defects lie outside of the window specified for drug-related ions. With a mass
defect window set approximately50 mDa from that of the parent drug, the
metabolite profile of dog bile was obtained with the majority of interference
ions removed (Zhang et al., 2003). The filtered ion chromatogram dramatically
simplified data interpretation and therefore facilitated the identification of both
common and uncommon metabolites. A similar approach was applied to
reduce the false positive entries in analyzing metabolites in liver microsomal
incubations (Mortishire-Smith et al., 2005).
Recently, Zhu and co-workers reported an improved MDF method
employing both drug and core structure filter templates to the processing of
high resolution LC/MS data for the detection and structural characterization
of metabolites with mass defects similar to, or significantly different from,
those of the parent drugs (Zhu et al., 2006). The effectiveness of MDF for
detecting metabolites in complex biological samples was further demonstrated
from the analysis of omeprazole metabolites in human plasma. The
unprocessed total ion chromatogram showed no distinct metabolite peaks
(Fig. 11.5a). After MDF processing, however, the metabolite peaks were easily
FIGURE 11.5 Chromatographic profiles of omeprazole samples analyzed by a Q-TOF
LC/MS system and after examination by the MDF approach. (a) and (b) are TIC
profiles of plasma spiked with omeprazole metabolites obtained without and with MDF
processing, respectively. Reprinted from Zhu et al. (2006) with permission of the
American Society for Pharmacology and Experimental Therapeutics.
SOFTWARE-ASSISTED METABOLITE IDENTIFICATION 347