基于UPLC-Q-Exactive-MS/MS结合网络药理学的藏药堆孜阿龙散抗RA的作用机制研究

Study on the mechanism of Tibetan medicine Duizialong Powder against RA based on UPLC-Q-Exactive-MS/MS combined with network pharmacology

关键词:  藏药堆孜阿龙散  抗RA  网络药理学  分子对接

Key words:  Tibetan medicine Duizialong Powder  anti-RA  network pharmacology  molecular docking

摘要:

目的 研究分析藏药堆孜阿龙散的主要成分，并利用网络药理学和分子对接技术寻找其治疗RA的作用机制。方法 通过UPLC-Q-Exactive-MS/MS技术分析并鉴定孜阿龙散的化学成分，上传至Swiss Target Prediction数据库获得靶点，然后利用GeneCard数据库筛选确定RA疾病的靶点；通过STRING数据库进行PPI分析，以及METASCAPE数据库进行GO功能和KEGG通路富集分析，构建“成分-靶点-通路”网络图，从而研究堆孜阿龙散治疗RA的作用机制，最后通过分子对接模拟其核心成分与蛋白的结合情况。结果 通过分子离子峰和二级特征碎片离子，结合文献和Compound Discover等数据库，共鉴定了堆孜阿龙散57个成分；上传至数据库获得成分靶点165个，RA疾病靶点5081个，导入韦恩图获得共同靶点101个；KEGG通路富集分析共获得140条通路（P<0.01），GO功能分析发现与生物过程（Biological Processes, BP）相关的有1341条，与细胞成分（Cellular Component, CC）相关的有79条，与分子功能（Molecular Function, MF）相关的有123条（P<0.01），构建了堆孜阿龙散“成分-靶点-通路”网路图。分子对接结果显示堆孜阿龙散核心成分（quercetin、quercetin-3-β-D-glucoside、isorhamnetin 3-glucoside、chrysoeriol、和rutin）与关键靶点（AKR1B1、PRKCA和VEGFA）具有较强的结合能力。结论 通过UPLC-Q-Exactive-MS/MS技术结合网络药理学的方法，初步揭示了藏药堆孜阿龙散的药效物质基础和预测了其抗RA的潜在作用机制。

Abstract:

OBJECTIVE The main chemical constituents of Tibetan medicine Duizialong Powder were analyzed, and the mechanism of its treatment for Rheumatoid Arthritis(RA) was investigated by network pharmacology and molecular docking techniques. METHODS UPLC-Q-Exactive-MS/MS technique was used to analyze and identify the chemical constituents of Duizialong Powder, and the targets were obtained by uploading to the Swiss Target Prediction database, and then the targets of RA disease were identified by GeneCard database. PPI analysis was conducted by STRING database, enrichment analysis of GO function and KEGG pathway was conducted by METASCAPE database, and constructed the network diagram of constituents-target-pathway. In the above study, the mechanism of action of Duizialong powder in the treatment of RA was studied, and the binding between its core components and proteins was verified by molecular docking, and finally, the binding between the core constituents and proteins was simulated by molecular docking. RESULTS A total of 57 chemical constituents of Duizialong powder were identified by molecular ion peaks and secondary characteristic fragment ions, combined with literature and Compound Discover database. After uploading to the database, 165 constituent targets, 5081 RA disease targets were obtained, and 101 common targets were obtained by importing Venn diagram. KEGG pathway enrichment analysis revealed a total of 140 pathways (P<0.01). GO function analysis revealed that there were 1341 related to Biological Process(BP), 79 related to Cellular Component(CC), and 123 related to Molecular Function(MF) (P<0.01). The constituents-target-pathway network diagram of Duizialong powder was constructed. Finally, molecular docking results showed that the core constituents (quercetin, quercetin-3-β-D-glucoside, isorhamnetin 3-glucoside, chrysoeriol, rutin) in Duizialong powder showed strong binding ability with key targets (AKR1B1, PRKCA, VEGFA). CONCLUSION Through UPLC-Q-Exactive-MS/MS technique combined with network pharmacology, the pharmacodynamic material basis of Duizialong powder was preliminarily revealed and the potential mechanism of anti-RA was predicted.