4.4 Article

A novel approach to perform metabolite screening during the quantitative LC-MS/MS analyses of in vitro metabolic stability samples using a hybrid triple-quadrupole linear ion trap mass spectrometer

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JOURNAL OF MASS SPECTROMETRY
卷 40, 期 10, 页码 1347-1356

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JOHN WILEY & SONS LTD
DOI: 10.1002/jms.917

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drug discovery; metabolite screening; microsomes; stability measurements; time-concentration profiles; triple-quadrupole linear ion trap MS

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In vitro metabolic stability experiments using microsomes or other liver preparations are important components in the discovery and lead-optimization stages of compound selection in the pharmaceutical industry. Currently, liquid chromatography-tandem mass spectrometric (LC-MS/MS) support of in vitro metabolic stability studies primarily involves the monitoring of disappearance of parent compounds, using selected reaction monitoring (SRM) on triple-quadrupole instruments. If moderate to high turnover is observed, separate metabolite identification experiments are then conducted to characterize the biotransformation products. In this paper, we present a novel method to simultaneously perform metabolite screening in addition to the quantitative stability measurements, both within the same chromatographic run. This is accomplished by combining SRM and SRM-triggered, information-dependent acquisition (IDA) of MS/MS spectra on a hybrid triple-quadrupole linear ion trap (QqQ(LIT)) mass spectrometer. Microsomal stability experiments using model compounds, bufuralol, propranolol, imipramine, midazolam, verapamil and diclofenac, were used to demonstrate the applicability of our approach. This SRM + SRM-IDA approach generated metabolic stability results similar to those obtained by conventional SRM-only approach. In addition, MS/MS spectra from potential metabolites were obtained with the enhanced product ion (EPI) scan function of LIT during the same injection. These spectra were correlated to the spectra of parent compounds to confirm the postulated structures. The time-concentration profiles of identified metabolites were also estimated from the acquired data. This approach has been successfully used to support discovery programs. Copyright (c) 2005 John Wiley & Sons, Ltd.

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