基于网络药理学的柿果药理功能定位及作用机制

基于网络药理学,通过国内外文献检索获取柿果中的化合物,采用Swiss target prediction数据库对化合物进行潜在靶点垂钓以探讨柿果的药理功能定位及作用机制。以Cytoscape软件构建化合物-靶点网络,靶点-疾病名称-疾病分类网络,同时对靶点进行蛋白相互作用(PPI)网络构建,采用DAVID数据库对靶点进行通路富集分析。本研究共收集到柿果中16个化合物,可作用于68个靶点,这些靶点主要作用于心血管疾病、神经精神性疾病等。PPI网络图包含84个节点,226条边,其中degree值排前10的关键蛋白分别为ERS1、PGS2、MMP2、TIMP1、MMP9、MMP1、AR、SLC6A3、PRKCB、CYP19A1。上述靶点可调节氮素代谢、血清素能突触以及TRP通道炎症介质的调节等信号通路。本研究为阐明柿果的药理功能定位及其作用机制研究提供了可靠的依据。     

Integrative analysis of ocular complications in atherosclerosis unveils pathway convergence and crosstalk

Abstract

Atherosclerosis is a life-threatening disease and a major cause of mortalities worldwide. While many of the atherosclerotic sequelae are reflected as microvascular effects in the eye, the molecular mechanisms of their development is not yet known. In this study, we employed a systems biology approach to unveil the most significant events and key molecular mediators of ophthalmic sequelae caused by atherosclerosis. Literature mining was used to identify the proteins involved in both atherosclerosis and ophthalmic diseases. A protein–protein interaction (PPI) network was prepared using the literature-mined seed nodes. Network topological analysis was carried out using Cytoscape, while network nodes were annotated using database for annotation, visualization and integrated discovery in order to identify the most enriched pathways and processes. Network analysis revealed that mitogen-activated protein kinase 1 (MAPK1) and protein kinase C occur with highest betweenness centrality, degree and closeness centrality, thus reflecting their functional importance to the network. Our analysis shows that atherosclerosis-associated ophthalmic complications are caused by the convergence of neurotrophin signaling pathways, multiple immune response pathways and focal adhesion pathway on the MAPK signaling pathway. The PPI network shares features with vasoregression, a process underlying multiple vascular eye diseases. Our study presents a first clear and composite picture of the components and crosstalk of the main pathways of atherosclerosis-induced ocular diseases. The hub bottleneck nodes highlight the presence of molecules important for mediating the ophthalmic complications of atherosclerosis and contain five established drug targets for future therapeutic modulation efforts.     

Identification of drug target candidates of the swine pathogen <Emphasis Type="Italic">Actinobacillus pleuropneumoniae</Emphasis> by construction of protein–protein interaction network

Porcine pleuropneumonia caused by Actinobacillus pleuropneumoniae has led to severe economic losses in the pig industry worldwide. A. pleuropneumoniae displays various levels of antimicrobial resistance, leading to the dire need to identify new drug targets. Protein–protein interaction (PPI) network can aid the identification of drug targets by discovering essential proteins during the life of bacteria. The aim of this study is to identify drug target candidates of A. pleuropneumoniae from essential proteins in PPI network. The homologous protein mapping method (HPM) was utilized to construct A. pleuropneumoniae PPI network. Afterwards, the subnetwork centered with H-NS was selected to verify the PPI network using bacterial two-hybrid assays. Drug target candidates were identified from the hub proteins by analyzing the topology of the network using interaction degree and homologous comparison with the pig proteome. An A. pleuropneumoniae PPI network containing 2737 non-redundant interaction pairs among 533 proteins was constructed. These proteins were distributed in 21 COG functional categories and 28 KEGG metabolic pathways. The A. pleuropneumoniae PPI network was scale free and the similar topological tendencies were found when compared with other bacteria PPI network. Furthermore, 56.3% of the H-NS subnetwork interactions were validated. 57 highly connected proteins (hub proteins) were identified from the A. pleuropneumoniae PPI network. Finally, 9 potential drug targets were identified from the hub proteins, with no homologs in swine. This study provides drug target candidates, which are promising for further investigations to explore lead compounds against A. pleuropneumoniae.     

Network medicine

To more effectively target complex diseases like cancer, diabetes and schizophrenia, we may need to rethink our strategies for drug development and the selection of molecular targets for pharmacological treatments. Here, we discuss the potential use of protein signaling networks as the targets for new therapeutic intervention. We argue that by targeting the architecture of aberrant signaling networks associated with cancer and other diseases new therapeutic strategies can be implemented. Transforming medicine into a network driven endeavour will require quantitative measurements of cell signaling processes; we will describe how this may be performed and combined with new algorithms to predict the trajectories taken by a cellular system either in time or through disease states. We term this approach, network medicine.     

基于网络药理学的杜仲-山茱萸配伍治疗糖尿病的作用机制

为探讨杜仲-山茱萸治疗糖尿病的作用机制。研究利用网络药理学的方法,首先通过中药系统药理学数据库筛选出杜仲和山茱萸的活性成分和相关靶点,再利用DisGeNET、DrugBank等数据库筛选出糖尿病的潜在靶点。以STRING数据库对活性靶点构建蛋白互作网络(PPI)分析,采用Cytoscape3.7.0软件绘制其“成分-靶点-通路”的相互作用网络,通过CludterProfiler对靶蛋白进行生物过程、细胞组分及分子功能分析;京都基因与基因组(KEGG)的代谢通路分析。实验结果筛选得到杜仲-山茱萸有效成分30个,其中槲皮素、山奈酚、β-谷甾醇等成分对PTGS2、DPP4、ADRB2、PPARG等相关靶点通过IL-17信号通路、钙信号通路、脂肪细胞脂解的调控等参与氮化合物代谢过程、血液循环、脂肪细胞分化和血压调节等过程。综上,杜仲-山茱萸配伍治疗糖尿病存在多成分和多重药理作用机制,为进一步研究其治疗糖尿病药理实验提供了参考,也为其他中药的相关研究提供借鉴和参考。     

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.     

Structural insights into pharmacophore-assisted in silico identification of protein–protein interaction inhibitors for inhibition of human toll-like receptor 4 – myeloid differentiation factor-2 (hTLR4−MD-2) complex

Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS?TLR4?MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein–protein interaction (PPI) in TLR4?MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4?MD-2) and dimerization (MD-2?TLR4*) protein–protein interaction interfaces in TLR4?MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4?MD-2 protein–protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4?MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.     

Strategies towards high-quality binary protein interactome maps

Many processes in a cell depend on protein–protein interactions (PPIs) and perturbations of these interactions can lead to diseases. Comprehensive knowledge of PPI networks will not only give us information on how the cell is organized, but will also provide new drug targets. Current binary PPI networks are mainly generated by high-throughput yeast two-hybrid. Due to the small overlap of these maps, it has long been assumed that these maps are of low quality containing many false positives. However, by using an orthogonal two-hybrid method, MAPPIT (mammalian protein–protein interaction trap), these maps were shown to be of high quality suggesting that the limited overlap is likely due to low sensitivity and not to low specificity.     

Effect of dapagliflozin on diabetic patients with cardiovascular disease via MAPK signalling pathway

Clinical studies have shown that dapagliflozin can reduce cardiovascular outcome in patients with type 2 diabetes mellitus (T2DM), but the exact mechanism is unclear. In this study, we used the molecular docking and network pharmacology methods to explore the potential mechanism of dapagliflozin on T2DM complicated with cardiovascular diseases (CVD). Dapagliflozin's potential targets were predicted via the Swiss Target Prediction platform. The pathogenic targets of T2DM and CVD were screened by the Online Mendelian Inheritance in Man (OMIM) and Gene Cards databases. The common targets of dapagliflozin, T2DM and CVD were used to establish a protein-protein interaction (PPI) network; the potential protein functional modules in the PPI network were found out by MCODE. Metascape tool was used for Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis. A potential protein functional module with the best score was obtained from the PPI network and 9 targets in the protein functional module all showed good binding properties when docking with dapagliflozin. The results of KEGG pathway enrichment analysis showed that the underlying mechanism mainly involved AGE-RAGE signalling pathway in diabetic complications, TNF signalling pathway and MAPK signalling pathway. Significantly, the MAPK signalling pathway was considered as the key pathway. In conclusion, we speculated that dapagliflozin played a therapeutic role in T2DM complicated with CVD mainly through MAPK signalling pathway. This study preliminarily reveals the possible mechanism of dapagliflozin in the treatment of T2DM complicated with CVD and provides a theoretical basis for future clinical research.     

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。     

MicroRNAs: Novel Regulators of Oligodendrocyte Differentiation and Potential Therapeutic Targets in Demyelination-Related Diseases

MicroRNAs (miRNAs or miRs) are a class of endogenous small non-coding RNAs that consist of about 22 nucleotides and play critical roles in various biological processes, including cell proliferation, differentiation, apoptosis, and tumorigenesis. In recent years, some specific miRNA, such as miR-219, miR-138, miR-9, miR-23, and miR-19b were found to participate in the regulation of oligodendrocyte (OL) differentiation and myelin maintenance, as well as in the pathogenesis of demyelination-related diseases (e.g., multiple sclerosis, ischemic stroke, and leukodystrophy). These miRNAs control their target mRNA or regulate the protein levels of some signaling pathways, and participate in OL differentiation and the pathogenesis of demyelination-related diseases. During pathologic processes, the expression levels of specific miRNAs are dynamically altered. Therefore, miRNAs act as diagnostic and prognostic indicators of defects in OL differentiation and demyelination-related diseases, and they can provide potential targets for therapeutic drug development.     

Comparative genomics and interactomics of polyadenylation factors for the prediction of new parasite targets: Entamoeba histolytica as a working model

Protein–protein interactions (PPI) play a key role in predicting the function of a target protein and drug ability to affect an entire biological system. Prediction of PPI networks greatly contributes to determine a target protein and signal pathways related to its function. Polyadenylation of mRNA 3′-end is essential for gene expression regulation and several polyadenylation factors have been shown as valuable targets for controlling protozoan parasites that affect human health. Here, by using a computational strategy based on sequence-based prediction approaches, phylogenetic analyses, and computational prediction of PPI networks, we compared interactomes of polyadenylation factors in relevant protozoan parasites and the human host, to identify key proteins and define potential targets for pathogen control. Then, we used Entamoeba histolytica as a working model to validate our computational results. RT-qPCR assays confirmed the coordinated modulation of connected proteins in the PPI network and evidenced that silencing of the bottleneck protein EhCFIm25 affects the expression of interacting proteins. In addition, molecular dynamics simulations and docking approaches allowed to characterize the relationships between EhCFIm25 and Ehnopp34, two connected bottleneck proteins. Interestingly, the experimental identification of EhCFIm25 interactome confirmed the close relationships among proteins involved in gene expression regulation and evidenced new links with moonlight proteins in E. histolytica, suggesting a connection between RNA biology and metabolism as described in other organisms. Altogether, our results strengthened the relevance of comparative genomics and interactomics of polyadenylation factors for the prediction of new targets for the control of these human pathogens.     

基于网络药理学分析芪贞元丹治疗动脉粥样硬化的作用机制*

目的: 基于网络药理学方法,探究中药复方芪贞元丹治疗动脉粥样硬化(AS)潜在的作用靶点和分子机制。方法: 查找TCMSP数据库,获得中药复方芪贞元丹中黄芪、女贞子、延胡索、丹参的活性成分和靶点,在OMIM等数据库中检索AS的靶点,使用Cytoscape绘图工具构建分子网络;检索STRING数据库并绘制PPI网络图,获取芪贞元丹治疗AS的关键靶点;并上传至Metascape数据平台对其进行GO和KEGG分析。结果: 芪贞元丹与AS有交集靶点118个,作为干预AS的作用靶点。芪贞元丹对抗AS可能与细胞因子介导、细胞因子受体结合等GO过程相关。KEGG富集结果显示155条通路与AS相关,主要涉及PI3K-Akt、HIF-1、NF-κB通路和炎症性肠病相关通路。结论: 通过网络药理学实验初步揭示芪贞元丹复方治疗AS的作用机制,复方中的槲皮素、山奈酚等活性成分作用于IL-6、PI3K-Akt等靶点,通过抗细胞凋亡、抑制氧化应激、抑制炎症反应等发挥抗AS作用,证明芪贞元丹复方治疗AS是多成分、多靶点、多途径协同作用的过程。     

Role of mycobacteria effectors in phagosome maturation blockage and new drug targets discovery

Tuberculosis remains a serious global health threat with nearly 10 million new cases and 1.7 million deaths every year. The emergence of multi-drug resistant (MDR) and extensively drug resistant (XDR) strains of Mycobacterium tuberculosis (Mtb) further complicates this problem. It is pressing to find new ways to combat Mtb. The success of Mtb is largely attributed to its ability to persist within macrophages by arresting phagosomal maturation. The bacterial proteins and lipids play important roles in this inhibition which involves several aspects of phagosomal maturation, including both fusion and fission events and recruitment of V-ATPases allowing acidification. Understanding the interaction between the pathogen and host macrophage is essential to eradicate or control tuberculosis. This review focuses on the mechanism of phagolysosome formation, the pivotal event for the fates of infection participants and abundance of novel drug targets.     

G protein-coupled receptors in energy homeostasis

G-protein coupled receptors (GPCRs) compromise the largest membrane protein superfamily which play vital roles in physiological and pathophysiological processes including energy homeostasis. Moreover, they also represent the up-to-date most successful drug target. The gut hormone GPCRs, such as glucagon receptor and GLP-1 receptor, have been intensively studied for their roles in metabolism and respective drugs have developed for the treatment of metabolic diseases such as type 2 diabetes (T2D). Along with the advances of biomedical research, more GPCRs have been found to play important roles in the regulation of energy homeostasis from nutrient sensing, appetite control to glucose and fatty acid metabolism with various mechanisms. The investigation of their biological functions will not only improve our understanding of how our body keeps the balance of energy intake and expenditure, but also highlight the possible drug targets for the treatment of metabolic diseases. The present review summarizes GPCRs involved in the energy control with special emphasis on their pathophysiological roles in metabolic diseases and hopefully triggers more intensive and systematic investigations in the field so that a comprehensive network control of energy homeostasis will be revealed, and better drugs will be developed in the foreseeable future.     

Evaluating the Pharmacological Mechanism of Chinese Medicine Si-Wu-Tang through Multi-Level Data Integration

Si-Wu-Tang (SWT) is a Traditional Chinese Medicine (TCM) formula widely used for the treatments of gynecological diseases. To explore the pharmacological mechanism of SWT, we incorporated microarray data of SWT with our herbal target database TCMID to analyze the potential activity mechanism of SWT''s herbal ingredients and targets. We detected 2,405 differentially expressed genes in the microarray data, 20 of 102 proteins targeted by SWT were encoded by these DEGs and can be targeted by 2 FDA-approved drugs and 39 experimental drugs. The results of pathway enrichment analysis of the 20 predicted targets were consistent with that of 2,405 differentially expressed genes, elaborating the potential pharmacological mechanisms of SWT. Further study from a perspective of protein-protein interaction (PPI) network showed that the predicted targets of SWT function cooperatively to perform their multi-target effects. We also constructed a network to combine herbs, ingredients, targets and drugs together which bridges the gap between SWT and conventional medicine, and used it to infer the potential mechanisms of herbal ingredients. Moreover, based on the hypothesis that the same or similar effects between different TCM formulae may result from targeting the same proteins, we analyzed 27 other TCM formulae which can also treat the gynecological diseases, the subsequent result provides additional insight to understand the potential mechanisms of SWT in treating amenorrhea. Our bioinformatics approach to detect the pharmacology of SWT may shed light on drug discovery for gynecological diseases and could be utilized to investigate other TCM formulae as well.