Int. J. Mol. Sci. 2013, 14(10), 19716-19730; doi:10.3390/ijms141019716
Technical Note

A Computational Drug Metabolite Detection Using the Stable Isotopic Mass-Shift Filtering with High Resolution Mass Spectrometry in Pioglitazone and Flurbiprofen

1 Toxicology and Pharmacokinetics Laboratories, Pharmaceutical Research Laboratories, Toray Industries, Inc., 6-10-1 Tebiro, Kamakura, Kanagawa 248-8555, Japan 2 Reifycs Inc., AIOS Toranomon 10F, 1-6-12 Nishishinbashi, Minato-ku, Tokyo 105-0003, Japan 3 Measurement Assistance Center, Agilent Technologies Japan, Ltd., 9-1 Takakura, Hachioji, Tokyo 192-8510, Japan
* Author to whom correspondence should be addressed.
Received: 22 July 2013; in revised form: 4 September 2013 / Accepted: 9 September 2013 / Published: 30 September 2013
(This article belongs to the Special Issue Xenobiotic Metabolism)
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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.
Keywords: drug metabolites; metabolites identification; mass spectrometry (MS); stable isotope; analytical software

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MDPI and ACS Style

Uchida, M.; Kanazawa, M.; Ogiwara, A.; Sezaki, H.; Ando, A.; Miyamoto, Y. A Computational Drug Metabolite Detection Using the Stable Isotopic Mass-Shift Filtering with High Resolution Mass Spectrometry in Pioglitazone and Flurbiprofen. Int. J. Mol. Sci. 2013, 14, 19716-19730.

AMA Style

Uchida M, Kanazawa M, Ogiwara A, Sezaki H, Ando A, Miyamoto Y. A Computational Drug Metabolite Detection Using the Stable Isotopic Mass-Shift Filtering with High Resolution Mass Spectrometry in Pioglitazone and Flurbiprofen. International Journal of Molecular Sciences. 2013; 14(10):19716-19730.

Chicago/Turabian Style

Uchida, Masashi; Kanazawa, Mitsuhiro; Ogiwara, Atsushi; Sezaki, Hiroshi; Ando, Akihiro; Miyamoto, Yohei. 2013. "A Computational Drug Metabolite Detection Using the Stable Isotopic Mass-Shift Filtering with High Resolution Mass Spectrometry in Pioglitazone and Flurbiprofen." Int. J. Mol. Sci. 14, no. 10: 19716-19730.

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