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Drug Metabolism and Disposition Fast Forward
First published on June 30, 2006; DOI: 10.1124/dmd.106.009241


0090-9556/06/3410-1722-1733$20.00
DMD 34:1722-1733, 2006

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Detection and Characterization of Metabolites in Biological Matrices Using Mass Defect Filtering of Liquid Chromatography/High Resolution Mass Spectrometry Data

Mingshe Zhu, Li Ma, Donglu Zhang, Kenneth Ray1, Weiping Zhao, W. Griffith Humphreys, Gary Skiles2, Mark Sanders, and Haiying Zhang

Pharmaceutical Candidate Optimization, Bristol-Myers Squibb Pharmaceutical Research Institute, Princeton, New Jersey

An improved mass defect filter (MDF) method employing both drug and core structure filter templates was applied to the processing of high resolution liquid chromatography/mass spectrometry (LC/MS) data for the detection and structural characterization of oxidative metabolites with mass defects similar to or significantly different from those of the parent drugs. The effectiveness of this approach was investigated using nefazodone as a model compound, which is known to undergo multiple common and uncommon oxidative reactions. Through the selective removal of all ions that fall outside of the preset filter windows, the MDF process facilitated the detection of all 14 nefazodone metabolites presented in human liver microsomes in the MDF-filtered chromatograms. The capability of the MDF approach to remove endogenous interferences from more complex biological matrices was examined by analyzing omeprazole metabolites in human plasma. The unprocessed mass chromatogram showed no distinct indication of metabolite peaks; however, after MDF processing, the metabolite peaks were easily identified in the chromatogram. Compared with precursor ion scan and neutral loss scan techniques, the MDF approach was shown to be more effective for the detection of metabolites in a complex matrix. The comprehensive metabolite detection capability of the MDF approach, together with accurate mass determination, makes high resolution LC/MS a useful tool for the screening and identification of both common and uncommon drug metabolites.


Address correspondence to: Dr. Haiying Zhang, Bristol-Myers Squibb, Discovery Analytical and Bioanalytical Science, PCO, Princeton, NJ 08540-4000. E-mail: haiying.zhang{at}bms.com




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A. Liu, A. D. Patterson, Z. Yang, X. Zhang, W. Liu, F. Qiu, H. Sun, K. W. Krausz, J. R. Idle, F. J. Gonzalez, et al.
Fenofibrate Metabolism in the Cynomolgus Monkey using Ultraperformance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry-Based Metabolomics
Drug Metab. Dispos., June 1, 2009; 37(6): 1157 - 1163.
[Abstract] [Full Text] [PDF]




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