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A strategy for qualitative and quantitative profiling of Angelicae Pubescentis Radix and detection of its analgesic and anti‐inflammatory components by spectrum–effect relationship and multivariate statistical analysis
Author(s) -
Hou Ajiao,
Yang Liu,
Zhang Jiaxu,
Wang Song,
Man Wenjing,
Guo Xinyue,
Yang Bingyou,
Kuang Haixue,
Li Bo,
Wang Qiuhong,
Jiang Hai
Publication year - 2020
Publication title -
biomedical chromatography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.4
H-Index - 65
eISSN - 1099-0801
pISSN - 0269-3879
DOI - 10.1002/bmc.4910
Subject(s) - chemistry , radix (gastropod) , bergapten , partial least squares regression , chemometrics , chromatography , qualitative analysis , high performance liquid chromatography , statistics , mathematics , psoralen , qualitative research , dna , social science , biochemistry , botany , sociology , biology
This study established a spectrum–effect relationship method for screening and quantifying the analgesic and anti‐inflammatory active ingredients in Angelicae Pubescentis Radix (AP) by ultra‐high‐performance liquid chromatography–quadrupole mass spectrometry detector analysis (UPLC–QDA). First, the fingerprint of AP was established to determine the common peaks. Next, six batches of AP samples, with significant differences, were selected for evaluation of pharmacological activity. Subsequently, the spectrum–effect relationship was used to screen the active ingredients. Finally, the screened ingredients were quantified using UPLC–QDA. In total, 21 common peaks were identified and four effective compounds (bergapten, columbianetin acetate, osthole and isoimperatorin) were selected using the gray relational analysis and partial least squares regression analysis. Quantitative analysis showed that the content of the four effective compounds was the highest in a randomly selected batch, S7 (Hubei). To our knowledge, this is the first attempt that evaluated the quality and spectrum–effect relationship of AP by quantitative analysis and chemometrics. This study identified the key pharmacologically active components of AP and thereby improved the quality evaluation system of AP. This method has broad application prospects for screening effective components and will be helpful in establishing more reliable, scientific and reasonable quality standards for AP and other traditional Chinese medicines.