HPLC指纹图谱技术结合PLS-DA在养阴清肺颗粒质量控制中的应用  

Application of HPLC Fingerprint and PLS-DA in Quality Control of Yangyin Qingfei Granules

作　　者：张薇[1] 张洁[1] 岳峰梅[1] Zhang Wei;Zhang Jie;Yue Fengmei(Department of Pharmacy,Shandong Provincial Hospital Affiliated to Shandong Un iversity,Ji'nan 250021,China)

机构地区：[1]山东大学附属省立医院药学部,济南250021

出　　处：《中国药师》2021年第2期218-222,共5页China Pharmacist

摘　　要：目的:建立养阴清肺颗粒的HPLC指纹图谱,结合偏最小二乘法-判别分析(PLS-DA),为其质量控制提供参考。方法:采用ZORBAX Eclipse XDB-C18色谱柱(250 mm×4.6 mm,5μm);流动相乙腈(A)-0.12%磷酸水溶液(B)梯度洗脱;体积流量:0.9 ml·min^(-1);分段检测波长为230 nm(检测芍药苷、甘草苷)、280 nm(检测麦冬甲基黄烷酮A)、254 nm(检测丹皮酚)、210 nm(检测梓醇、哈巴苷及哈巴俄苷)、330 nm(检测毛蕊花糖苷);柱温:30℃;进样量:10μl。用中药色谱指纹图谱相似度评价系统(2012A版)建立指纹图谱共有模式和相似度计算,用SIMCA14.1软件建立PLS-DA模型做统计分析。结果:建立12批养阴清肺颗粒的指纹图谱,共确定20个共有指纹峰,通过与对照品指认了8个成分;12批样品指纹图谱相似度为0.959~0.982,通过聚类分析(CA)可将12批样品聚成3类,结合主成分分析(PCA)、偏最小二乘法-判别分析(PLS-DA)发现8个成分是造成不同批次样品差异性的主要标记物。结论:该研究建立指纹图谱方法有助于养阴清肺颗粒整体质量控制,同时为其质量评价提供一种有效手段。Objective: To establish the HPLC fingerprint of Yangyin Qingfei granules to provide reference for their identification and quality control through combining discriminant analysis of partial least squares(PLS-DA). Methods: The separation was performed on a ZORBAX Eclipse XDB-C18 column(250 mm×4.6 mm,5 μm) with the mobile phase of acetonitrile and 0.12% phosphoric acid solution with gradient elution at a flow rate of 0.9 ml·min^(-1). The detection wavelength was set at 230 nm for paeoniflorin and liquiritin,280 nm for methylophiopogonanone A,254 nm for paeonol,210 nm for catalpol,harpagide and harpagoside,and 330 nm for verbascoside with the column temperature at 30 ℃,and the sample volume was 10 μl. The fingerprint common pattern and similarity calculation were established according to Traditional Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System(2012 A). The PLS-DA model was established by using SIMCA 14.1 software to perform statistical analysis. Results: The fingerprints of 12 batches of Yangyin Qingfei granules were established,and there were 20 common peaks with the similarity of 0.959-0.982. The samples were classified into three groups by hierarchical cluster analysis combined with principal component analysis(PCA) and discriminant analysis of partial least squares(PLS-DA),and 8 components were the main markers causing differences in the different batches of samples. Conclusion: The developed mode identification method is helpful to control the overall quality of Yangyin Qingfei granules,and it provides an effective approach for quality evaluation.

关 键 词：养阴清肺颗粒 指纹图谱 相似度 主成分分析 偏最小二乘法-判别分析 聚类分析 

分 类 号：TQ460.72[医药卫生—药物分析学]