Li Austin C, Ding Jie, Jiang Xiangyu, Denissen Jon
Covance Laboratories Inc., 3301 Kinsman Boulevard, Madison, WI 53704-2523, USA.
Rapid Commun Mass Spectrom. 2009 Sep;23(18):3003-12. doi: 10.1002/rcm.4207.
The relatively high background matrix in in vivo samples typically poses difficulties in drug metabolite identification, and causes repeated analytical runs on unit resolution liquid chromatography/mass spectrometry (LC/MS) systems before the completion of biotransformation characterization. Ballpark parameter settings for the LTQ-Orbitrap are reported herein that enable complete in vivo metabolite identification within two HPLC/MS injections on the hybrid LTQ-Orbitrap data collection system. By setting the FT survey full scan at 60K resolution to trigger five dependent LTQ MS(2) scans, and proper parameters of Repeat Duration, Exclusion Duration and Repeat Count for the first run (exploratory), the Orbitrap achieved the optimal parallel data acquisition capability and collected maximum number of product ion scans. Biotransformation knowledge based prediction played the key role in exact mass ion extraction and multiple mass defect filtration when the initial data was processed. Meanwhile, product ion extraction and neutral loss extraction of the initial dependent data provided additional bonus in identifying metabolites. With updated parent mass list and the data-dependent setting to let only the ions on the parent mass list trigger dependent scans, the second run (confirmatory) ensures that all precursor ions of identified metabolites trigger not only dependent product ion scans, but also at or close to the highest concentration of the eluted metabolite peaks. This workflow has been developed for metabolite identification of in vivo or ADME studies, of which the samples typically contain a high level of complex matrix. However, due to the proprietary nature of the in vivo studies, this workflow is presented herein with in vitro buspirone sample incubated with human liver microsomes (HLM). The major HLM-mediated biotransformation on buspirone was identified as oxidation or hydroxylation since five mono- (+16 Da), seven di- (+32 Da) and at least three tri-oxygenated (+48 Da) metabolites were identified. Besides the metabolites 1-pyrimidinylpiperazine (1-PP) and hydroxylated 1-PP that formed by N-dealkylation, a new metabolite M308 was identified as the result of a second N-dealkylation of the pyrimidine unit. Two new metabolites containing the 8-butyl-8-azaspiro[4,5]decane-7,9-dione partial structure, M240 and M254, were also identified that were formed apparently due to the first N-dealkylation of the 1-PP moiety.
体内样品中相对较高的背景基质通常给药物代谢物鉴定带来困难,并导致在生物转化特征完成之前,在单位分辨率液相色谱/质谱(LC/MS)系统上进行重复的分析运行。本文报道了LTQ-Orbitrap的大致参数设置,该设置能够在混合LTQ-Orbitrap数据采集系统上通过两次HPLC/MS进样完成体内代谢物的完整鉴定。通过将FT全扫描设置为60K分辨率以触发五次相关的LTQ MS(2)扫描,以及为第一次运行(探索性)设置适当的重复持续时间、排除持续时间和重复次数参数,Orbitrap实现了最佳的并行数据采集能力并收集了最大数量的产物离子扫描。在处理初始数据时,基于生物转化知识的预测在精确质量离子提取和多重质量缺陷过滤中起关键作用。同时,初始相关数据的产物离子提取和中性丢失提取在代谢物鉴定方面提供了额外的帮助。通过更新母体质列表并设置数据依赖,使得只有母体质列表上的离子触发相关扫描,第二次运行(确证性)确保已鉴定代谢物的所有前体离子不仅触发相关的产物离子扫描,而且在洗脱代谢物峰的最高浓度处或接近该浓度处触发扫描。此工作流程是为体内或ADME研究的代谢物鉴定而开发的,这些研究的样品通常含有高水平的复杂基质。然而,由于体内研究的保密性,本文以与人类肝微粒体(HLM)孵育的体外丁螺环酮样品展示此工作流程。丁螺环酮主要的HLM介导的生物转化被鉴定为氧化或羟基化,因为鉴定出了五种单加氧(+16 Da)、七种双加氧(+32 Da)和至少三种三加氧(+48 Da)代谢物。除了通过N-脱烷基化形成的代谢物1-嘧啶基哌嗪(1-PP)和羟基化的1-PP外,一种新的代谢物M308被鉴定为嘧啶单元第二次N-脱烷基化的结果。还鉴定出了两种含有8-丁基-8-氮杂螺[4,5]癸烷-7,9-二酮部分结构的新代谢物M240和M254,它们显然是由于1-PP部分的第一次N-脱烷基化形成的。