目的 通过超高效液相色谱-静电场轨道阱高分辨质谱（UPLC-Q-Exactive-Focus-MS/MS）分析酸枣仁中的化学成分，依据解析的化学成分及中药系统药理学数据库与分析平台（TCMSP）、本草组鉴数据库（HERB）获取的酸枣仁主要成分结合网络药理学和分子对接技术初步预测其抗阿尔茨海默病（AD）的药效物质基础，筛选出潜在功效成分，预测作用机制。方法 采用UPLC-Q-Exactive Focus-MS/MS对酸枣仁进行化学成分分析，分别在正、负离子模式下扫描，结合对照品、文献中的碎片离子信息、保留时间进行匹配，确认化学成分。利用TCMSP、HERB数据库获取酸枣仁的主要成分及其对应作用靶点信息；通过GeneCards、OMIM数据库获得AD相关疾病靶点；将酸枣仁主要成分对应靶点与AD靶点取交集，借助String 11.5平台和Cytoscape 3.7.2软件绘制交集基因蛋白质相互作用（PPI）网络；利用DAVID 6.8对核心靶点进行基因本体（GO）功能与京都基因与基因组百科全书（KEGG）通路富集分析，通过微生信云平台对富集结果可视化；借助AutoDock Tools软件对核心成分及关键靶点基因进行分子对接。结果 酸枣仁定性分析中共鉴定出40个化合物，主要包括3个有机酸类、28个黄酮类、8个生物碱类、1个皂苷类；筛选出发挥改善AD作用的核心成分5个，包括拟雌内酯、油酸、山柰酚、乌药碱、酸李碱；酸枣仁改善AD的核心靶点有JUN、AKT1、STAT3、MAPK14、ESR1、IL16等；KEGG通路分析共得到157条通路，其中PI3K-Akt信号通路、MAPK信号通路、HIF-1信号通路排名靠前；GO富集分析得到生物过程（BP）条目336个、细胞组分（CC）条目45个、分子功能（MF）42个。分子对接结果显示，酸枣仁的4个核心成分与关键靶点间存在分子结合位点且结合能较强，均小于-20.93 kJ·mol^-1。结论 通过UPLC-Q-Exactive-Focus-MS/MS解析的化学成分结合网络药理学、分子对接预测了酸枣仁是通过多成分、多靶点、多途径来发挥抗AD作用的。

Objective To analyze the chemical components of Ziziphi Spinosae Semen (ZSS) by UPLC-Q-Exactive-Focus-MS/MS, then predict the pharmacodynamic substance basis of treating Alzheimer's disease (AD) based on its chemical components, its main active components obtained from TCMSP and HERB database, network pharmacology and molecular docking technology, checking out the potential efficacy ingredients and mechanism of action. Methods UPLC-Q-Exactive-Focus-MS/MS was used to analyze the chemical components of ZSS, which were scanned in positive and negative modes respectively. The chemical components was confirmed by matching the reference substance with the fragment ion information and retention time. The active ingredients and action targets of ZSS were obtained through TCMSP databases and HERB databases, AD targets were obtained from GeneCards and OMIM databases. The corresponding targets of the main ingredients of ZSS were intersected with the AD targets, and the protein-protein interaction (PPI) network of the intersected genes was mapped with the help of STRING 11.5 platform and Cytoscape 3.7.2 software. The analysis of gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were performed by the DVIAD 6.8 online database and visually presented through the platform of bioinformatics. Furthermore, molecular docking technology was performed to validate the binding pattern and affinity between the key ingredients and the crucial targets by using AutoDock Tools software. Results There were 40 chemical components analyzed by qualitative analysis of ZSS, including three organic acids, 28 flavonoids, eight alkaloids, one saponin. Screening out five core components that play a therapeutic role in AD, including coumestrol, oleic acid, kaempferol, coclaurine and zizyphusine, etc. The core targets of ZSS for treating AD include JUN, AKT1, STAT3, MAPK14, ESR1, IL16, etc. A total of 157 pathways were identified through KEGG pathway analysis, with PISKAkt, MAPK and HIF-1 response related signaling pathways ranking high. GO enrichment analysis yielded 336 entries for biological processes (BP), 45 entries for cellular components (CC), and 42 entries for molecular functions (MF). The molecular docking results showed that the binding energy between the key biotargets and the four potential active components were much less than -20.93 kJ·mol-1. Conclusion Based on the chemical components analyzed by UPLC-Q-Exactive-Focus-MS/MS combined with network pharmacology, molecular dock, ZSS plays a role in anti-Alzheimer's disease through multi-components, multi-targets, and multi-pathways.

R284.1；R285.5

陕西省中医药管理局中医药全省性专款专项项目（2021-QYZL-01）；陕西省重点研发计划一般项目（2022-SF-315）；“陕西省中医药管理局双链融合”中青年科研创新团队（2022-SLRH-YQ-003）；陕西省中医药管理局“医研校企”中医药传承创新平台（中医药创新药物/器械“研发-转化-推广”平台）；陕西省中医药研究院“苗圃计划”一般项目（2021-26）