School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Hwa Mei Hospital, University of Chinese Academy of Sciences (Ningbo No. 2 Hospital), Ningbo, China.
Phytochem Anal. 2022 Aug;33(6):943-960. doi: 10.1002/pca.3150. Epub 2022 Jun 20.
Pharmacological studies indicate that Astragalus (AR) has various bioactivities, including anticancer, antiaging, anti-inflammatory, antiviral, and antioxidant activities. Flavonoids, saponins, amino acids, and polysaccharides are the main active components in AR. However, its complex chemical compositions bring certain difficulties to the analysis of this traditional Chinese medicine (TCM). Therefore, there is an urgent need to establish a method for rapid classification and identification of the chemical constituents in AR.
To establish a method for rapid classification and identification of the main components of flavonoids, saponins, and amino acids in AR.
The samples were analysed with ultra-high-performance liquid chromatography time-of-flight quadrupole mass spectrometry (UPLC-Q-TOF-MS) and data post-processing techniques. Firstly, fragmentation information was obtained in the positive and negative ion modes. Then, to realize the rapid classification and identification of AR components, the characteristic fragmentations (CFs) and neutral losses (NLs) were compared with information described in the literature.
A total of 45 chemical constituents were successfully screened out, including 22 flavonoids, 13 saponins, and 10 amino acids.
The established method realised the efficient classification and identification of flavonoids, saponins, and amino acid compounds in AR, which provided a basis for further study on AR.
药理学研究表明，黄芪（AR）具有多种生物活性，包括抗癌、抗衰老、抗炎、抗病毒和抗氧化活性。黄酮类、皂苷类、氨基酸和多糖是 AR 的主要活性成分。然而，其复杂的化学成分给这种中药（TCM）的分析带来了一定的困难。因此，迫切需要建立一种快速分类和鉴定 AR 中化学成分的方法。
建立一种快速分类和鉴定 AR 中黄酮类、皂苷类和氨基酸主要成分的方法。
采用超高效液相色谱-飞行时间四级杆质谱联用（UPLC-Q-TOF-MS）及数据后处理技术对样品进行分析。首先，在正、负离子模式下获得碎片信息。然后，为了实现 AR 成分的快速分类和鉴定，比较了特征碎片（CFs）和中性损失（NLs）与文献中描述的信息。
共筛选出 45 种化学成分，包括 22 种黄酮类、13 种皂苷类和 10 种氨基酸。
所建立的方法实现了 AR 中黄酮类、皂苷类和氨基酸类化合物的高效分类和鉴定，为进一步研究 AR 提供了依据。
