A Rapid Methodology for the Characterization of Dialkyl Tertiary Amine-N-Oxide Metabolites Using Structurally Dependent Dissociation Pathways and Reconstructed Ion Current Chromatograms

摘要

A high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (HPLC-ESI-MS/MS) approach to the characterization of dialkyl tertiary amine-N-oxides is presented. The methodology is based upon forming reconstructed ion current chromatograms (RICCs) of m/z values of product ions known to form through diagnostic losses from dialkyl tertiary amine-N-oxides. The diagnostic losses of N,N-dimethylhydroxylamine and N,N-diethylhydroxylamine were identified through the analysis of a structurally diverse library of compounds by ESI-low-energy collision-induced dissociation (CID)-MS/MS using quadrupole ion trap-mass spectrometry (QIT-MS) and quadrupole time-of-flight-mass spectrometry (QqTOF-MS). The library consisted of dialkyl tertiary amine-containing commercially available pharmaceuticals, along with a number of model, synthetic N-oxides. The loss of the nitrogen-containing group was observed in 89percent of the low-energy CID product ion spectra acquired using various collision energies. Further, the resultant product ions, formed through the loss of the nitrogen-containing group, were shown to be unstable because of the observation of second-generation dissociation. These observations regarding gas-phase ion chemistry could be useful to developers of in silico programs for fragmentation prediction by allowing the creation of improved algorithms and models for predicting dissociation. Using the information derived from the library analysis, the characterization methodology was developed and demonstrated using tetracaine. The approach is rapid, MS/MS platform independent, utilizes existing technology, and could be automated. Further, it is definitive and overcomes the limitations of other tools for N-oxide identification by localizing the site of oxidation. Thus, it provides a useful addition to the existing approaches for metabolite identification.