Revealing synergistic mechanism of multiple components in Stauntonia brachyanthera Hand.-Mazz. for gout by virtual screening and system pharmacological approach

Stauntonia brachyanthera Hand.-Mazz. (SB), reported as a traditional Chinese medicine, displays a wide spectrum of interesting bioactivities, such as anti-inflammatory and analgesia. It is noteworthy that anti-gout effects of the components in SB have been reported. Hence, this study contributes to the prediction of promising active compounds and mechanisms for the treatment of gout. The active compounds with better oral bioavailability, and drug-likeness of SB were selected for further investigation by the approach of network pharmacology, molecular docking, gene ontology (GO) analysis, and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis, respectively. A total of 34 predicted targets and 98 compounds in SB were obtained. Sorted by structure types of compounds, phenylethanoid glycosides exhibited the best anti-gout activity, followed by phenolics and flavonoids. What’s more, it was shown in the network analysis that Serine/threonine-protein kinase mTOR (mTOR), Mitogen-activated protein kinase 12 (MAPK12), tumor necrosis factor (TNF-α), Integrin alpha-4 (ITGA4) and Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit gamma (PIK3CG) were the key targets with intensely interaction, which should be attached more attention for further study. The functional enrichment analysis indicated that SB probably produced the anti-gout effects by synergistically regulating many biological pathways, such as MAPK signaling pathway, PI3K-Akt signaling pathway, Toll-like receptor signaling pathway and NOD-like receptor signaling pathway, etc. In addition, C61, C67, C68 and C81 might be promising leading compounds with good molecular docking score. As a consequence, the active constituents and mechanisms based on data analysis were holistically illuminated, which was of vital importance to the development of new drugs for gout.     

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.     

Elucidating Drug-Like Compounds and Potential Mechanisms of Corn Silk (Stigma Maydis) against Obesity: A Network Pharmacology Study

Corn silk (Stigma Maydis) has been utilized as an important herb against obesity by Chinese, Korean, and Native Americans, but its phytochemicals and mechanisms(s) against obesity have not been deciphered completely. This study aimed to identify promising bioactive constituents and mechanism of action(s) of corn silk (CS) against obesity via network pharmacology. The compounds from CS were identified using Gas Chromatography Mass Spectrometry (GC-MS) and were confirmed ultimately by Lipinski’s rule via SwissADME. The relationships of the compound-targets or obesity-related targets were confirmed by public bioinformatics. The signaling pathways related to obesity, protein-protein interaction (PPI), and signaling pathways-targets-bioactives (STB) were constructed, visualized, and analyzed by RPackage. Lastly, Molecular Docking Test (MDT) was performed to validate affinity between ligand(s) and protein(s) on key signaling pathway(s). We identified a total of 36 compounds from CS via GC-MS, all accepted by Lipinski’s rule. The number of 36 compounds linked to 154 targets, 85 among 154 targets related directly to obesity-targets (3028 targets). Of the final 85 targets, we showed that the PPI network (79 edges, 357 edges), 12 signaling pathways on a bubble chart, and STB network (67 edges, 239 edges) are considered as therapeutic components. The MDT confirmed that two key activators (β-Amyrone, β-Stigmasterol) bound most stably to PPARA, PPARD, PPARG, FABP3, FABP4, and NR1H3 on the PPAR signaling pathway, also, three key inhibitors (Neotocopherol, Xanthosine, and β-Amyrone) bound most tightly to AKT1, IL6, FGF2, and PHLPP1 on the PI3K-Akt signaling pathway. Overall, we provided promising key signaling pathways, targets, and bioactives of CS against obesity, suggesting crucial pharmacological evidence for further clinical testing.     

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.     

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...     

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.     

Insights into Pancreatic Cancer Etiology from Pathway Analysis of Genome-Wide Association Study Data

Background

Pancreatic cancer is the fourth leading cause of cancer death in the U.S. and the etiology of this highly lethal disease has not been well defined. To identify genetic susceptibility factors for pancreatic cancer, we conducted pathway analysis of genome-wide association study (GWAS) data in 3,141 pancreatic cancer patients and 3,367 controls with European ancestry.

Methods

Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways identified from the Kyoto Encyclopedia of Genes and Genomes database. We used the logistic kernel machine (LKM) test to identify major contributing genes to each pathway. We conducted functional enrichment analysis of the most significant genes (P<0.01) using the Database for Annotation, Visualization, and Integrated Discovery (DAVID).

Results

Two pathways were significantly associated with risk of pancreatic cancer after adjusting for multiple comparisons (P<0.00025) and in replication testing: neuroactive ligand-receptor interaction, (Ps<0.00002), and the olfactory transduction pathway (P = 0.0001). LKM test identified four genes that were significantly associated with risk of pancreatic cancer after Bonferroni correction (P<1×10⁻⁵): ABO, HNF1A, OR13C4, and SHH. Functional enrichment analysis using DAVID consistently found the G protein-coupled receptor signaling pathway (including both neuroactive ligand-receptor interaction and olfactory transduction pathways) to be the most significant pathway for pancreatic cancer risk in this study population.

Conclusion

These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer.     

Identification of key candidate genes and pathways in multiple myeloma by integrated bioinformatics analysis

Multiple myeloma (MM) is a common hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. This study aimed to elucidate key candidate genes and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE6477 and GSE47552 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) with p < .05 and [logFC] > 1 were identified. Functional enrichment, protein–protein interaction network construction and survival analyses were then performed. First, 51 upregulated and 78 downregulated DEGs shared between the two GSE datasets were identified. Second, functional enrichment analysis showed that these DEGs are mainly involved in the B cell receptor signaling pathway, hematopoietic cell lineage, and NF-kappa B pathway. Moreover, interrelation analysis of immune system processes showed enrichment of the downregulated DEGs mainly in B cell differentiation, positive regulation of monocyte chemotaxis and positive regulation of T cell proliferation. Finally, the correlation between DEG expression and survival in MM was evaluated using the PrognoScan database. In conclusion, we identified key candidate genes that affect the outcomes of patients with MM, and these genes might serve as potential therapeutic targets.     

High-dose dexamethasone injection disordered metabolism and multiple protein kinases expression in the mouse kidney

Glucocorticoids (GCs) have been widely used in clinical treatment as anti-inflammatory, anti-shock and immunosuppressive medicines. However, the effect of excessive GCs on immune response and metabolism of kidney remains unclear. Here, we profiled the gene expression of kidney from mice with high-dose dexamethasone (DEX) treatment. A total of 1193 differentially expressed genes (DEGs) were screened in DEX treatment group compared with the saline group, including 715 down- regulated and 478 up-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of these DEGs showed extracellular matrix (ECM)–receptor interaction, cell adhesion molecules signaling pathway were significantly enriched, and that the vast majority of DEGs were involved in monocarboxylic acid metabolism, leukocyte cell–cell adhesion and fatty acid metabolism. Gene set enrichment analysis (GSEA) revealed that DEGs were strongly associated with immune-response and cell adhesion gene sets, such as Fc γ R-mediated phagocytosis, leukocyte transendothelial migration, T-cell receptor signaling pathway, cell adhesion, ECM–receptor interaction and focal adhesion-associated pathways. KEGG pathway analysis of differentially expressed kinases (DEKs) showed T-cell receptor and forkhead box class O signaling pathway were enriched. Furthermore, we found multiple protein kinases expression were dysregulated greatly after dexamethasone treatment, including classical effector of GCs stimulation-serum and GC-regulated kinase. These protein kinases are involved in multiple signaling pathways in mice kidney, such as mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/Akt signaling pathway. We profiled the gene expression of the kidney from high-dose dexamethasone-treated mice and provided important information for further study the mechanism of side effects of GCs in clinical therapy.     

Andrographolide in atherosclerosis: integrating network pharmacology and in vitro pharmacological evaluation

Objective: Andrographis paniculata (Burm.f.) Nees is a medicinal plant that has been traditionally used as an anti-inflammatory and antibacterial remedy for several conditions. Andrographolide (AG), the active constituent of A. paniculata (Burm.f.) Nees, has anti-lipidic and anti-inflammatory properties as well as cardiovascular protective effects. The present study aimed to explore the effects of AG on the progression of atherosclerosis and to investigate related mechanisms via network pharmacology.Materials and methods: Compound-related information was obtained from the PubChem database. Potential target genes were identified using STITCH, SwissTargetPrediction, Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine, and Comparative Toxicogenomics Database. Genes involved in atherosclerosis were obtained from DisGeNet and compared with AG target genes to obtain an overlapping set. Protein–protein interactions were determined by STRING. Gene ontology (GO) analysis was performed at WebGestalt, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment was analyzed using Metascape. The final network showing the relationship between compounds, targets, and pathways was constructed using Cytoscape. After that, oxLDL-induced RAW264.7 cells were used to further validate a part of the network pharmacology results.Result: Eighty-one potential AG target genes were identified. PPI, GO, and KEGG enrichment revealed genes closely related to tumor progression, lipid transport, inflammation, and related pathways. AG improves the reverse cholesterol transport (RCT) through NF-κB/CEBPB/PPARG signaling in oxLDL-induced RAW264.7 cells.Conclusion: We successfully predict AG’s potential targets and pathways in atherosclerosis and illustrate the mechanism of action. AG may regulate NF-κB/CEBPB/PPARG signaling to alleviate atherosclerosis.     

A RAC/CDC-42–Independent GIT/PIX/PAK Signaling Pathway Mediates Cell Migration in C. elegans

P21 activated kinase (PAK), PAK interacting exchange factor (PIX), and G protein coupled receptor kinase interactor (GIT) compose a highly conserved signaling module controlling cell migrations, immune system signaling, and the formation of the mammalian nervous system. Traditionally, this signaling module is thought to facilitate the function of RAC and CDC-42 GTPases by allowing for the recruitment of a GTPase effector (PAK), a GTPase activator (PIX), and a scaffolding protein (GIT) as a regulated signaling unit to specific subcellular locations. Instead, we report here that this signaling module functions independently of RAC/CDC-42 GTPases in vivo to control the cell shape and migration of the distal tip cells (DTCs) during morphogenesis of the Caenorhabditis elegans gonad. In addition, this RAC/CDC-42–independent PAK pathway functions in parallel to a classical GTPase/PAK pathway to control the guidance aspect of DTC migration. Among the C. elegans PAKs, only PAK-1 functions in the GIT/PIX/PAK pathway independently of RAC/CDC42 GTPases, while both PAK-1 and MAX-2 are redundantly utilized in the GTPase/PAK pathway. Both RAC/CDC42–dependent and –independent PAK pathways function with the integrin receptors, suggesting that signaling through integrins can control the morphology, movement, and guidance of DTC through discrete pathways. Collectively, our results define a new signaling capacity for the GIT/PIX/PAK module that is likely to be conserved in vertebrates and demonstrate that PAK family members, which are redundantly utilized as GTPase effectors, can act non-redundantly in pathways independent of these GTPases.     

基于网络药理学探讨皂角刺治疗乳痈的作用机制

摘要 目的：基于网络药理学探讨皂角刺治疗乳痈的作用机制。方法：通过建立皂角刺药物靶点数据集、乳痈相关疾病靶点数据集，构建皂角刺治疗急性乳腺炎的蛋白互作（PPI）网络，构建并分析"皂角刺活性成分-潜在靶点-急性乳腺炎"网络。开展基因本体（GO）功能富集分析和京都基因与基因组百科全书（KEGG）通路富集分析，探讨皂角刺治疗乳痈的可能机制。结果：共得到皂角刺活性成分11个，筛选出活性成分所对应的不重复靶点共97个，其中1个活性成分无对应靶点。通过搜集GeneCards 和OMIM数据库，共得到292个急性乳腺炎的相关靶点基因。将疾病靶点基因与药物活性成分所对应的靶点进行比对后，得到10个交集靶点，即皂角刺治疗急性乳腺炎的潜在靶点。皂角刺活性成分按degree值排前3名的依次为槲皮素（quercetin）、漆黄素（fisetin）、山奈酚（kaempferol），其中皂角刺治疗乳痈的靶点包括白细胞介素-6（IL-6）、表皮生长因子受体（EGFR）、酪氨酸激酶受体2（ERBB2）、细胞间黏附分子-1（ICAM1）、雌激素受体1（ESR1）等5个关键靶点，主要涉及乳腺癌疾病通路、TNF信号通路和雌激素信号通路等3条信号通路。结论：皂角刺治疗乳痈的作用机制可能与机体的炎症反应以及雌激素水平变化等密切相关。     

Integrated Enrichment Analysis of Variants and Pathways in Genome-Wide Association Studies Indicates Central Role for IL-2 Signaling Genes in Type 1 Diabetes,and Cytokine Signaling Genes in Crohn's Disease

Pathway analyses of genome-wide association studies aggregate information over sets of related genes, such as genes in common pathways, to identify gene sets that are enriched for variants associated with disease. We develop a model-based approach to pathway analysis, and apply this approach to data from the Wellcome Trust Case Control Consortium (WTCCC) studies. Our method offers several benefits over existing approaches. First, our method not only interrogates pathways for enrichment of disease associations, but also estimates the level of enrichment, which yields a coherent way to promote variants in enriched pathways, enhancing discovery of genes underlying disease. Second, our approach allows for multiple enriched pathways, a feature that leads to novel findings in two diseases where the major histocompatibility complex (MHC) is a major determinant of disease susceptibility. Third, by modeling disease as the combined effect of multiple markers, our method automatically accounts for linkage disequilibrium among variants. Interrogation of pathways from eight pathway databases yields strong support for enriched pathways, indicating links between Crohn''s disease (CD) and cytokine-driven networks that modulate immune responses; between rheumatoid arthritis (RA) and “Measles” pathway genes involved in immune responses triggered by measles infection; and between type 1 diabetes (T1D) and IL2-mediated signaling genes. Prioritizing variants in these enriched pathways yields many additional putative disease associations compared to analyses without enrichment. For CD and RA, 7 of 8 additional non-MHC associations are corroborated by other studies, providing validation for our approach. For T1D, prioritization of IL-2 signaling genes yields strong evidence for 7 additional non-MHC candidate disease loci, as well as suggestive evidence for several more. Of the 7 strongest associations, 4 are validated by other studies, and 3 (near IL-2 signaling genes RAF1, MAPK14, and FYN) constitute novel putative T1D loci for further study.     

Bioinformatic prediction and analysis of glucolipid metabolic regulation by miR-34a in <Emphasis Type="Italic">Megalobrama amblycephala</Emphasis>

The objective of this study was to analyze the target genes and regulatory function of miR-34a in Megalobrama amblycephala using second-generation high-throughput sequencing and bioinformatic tools. Functional enrichment analysis was performed by gene ontology. MiR-34a and target gene expression levels were measured in M. amblycephala fed normal and high-carbohydrate diets. The results revealed that miR-34a was highly conserved in several species, and miR-34a of M. amblycephala has a close evolutionary relationship to that of zebrafish and common carp. miRanda, TargetScan, RNAhybrid predicted 5,185, 6,282 and 2,168 target genes, respectively, and 645 target genes were in common. According to annotation information, the target genes were enriched in phosphate metabolism, glycerophospholipid metabolism, Golgi vesicle transport, cell division, and other biological processes (P?<?0.05). Pathway enrichment analysis revealed that these target genes were mainly enriched in alpha-linolenic acid and linoleic acid metabolism, ether lipid metabolism, VEGF signaling pathway, Fc epsilon RI signaling pathway, GnRH signaling pathway, and MAPK signaling pathway (P?<?0.05). The regulatory role of miR-34a was more significant in the liver than in the brain of M. amblycephala. MiR-34a regulates glucose lipid homeostasis induced by high glucose diets by upregulating hepatic PI3K/Akt, FOXO, and TOR signaling pathways.     

基于疾病与活性化合物靶点网络构建的异鼠李素抗缺血性神经损伤作用评价与验证研究

基于网络药理学与分子对接探讨异鼠李素对缺血性神经损伤的治疗作用。采用ChEMBL、SwissTargetPrediction、DrugBank、STITCH及BindingDB数据库检索异鼠李素药理学靶点,应用DisGeNET、GenCLiP及CTD数据库检索缺血性神经损伤的疾病靶点,取交集作为异鼠李素对缺血性神经损伤的治疗靶点,并进行表型分析。将交集靶点导入STRING构建蛋白互作网络,使用Network analyser进行拓扑分析,同时应用MODE构建功能模块,并基于ClueGo对功能模块进行分析。之后应用DAVID数据库对治疗靶点进行GO及KEGG富集分析。利用Discovery Studio评价异鼠李素与核心靶点的结合活性,最后建立OGD/R损伤PC12细胞模型,采用MTT和LDH法检测细胞活力,Western blot法对AKT1、IL6和MMP2的表达进行检测。异鼠李素通过50个缺血性神经损伤相关靶点,调控细胞凋亡、转录、蛋白质磷酸化、炎症反应等生物学过程,干预PI3K-AKT信号通路、HIF-1信号通路、雌激素信号通路、肿瘤坏死因子信号通路、FoxO信号通路等多条途径发挥抗缺血性神经损伤的作用。初步阐释异鼠李素治疗缺血性神经损伤的作用,涉及多靶点、多通路,为进一步探究其药理学活性奠定理论基础。     

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...