化学
质谱法
代谢物
色谱法
碎片(计算)
离子阱
质量
质谱
四极离子阱
四极杆质量分析仪
三级四极质谱仪
分辨率(逻辑)
分析化学(期刊)
串联质谱法
选择性反应监测
生物化学
人工智能
操作系统
计算机科学
作者
Haiying Zhang,Donglu Zhang,Kenneth L. Ray,Mingshe Zhu
摘要
Identification of drug metabolites by liquid chromatography/mass spectrometry (LC/MS) involves metabolite detection in biological matrixes and structural characterization based on product ion spectra. Traditionally, metabolite detection is accomplished primarily on the basis of predicted molecular masses or fragmentation patterns of metabolites using triple-quadrupole and ion trap mass spectrometers. Recently, a novel mass defect filter (MDF) technique has been developed, which enables high-resolution mass spectrometers to be utilized for detecting both predicted and unexpected drug metabolites based on narrow, well-defined mass defect ranges for these metabolites. This is a new approach that is completely different from, but complementary to, traditional molecular mass- or MS/MS fragmentation-based LC/MS approaches. This article reviews the mass defect patterns of various classes of drug metabolites and the basic principles of the MDF approach. Examples are given on the applications of the MDF technique to the detection of stable and chemically reactive metabolites in vitro and in vivo. Advantages, limitations, and future applications are also discussed on MDF and its combinations with other data mining techniques for the detection and identification of drug metabolites.
科研通智能强力驱动
Strongly Powered by AbleSci AI