Literature DB >> 23280752

An introduction to hybrid ion trap/time-of-flight mass spectrometry coupled with liquid chromatography applied to drug metabolism studies.

Zhao-Ying Liu1.   

Abstract

Metabolism studies play an important role at various stages of drug discovery and development. Liquid chromatography combined with mass spectrometry (LC/MS) has become a most powerful and widely used analytical tool for identifying drug metabolites. The suitability of different types of mass spectrometers for metabolite profiling differs widely, and therefore, the data quality and reliability of the results also depend on which instrumentation is used. As one of the latest LC/MS instrumentation designs, hybrid ion trap/time-of-flight MS coupled with LC (LC-IT-TOF-MS) has successfully integrated ease of operation, compatibility with LC flow rates and data-dependent MS(n) with high mass accuracy and mass resolving power. The MS(n) and accurate mass capabilities are routinely utilized to rapidly confirm the identification of expected metabolites or to elucidate the structures of uncommon or unexpected metabolites. These features make the LC-IT-TOF-MS a very powerful analytical tool for metabolite identification. This paper begins with a brief introduction to some basic principles and main properties of a hybrid IT-TOF instrument. Then, a general workflow for metabolite profiling using LC-IT-TOF-MS, starting from sample collection and preparation to final identification of the metabolite structures, is discussed in detail. The data extraction and mining techniques to find and confirm metabolites are discussed and illustrated with some examples. This paper is directed to readers with no prior experience with LC-IT-TOF-MS and will provide a broad understanding of the development and utility of this instrument for drug metabolism studies.
Copyright © 2012 John Wiley & Sons, Ltd.

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Year:  2012        PMID: 23280752     DOI: 10.1002/jms.3126

Source DB:  PubMed          Journal:  J Mass Spectrom        ISSN: 1076-5174            Impact factor:   1.982


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