基于体内暴露及网络药理学探讨鞣花酸干预胃肠道出血的作用机制

Investigation on Intervention Mechanism of Ellagic Acid on Gastrointestinal Bleeding Based on in Vivo Exposure and Network Pharmacology

关键词:  鞣花酸  尿石素  胃肠道出血  液质联用  网络药理学  分子对接

Key words:  ellagic acid  urolithin  gastrointestinal bleeding  LC-MS  network pharmacology  molecular docking

摘要:

目的 基于超高效液相色谱-四极杆-飞行时间质谱(UPLC-Q-TOF-MS)技术对口服给药鞣花酸后大鼠体内暴露成分进行分析鉴定,结合网络药理学探讨鞣花酸及其体内暴露成分治疗胃肠道出血(gastrointestinal bleeding,GIB)的作用机制。方法 采用UPLC-Q-TOF-MS鉴定大鼠口服鞣花酸后的外源性代谢产物,利用PharmMapper、SwissTargetPrediction数据库预测鞣花酸体内暴露成分的潜在作用靶点,通过GeneCards、OMIM、DRUGBANK数据库收集GIB相关疾病靶点,进一步筛选出成分与疾病的交集靶点;通过STRING 11.0数据库构建蛋白-蛋白相互作用(protein-protein interaction,PPI)网络,借助CytoScape 3.8.2软件对PPI网络进行可视化分析,筛选核心作用靶点;采用Metascape分析平台对交集靶点进行GO分析和KEGG富集分析,并通过CytoScape 3.8.2软件构建成分-靶点-通路图。最后,基于AutoDockVina 1.1.2软件进行分子对接计算,验证化学成分与核心靶点的靶向关系。结果 基于UPLC-Q-TOF-MS分析,鉴定了鞣花酸体内暴露成分,包括鞣花酸原型成分及10个尿石素类代谢物,通过网络药理学预测,发现其潜在作用靶点500个,以及GIB相关靶点1 117个。SRC、PIK3R1、HRAS等为PPI网络的核心靶点。KEGG富集结果发现,该类成分主要涉及PI3K-Akt信号通路、抗EGFR酪氨酸激酶抑制剂通路、黏着斑信号通路等相关通路,GO富集分析主要涉及激酶活性调节、蛋白质丝氨酸/苏氨酸/酪氨酸激酶活性、蛋白质磷酸化等。分子对接结果显示,11个成分与6个核心靶点均有较好的结合活性。结论 鞣花酸体内暴露成分可能通过减少氧化应激,抑制炎症反应等发挥止血作用,为含有鞣花酸类相关中药治疗GIB的物质基础及作用机制研究提供科学依据。

Abstract:

OBJECTIVE To analyze and identify the exposed components in rats after oral administration of ellagic acid by ultra performance liquid chromatography-quadrupole-time of flight mass spectrometry(UPLC-Q-TOF-MS) technology, and to explore the mechanism of ellagic acid and its exposed components in the treatment of gastrointestinal bleeding(GIB) in combination with network pharmacology. METHODS The UPLC-Q-TOF-MS was applied to detect metabolites in rats after oral administration of ellagic acid. The PharmMapper and SwissTargetPrediction database were used to predict the potential targets of the ingredients. And GIB disease-related targets were obtained from GeneCards, OMIM, and DRUGBANK database. The drug-disease common target genes were uploaded to STRING 11.0 for the construction of the protein-protein interaction(PPI) network. To obtain the core targets, CytoScape 3.8.2 was used to visualize and analyze the PPI network. The gene ontology(GO) analysis and Kyoto encyclopedia of genes and genomes(KEGG) pathway enrichment analysis were performed on the common targets by Metascape. The component-target-pathway network was constructed by CytoScape 3.8.2. Finally, AutoDockVina 1.1.2 software was used for molecular docking to verify the affinity of key components and core targets. RESULTS Based on UPLC-Q-TOF-MS analysis, the in vivo exposure components of ellagic acid were identified, including the prototype components of ellagic acid and 10 urolithins metabolites. Through network pharmacological prediction, 500 potential action targets were found, as well as 1 117 GIB related targets. SRC, PIK3R1, HRAS and others were the core targets from the PPI network. It was found that these components were mainly involved in signaling pathways such as PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance pathway, focal adhesion signaling pathway and others. The GO analysis mainly involved in the regulation of kinase activity, protein serine/threonine/tyrosine kinase activity, protein phosphorylation and so on. Molecular docking results showed that 11 components could target to 6 core proteins. CONCLUSION This study suggests that ellagic acid and urolithins might exert hemostatic effects by reducing oxidative stress and inhibiting inflammatory responses, as well as provides a scientific basis for the material basis and mechanism of ellagic acid-related traditional Chinese medicine in the treatment of GIB.