[关键词]
[摘要]
目的 建立UPLC-MS/MS法同时测定玉叶清火片中10种指标成分(京尼平苷酸、绿原酸、山栀苷甲酯、3,5-O-二咖啡酰基奎宁酸、栀子苷、玉叶金花苷酸甲酯、β-蜕皮甾酮、穿心莲内酯、蟛蜞菊内酯、脱水穿心莲内酯)的含量,结合化学模式识别方法对其进行系统、全面和科学的质量评价。方法 安捷伦Zorbax SB C18柱(50 mm×3.0 mm,1.8 μm);流动相为甲醇-0.1%乙酸(含0.02 mol/L乙酸铵)水溶液,梯度洗脱,体积流量0.3 mL/min;质谱采用ESI正、负离子同时采集,多反应监测(MRM)模式扫描,并对定量测定结果进行聚类分析(CA)、主成分分析(PCA)及正交偏最小二乘法-判别分析(OPLS-DA),综合评价其质量的差异性。结果 在优化的色谱质谱条件下,10种成分分别在0.352 5~14.100 0、5.402~270.100、0.205 8~8.232 0、1.050~42.020、4.020~160.800、4.328~173.100、2.044~204.400、2.251~225.000、0.232 8~9.312 0、4.708~188.300 μg/mL线性关系良好(r>0.999 1),平均加样回收率95.02%~99.66%(RSD<3.0%);定量分析结果表明大多数批次药物质量较为稳定;但通过CA和PCA均发现不同批次药品质量之间仍然存在微小差异,最后通过OPLS-DA筛出引起批次间质量差异的6个标志性成分,分别是穿心莲内酯、脱水穿心莲内酯、玉叶金花苷酸甲酯、山栀苷甲酯、3,5-O-二咖啡酰基奎宁酸、绿原酸。结论 实验建立的方法简便、灵敏、高效,可用于玉叶清火片中多种主要活性成分的快速测定;测定结果结合化学模式识别技术可从整体上综合评价药物质量,为玉叶清火片的质量控制研究提供新的科学依据和数据处理方法。
[Key word]
[Abstract]
Objective To establish the UPLC-MS/MS method for the simultaneous determination of 10 active components (geniposidic acid, chlorogenic acid, shanzhiside methyl ester, 3,5-O-dicaffeoylquinic acid, geniposide, mussaenoside, β-ecdysone, andrographolide, wedelolacton, and dehydroandrographolide) in Yuye Qinghuo Tablets (YQT), in order to make a systemic, comprehensive, and scientific quality evaluation of the drug combined with the chemical pattern recognition method. Methods The chromatographic separation was achieved on Agilent Zorbax SB C18 (50 mm×3.0 mm, 1.8 μm); The mobile phase was consisted of methanol-0.1% acetic acid (containing 20 mmol/L ammonium acetate) at a flow rate of 0.3 mL/min with gradient elution, the mass spectrum was scanned by ESI+ and ESI-multiple reaction monitoring (MRM) mode. And the content analysis was carried out by cluster analysis (CA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) to comprehensively evaluate the difference in quality of YQT. Results Under the optimized conditions, 10 components showed good linear relationships in the ranges of 0.352 5-14.100 0, 5.402-270.100, 0.205 8-8.232 0, 1.050-42.020, 4.020-160.800, 4.328-173.100, 2.044-204.400, 2.251-225.000, 0.232 8-9.312 0, and 4.708-188.300 μg/mL, respectively (r>0.999 1), whose average recoveries were 95.02%-99.66% (RSD<3.0%). The analysis results showed that the quality of the most batches was stable. However, it was found that there were still slight differences in the quality of different batches of drugs by CA and PCA. Finally, six symbolic components causing the quality differences among batches were screened out by OPLS-DA, they were andrographolide, dehydroandrographolide, mussaenoside, shanzhiside methyl ester, 3,5-O-dicaffeoylquinic acid, and chlorogenic acid, respectively. Conclusion This simple, sensitive, and efficient method can be used for the rapid determination of main active components in YQT. The analysis of results combined with the chemical pattern recognition technology can comprehensively evaluate the drug quality as a whole, which provide new scientific basis and data processing methods for the quality control research of YQT.
[中图分类号]
[基金项目]
柳州市科技攻关项目(2018B0501a011)