Identification of prototypes from Ligustri Lucidi Fructus in rat plasma based on a data-dependent acquisition and multicomponent pharmacokinetic study.
Yucheng WangKeyu FengMengrong LiLi-Feng HanWeiqiang WangDandan SiXiaopeng ChenWenzhi YangXiumei GaoErwei LiuPublished in: Biomedical chromatography : BMC (2020)
The identification and quantization of traditional Chinese medicine (TCM) are a challenge for researchers and industry. Using untargeted analytical methods, the in vivo detection and identification of TCM compounds are difficult because of the significant interference of endogenous substances. Fortunately, the ongoing development of new analytical technologies, especially Q-Orbitrap-MS, offers some solutions. Our team developed a holistic MS method, combining untargeted data-dependent MS2 (dd-MS2 ) modes to extensively identify TCM prototypes in vivo. The method was successfully applied to the analysis of Ligustri Lucidi Fructus (LLF). LLF is a widely used TCM with a remarkable nourishing effect on the liver and kidney. In the study, we aimed to identify the prototypes in rat plasma after oral administration of LLF extract. Following separation on an HSS T3 column, LLF extract and rat plasma were performed in untargeted dd-MS2 mode. Forty-seven compounds were characterized in rats plasma as prototypes of LLF extract. Furthermore, seven major prototypes were chosen as pharmacokinetic markers to investigate LLF's pharmacokinetic properties. The results provides comprehensive determination of compounds in LLF both in vitro and in vivo, which is important for quality control, pharmacology studies and clinical use of LLF.
Keyphrases
- mass spectrometry
- liquid chromatography
- high resolution mass spectrometry
- tandem mass spectrometry
- solid phase extraction
- ms ms
- gas chromatography
- multiple sclerosis
- high resolution
- simultaneous determination
- ultra high performance liquid chromatography
- quality control
- oxidative stress
- bioinformatics analysis
- electronic health record
- anti inflammatory
- artificial intelligence
- quality improvement
- gas chromatography mass spectrometry
- case control