采用 HPLC 结合化学计量学方法对茯苓多糖进行多指纹图谱分析。
Multiple-fingerprint analysis of Poria cocos polysaccharide by HPLC combined with chemometrics methods.
机构信息
Shanghai Key Laboratory of Functional Materials Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, China.
Shanghai Institute for Food and Drug Control, National Medical Products Administration Key Laboratory for Monitoring and Evaluation of Cosmetics, Shanghai, 201203, China.
出版信息
J Pharm Biomed Anal. 2021 May 10;198:114012. doi: 10.1016/j.jpba.2021.114012. Epub 2021 Mar 6.
In this study, the multiple fingerprints, which were integrated with HPGFC-ELSD (high performance gel filtration chromatography - evaporative light scattering detector) fingerprint, PMP-HPLC-DAD (1-phenyl-3-methyl-5-pyrazolone-high performance liquid chromatography - diode array detector) fingerprint of complete acid hydrolysates and HILIC-HPLC-ELSD (hydrophilic interaction - high performance liquid chromatography - evaporative light scattering detector) fingerprint of enzyme hydrolysates, were established to evaluate the quality of polysaccharides from Poria cocos (PCPs). The similarity evaluation showed that 16 batches of PCPs from different origins had high similarity in structural characteristics based on the multiple fingerprints. The chromatographic data of multiple fingerprints of PCPs were fused, processed and analyzed by chemometric methods including HCA (hierarchical cluster analysis), PCA (principal component analysis) and PLS-DA (partial least squares discriminant analysis). The 16 batches of PCPs were divided into 3 categories in PCA, indicating a certain relationship between the structural characteristics and the origins. PLS-DA analysis indicated that Man, Glc, Gal, Fuc, the components with m/z of 2.22 × 10∼1.53 × 10 Da and 3.46 × 10∼2.69 × 10 Da, oligosaccharides with DPs of 6 and 7, respectively, could be regarded as potential chemical markers for the classification of PCPs from different origins. According to the multiple fingerprints and chemometric analysis, the two commercial samples were proved to be adulterants.
在这项研究中，建立了包含 HPGFC-ELSD（高效凝胶过滤色谱-蒸发光散射检测器）指纹、PMP-HPLC-DAD（1-苯基-3-甲基-5-吡唑酮-高效液相色谱-二极管阵列检测器）完全酸水解产物指纹和 HILIC-HPLC-ELSD（亲水相互作用-高效液相色谱-蒸发光散射检测器）酶解产物指纹的多糖的多指纹图谱，以评估茯苓多糖（PCPs）的质量。相似度评价表明，基于多指纹图谱，来自不同来源的 16 批 PCPs 在结构特征上具有高度相似性。采用化学计量学方法（包括层次聚类分析（HCA）、主成分分析（PCA）和偏最小二乘判别分析（PLS-DA））对 PCPs 多指纹图谱的色谱数据进行融合、处理和分析。在 PCA 中，将 16 批 PCPs 分为 3 类，表明结构特征与来源之间存在一定的关系。PLS-DA 分析表明，Man、Glc、Gal、Fuc、m/z 为 2.22×10∼1.53×10 Da 和 3.46×10∼2.69×10 Da 的成分、DP 分别为 6 和 7 的寡糖可以作为不同来源 PCPs 分类的潜在化学标志物。根据多指纹图谱和化学计量学分析，证明了这两个商业样本是掺杂物。
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