目的 采用超高效液相色谱-飞行时间质谱联用（UPLC/Q-TOF-MS）技术、网络药理学及蛋白质组学方法，对坤心宁颗粒中的潜在质量标志物（quality markers，Q-Marker）进行预测分析，并建立坤心宁颗粒的质量评价方法。方法 采用UPLC/Q-TOF-MS技术对坤心宁颗粒及给药后大鼠血浆中的化学成分（入血成分）进行解析；应用蛋白质组学技术挖掘坤心宁颗粒改善肾阴阳两虚型围绝经期综合征（perimenopausal syndrome，PMS）的关键信号通路；通过网络药理学对入血成分进行靶点预测，联合蛋白质组学差异通路分析，确定坤心宁颗粒的潜在Q-Marker；基于HPLC技术建立坤心宁颗粒中8种Q-Marker的定量方法，实现对坤心宁颗粒的质量评价。结果 UPLC/Q-TOF-MS检测结合质谱数据及文献数据分析，鉴定出坤心宁颗粒中20种入血成分，结合网络药理学和蛋白质组学技术最终确定梓醇、地黄苷D、芍药苷、毛蕊异黄酮葡萄糖苷、(−)-丁香树脂酚-4-O-β-D-呋喃芹糖基-(1→2)-β-D-吡喃葡萄糖苷、仙茅苷、淫羊藿苷和宝藿苷I共8种成分为坤心宁颗粒的Q-Marker；建立HPLC分析方法对15批坤心宁颗粒样品进行定量测定，结果显示各批样品中8种Q-Marker含量均保持稳定。结论 借助多维分析技术确定了坤心宁颗粒中的8种潜在Q-Marker，为其全面质量控制提供有效手段。

Objective The potential quality markers (Q-Marker) of Kunxinning Granules (KG, 坤心宁颗粒) were studied by UPLC/Q-TOF-MS technology, network pharmacology and proteomics, and the quality evaluation method of KG was established. Methods UPLC/Q-TOF-MS technology was used to analyze the chemical components of KG and drug-containing plasma. The key signal pathway of KG in improving renal and yin-yang deficiency perimenopausal syndrome (PMS) was explored by proteomics. The potential Q-Marker of KG were determined by network pharmacology and proteomic differential pathway analysis. The quantitative method of eight Q-Marker in KG was established based on HPLC technology to realize the quality evaluation of KG. Results UPLC/Q-TOF-MS detection combined with mass spectrometry data and literature data analysis, identified 20 components in plasma from KG. Combined with network pharmacology and proteomics techniques, a total of eight components, including catalpol, rehmannioside D, paeoniflorin, calycosin-7-O-b-D-glucoside, (−)-syringaresinol-4-O-b-D-apiofuranosyl-(1→2)-b-D-glucopyranoside, curculigoside, icariin and baohuoside I, were identified as the Q-Marker of KG. An HPLC analytical method was established to determine the contents of the eight Q-Marker in 15 batches of KG samples. The results indicated that the contents of the eight Q-Marker in each batch of samples remained stable. Conclusion With the aid of multi-dimensional analysis techniques, eight Q-Marker of KG were determined, providing an effective tool for its comprehensive quality control.

R283.6

中央高校基本科研业务费专项资金资助（63241465）