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    常通舒颗粒HPLC指纹图谱及多指标成分含量测定研究

    Study on HPLC Fingerprint and Multiple Index Components Determination of Changtongshu Granules

      摘要
    • 摘要:
      目的  建立常通舒颗粒的HPLC指纹图谱及多指标成分含量测定方法。
      方法 采用HPLC建立常通舒颗粒指纹图谱，通过中药指纹图谱相似度评价系统软件对3家企业22批样品进行相似度评价；采用Agilent ZORBAX SB-C18色谱柱(250 mm×4.6 mm，5 μm)，乙腈-0.2%磷酸水梯度洗脱，柱温35 ℃，流速1 mL·min−1，测定常通舒颗粒中没食子酸、原儿茶酸、芍药苷、二苯乙烯苷、苯甲酸、大黄素的含量；以聚类分析、主成分分析和正交-偏最小二乘法判别分析对样品质量进行评价。
      结果 标示了12个共有峰，指认了7个成分，与对照图谱相比，3个企业22批样品中，只有3批样品相似度>0.96，1批样品相似度>0.87，其余样品相似度在0.627~0.859；聚类分析将A企业聚为一类，B企业聚为一类，C企业聚为另一类；主成分分析显示6个主成分的累计方差贡献率为94.447%，三维模型分类结果与聚类分析一致；正交-偏最小二乘法判别分析筛选出没食子酸、原儿茶酸、芍药苷、二苯乙烯苷、苯甲酸、大黄素6个差异性成分。
      结论 本实验建立的方法准确，简单，重复性好，可用于常通舒颗粒的质量控制与评价。

       

      Abstract:
      OBJECTIVE  To establish the HPLC fingerprint of Changtongshu granules, and components determination methods of multi-index component.
      METHODS  HPLC was used to create the fingerprint of Changtongshu granules, and to evaluate the similarity of 22 batches of samples from 3 companies by the similarity evaluation system software for traditional Chinese medicine fingerprint. With Agilent ZORBAX SB-C18 chromatographic column(250 mm×4.6 mm, 5 μm), acetonitrile-0.2% phosphoric acid as mobile phase of gradient elution, column temperature of 35 °C, flow rate of 1 mL·min−1. To determine the contents of gallic acid, protocatechin acid, paeoniflorin, 2,3,5,4’-tetrahydroxy stilbene-2-O-β-D-glucoside, benzoic acid and emodin. The quality of sample was evaluated using cluster analysis, principal component analysis and orthogonal partial least squares method-discriminant analysis.
      RESULTS  A total of 12 common peaks were identified, and 7 components were identified. Comparing the 22 batches of samples from 3 different companies with the reference fingerprint, only 3 batches of samples had a similarity above 0.96, 1 sample greater than 0.87, while the similarity of the remaining samples ranged from 0.627 to 0.859. Though cluster analysis, the sample from manufacturer A were clustered into group Ⅰ, the sample from manufacturer B were clustered into group Ⅱ, and the sample from manufacturer C was clustered into group Ⅲ. Principal component analysis showed that the cumulative variance contribution rate of the six principal components was 94.447%, and the classification results of the three-dimensional model were consistent with cluster analysis. Based on orthogonal partial least squares method-discriminant analysis, 6 components with large differences were identified, including gallic acid, protocatechin acid, paeoniflorin, 2,3,5,4’-tetrahydroxy stilbene-2-O-β-D-glucoside, benzoic acid, and emodin.
      CONCLUSION  The established method is accurate, simple and good repeatability, and it can be used for Chuantongshu granules quality control and evaluation.

       

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