Screening of bioactive components from traditional Chinese medicine by immobilized β 2 adrenergic receptor coupled with high performance liquid chromatography/mass spectrometry

• Published in: Journal of chromatography. B, Analytical technologies in the biomedical and life sciences Vol. 1134-1135; p. 121782
• Main Authors: Gao, Xiaokang, Yang, Lingjian, Bai, Yajun, Li, Qian, Zhao, Xinfeng, Bian, Liujiao, Zheng, Xiaohui
• Format: Journal Article
• Language: English
• Published: Netherlands 15.12.2019
• Subjects: Berberine Alkaloids - analysis; Berberine Alkaloids - metabolism; Chromatography, Affinity - methods; Chromatography, High Pressure Liquid - methods; Corydalis - chemistry; Drug Evaluation, Preclinical - methods; Drugs, Chinese Herbal - analysis; Drugs, Chinese Herbal - metabolism; Receptors, Adrenergic, beta-2 - chemistry; Receptors, Adrenergic, beta-2 - metabolism
• ISSN: 1873-376X

Traditional Chinese medicine (TCM) represents a valuable resource for lead compounds discovery. Given the complexity of TCM components, analytical methods play a key role in novel drug development. In our study, we established a high specific and reliable bio-active components screen system, where β adrenergic receptor (β -AR) was immobilized on silica by non-covalent bonds and packed into a stainless steel column (4.6 × 50 mm, 7 μm) to form β -AR chromatography column. The column was further coupled with high performance liquid chromatography-time of flight tandem mass spectrometry (TOF-MS/MS). By utilizing this strategy, we successfully identified four β -AR-targeting compounds: tetrahydroberberine, tetrahydrocolumbamine, fumarine and corydaline from Corydalis Rhizome. The association constants between β -AR and tetrahydroberberine (9.04 × 10 /M) as well as fumarine (4.30 × 10 /M) were determined by frontal chromatography. We also found that these two compounds shared the identical binding site on immobilized β -AR with corresponding concentrations of 6.67 × 10  M and 5.88 × 10  M, respectively. The newly established method represents an efficient tool to identify the target specific natural compounds.