that the common targets were involved in multiple signaling pathways, including the calcium, cAMP, MAPK, and PI3K-Akt signaling pathways, as well as platelet activation, which is closely related to platelet aggregation. The molecular docking results showed that the 14 core components and 10 core targets could bind spontaneously. Two core targets (MAPK1 and CCR5) and 7 core components (Isoprocurcumenol, Curcumadione, Epiprocurcumenol, (+)-Curdione, Neocurdione, Procurcumenol, and 13-Hydroxygermacrone) were closely related to CR in the treatment of primary dysmenorrhea. Furthermore, the in vivo platelet test showed that CR clearly inhibited platelet aggregation. Five core components ((+)-Curdione, Neocurdione, Isoprocurcumenol, Curcumadione and Procurcumenol) obviously inhibited platelet aggregation in vitro. In addition, based on the relationships among the signaling pathways, we confirmed that CR can effectively inhibit the expression of MAPK and PI3K-Akt signaling pathway-related proteins and decrease the protein expression levels of ERK, JNK, MAPK, PI3K, AKT and CCR5, thereby inhibiting platelet aggregation.ConclusionThis study demonstrated the bioactive constituents and mechanisms of CR in promoting blood circulation and removing blood stasis and its multicomponent, multitarget and multipathway treatment characteristics in primary dysmenorrhea. The results provide theoretical evidence for the development and utilization of CR.     

Network pharmacology and molecular docking analyses on Lianhua Qingwen capsule indicate Akt1 is a potential target to treat and prevent COVID‐19

ObjectivesCoronavirus disease 2019 (COVID‐19) is rapidly spreading worldwide. Lianhua Qingwen capsule (LQC) has shown therapeutic effects in patients with COVID‐19. This study is aimed to discover its molecular mechanism and provide potential drug targets.Materials and MethodsAn LQC target and COVID‐19–related gene set was established using the Traditional Chinese Medicine Systems Pharmacology database and seven disease‐gene databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein‐protein interaction (PPI) network were performed to discover the potential mechanism. Molecular docking was performed to visualize the patterns of interactions between the effective molecule and targeted protein.ResultsA gene set of 65 genes was generated. We then constructed a compound‐target network that contained 234 nodes of active compounds and 916 edges of compound‐target pairs. The GO and KEGG indicated that LQC can act by regulating immune response, apoptosis and virus infection. PPI network and subnetworks identified nine hub genes. The molecular docking was conducted on the most significant gene Akt1, which is involved in lung injury, lung fibrogenesis and virus infection. Six active compounds of LQC can enter the active pocket of Akt1, namely beta‐carotene, kaempferol, luteolin, naringenin, quercetin and wogonin, thereby exerting potential therapeutic effects in COVID‐19.ConclusionsThe network pharmacological strategy integrates molecular docking to unravel the molecular mechanism of LQC. Akt1 is a promising drug target to reduce tissue damage and help eliminate virus infection.     

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...     

小儿脓毒症休克相关基因的筛选及网络构建

为探究脓毒症休克与SIRS的差异表达基因及网络的构建,筛选潜在的核心基因,从GEO数据库下载相关基因表达谱GSE26378,数据分为脓毒症休克与SIRS各29个样本,通过在线软件GCBI对其进行标准化及差异基因筛选;对差异基因进行GO分析;基于KEGG进行功能通路分析以及基因信号网络分析;差异基因共表达网络分析。结果表明:两组中总共有1 456个基因被识别为差异基因(P0.05),与SIRS组相比,脓毒症休克组中有条859条下调基因,597条上调基因。GO功能富集分析显示差异基因主要参与了细胞周期、细胞免疫、细胞代谢。KEGG功能通路分析显示差异基因主要参与了MAPK信号通路、P53信号通路、wnt信号通路、细胞凋亡信号通路,细胞周期受体信号通路等。共表达分析发现基因CCNB1、NUSAP1、OIP5、SHCBP1、ZWINT、TOP2A、DLGAP5等位于网络中央部位,而基因信号网络分析发现基因PLCB1、PIK3CA、STAT3、CAMK2D、PRKCB、CREB1位于网络核心。基因芯片分析有助于发现脓毒症休克与SIRS患儿外周血单核细胞在转录组学上的改变,而生物信息学网络分析有助于发现潜在的靶点。     

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。