Abstract
The identification of metabolites in drug discovery is important. At present, radioisotopes and mass spectrometry are both widely used. However, rapid and comprehensive identification is still laborious and difficult. In this study, we developed new analytical software and employed a stable isotope as a tool to identify drug metabolites using mass spectrometry. A deuterium-labeled compound and non-labeled compound were both metabolized in human liver microsomes and analyzed by liquid chromatography/time-of-flight mass spectrometry (LC-TOF-MS). We computationally aligned two different MS data sets and filtered ions having a specific mass-shift equal to masses of labeled isotopes between those data using our own software. For pioglitazone and flurbiprofen, eight and four metabolites, respectively, were identified with calculations of mass and formulas and chemical structural fragmentation analysis. With high resolution MS, the approach became more accurate. The approach detected two unexpected metabolites in pioglitazone, i.e., the hydroxypropanamide form and the aldehyde hydrolysis form, which other approaches such as metabolite-biotransformation list matching and mass defect filtering could not detect. We demonstrated that the approach using computational alignment and stable isotopic mass-shift filtering has the ability to identify drug metabolites and is useful in drug discovery.
Highlights
Identifying metabolites is crucial to the drug discovery process
Pioglitazone, pioglitazone-d4, flurbiprofen and flurbiprofen-d3 were incubated in human liver microsomes, individually, and these reaction mixtures were analyzed by liquid chromatography (LC)-TOF-mass spectrometry (MS) separately
The data from the deuterium-labeled and un-labeled compounds were aligned, and particular ions that had the same retention times, a similar signal intensity and a specific mass-shift of 4.00 ± 0.04 Da and 3.00 ± 0.03 Da were captured in pioglitazone and flurbiprofen, respectively
Summary
Identifying metabolites is crucial to the drug discovery process. Generally, drug metabolism is a detoxification step in vivo [1]. We have developed a post-processing filtering approach for identifying drug metabolites using MS and new analytical software. Stable isotope-labeled compounds are widely used as internal standards for the quantification and as tracers for the structural identification of candidates and their metabolites [12,13,14]. Our results indicated that filtering a specific mass-shift equal to the labeled isotopic mass represents a fast and comprehensive method for identification of drug metabolites. We used a stable isotope as a detection tool in drug metabolite identification, and have developed this approach with new analytical software that can visually filter particular ions having a specific mass-shift. A computationally accurate alignment of detected ions in LC/MS data enables the detection and visual inspection of twin ions, which are derived from different LC/MS measurements
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