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In silico methods for predicting metabolism and mass fragmentation applied to quetiapine in liquid chromatography/time‐of‐flight mass spectrometry urine drug screening
Author(s) -
Pelander Anna,
Tyrkkö Elli,
Ojanperä Ilkka
Publication year - 2009
Publication title -
rapid communications in mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 136
eISSN - 1097-0231
pISSN - 0951-4198
DOI - 10.1002/rcm.3901
Subject(s) - chemistry , chromatography , metabolite , mass spectrometry , urine , context (archaeology) , fragmentation (computing) , biochemistry , paleontology , computer science , biology , operating system
Current in silico tools were evaluated for their ability to predict metabolism and mass spectral fragmentation in the context of analytical toxicology practice. A metabolite prediction program (Lhasa Meteor), a metabolite detection program (Bruker MetaboliteDetect), and a fragmentation prediction program (ACD/MS Fragmenter) were used to assign phase I metabolites of the antipsychotic drug quetiapine in the liquid chromatography/time‐of‐flight mass spectrometry (LC/TOFMS) accurate mass data from ten autopsy urine samples. In the literature, the main metabolic routes of quetiapine have been reported to be sulfoxidation, oxidation to the corresponding carboxylic acid, N ‐ and O ‐dealkylation and hydroxylation. Of the 14 metabolites predicted by Meteor, eight were detected by LC/TOFMS in the urine samples with use of MetaboliteDetect software and manual inspection. An additional five hydroxy derivatives were detected, but not predicted by Meteor. The fragment structures provided by ACD/MS Fragmenter software confirmed the identification of the metabolites. Mean mass accuracy and isotopic pattern match (SigmaFit) values for the fragments were 2.40 ppm (0.62 mDa) and 0.010, respectively. ACD/MS Fragmenter, in particular, allowed metabolites with identical molecular formulae to be differentiated without a need to access the respective reference standards or reference spectra. This was well exemplified with the hydroxy/sulfoxy metabolites of quetiapine and their N ‐ and O ‐dealkylated forms. The procedure resulted in assigning 13 quetiapine metabolites in urine. The present approach is instrumental in developing an extensive database containing exact monoisotopic masses and verified retention times of drugs and their urinary metabolites for LC/TOFMS drug screening. Copyright © 2009 John Wiley & Sons, Ltd.