Data-Dependent Neutral Gain MS super(3): Toward Automated Identification of the N-Oxide Functional Group in Drug Metabolites
We report here an automated method for the identification of N-oxide functional groups in drug metabolites by using the combination of liquid chromatography/tandem mass spectrometry (LC/MS super()n based on ion-molecule reactions and collision-activated dissociation (CAD). Data-dependent acquisition...
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Veröffentlicht in: | Journal of the American Society for Mass Spectrometry 2010-04, Vol.21 (4), p.559-563 |
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creator | Habicht, Steven C Vinueza, Nelson R Duan, Penggao Fu, Mingkun Kenttaemaa, Hilkka I |
description | We report here an automated method for the identification of N-oxide functional groups in drug metabolites by using the combination of liquid chromatography/tandem mass spectrometry (LC/MS super()n based on ion-molecule reactions and collision-activated dissociation (CAD). Data-dependent acquisition, which has been readily utilized for metabolite characterization using CAD-based methods, is adapted for use with ion-molecule reaction-based tandem mass spectrometry by careful choice of select experimental parameters. Two different experiments utilizing ion-molecule reactions are demonstrated, data-dependent neutral gain MS super(3) and data-dependent neutral gain pseudo-MS super(3), both of which generate functional group selective mass spectral data in a single experiment and facilitate increased throughput in structural elucidation of unknown mixture components. Initial results have been generated by using an LC/MS super()nmethod based on ion-molecule reactions developed earlier for the identification of the N-oxide functional group in pharmaceutical samples, a notoriously difficult functional group to identify via CAD alone. Since commercial software and straightforward, external instrument modification are used, these experiments are readily adaptable to the industrial pharmaceutical laboratory. |
doi_str_mv | 10.1016/j.jasms.2009.12.015 |
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Data-dependent acquisition, which has been readily utilized for metabolite characterization using CAD-based methods, is adapted for use with ion-molecule reaction-based tandem mass spectrometry by careful choice of select experimental parameters. Two different experiments utilizing ion-molecule reactions are demonstrated, data-dependent neutral gain MS super(3) and data-dependent neutral gain pseudo-MS super(3), both of which generate functional group selective mass spectral data in a single experiment and facilitate increased throughput in structural elucidation of unknown mixture components. Initial results have been generated by using an LC/MS super()nmethod based on ion-molecule reactions developed earlier for the identification of the N-oxide functional group in pharmaceutical samples, a notoriously difficult functional group to identify via CAD alone. 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Data-dependent acquisition, which has been readily utilized for metabolite characterization using CAD-based methods, is adapted for use with ion-molecule reaction-based tandem mass spectrometry by careful choice of select experimental parameters. Two different experiments utilizing ion-molecule reactions are demonstrated, data-dependent neutral gain MS super(3) and data-dependent neutral gain pseudo-MS super(3), both of which generate functional group selective mass spectral data in a single experiment and facilitate increased throughput in structural elucidation of unknown mixture components. Initial results have been generated by using an LC/MS super()nmethod based on ion-molecule reactions developed earlier for the identification of the N-oxide functional group in pharmaceutical samples, a notoriously difficult functional group to identify via CAD alone. 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subjects | Automated Computer aided design Drugs Functional groups Gain Mass spectrometry Metabolites Pharmaceuticals |
title | Data-Dependent Neutral Gain MS super(3): Toward Automated Identification of the N-Oxide Functional Group in Drug Metabolites |
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