In vivo metabolite detection and identification in drug discovery via LC-MS/MS with data-dependent scanning and postacquisition data mining.

An important aspect in drug discovery is the early structural identification of the metabolites of potential new drugs. This gives information on the metabolically labile points in the molecules under investigation, suggesting structural modifications to improve their metabolic stability, and allowing an early safety assessment via the identification of metabolic activation products. From an analytical point of view, metabolite identification still remains a challenging task, especially for in vivo samples, in which they occur at trace levels together with high amounts of endogenous compounds. Here we describe a method, based on LC-ion trap tandem MS, for the rapid in vivo metabolite identification. It is based on the automatic, data-dependent acquisition of multiple product ion MS/MS scans, followed by a postacquisition search, within the entire MS/MS data set obtained, for specific neutral losses or marker ions in the tandem mass spectra of parent molecule and putative metabolites. One advantage of the method is speed, since it requires minimum sample preparation and all the necessary data can be obtained in one chromatographic run. In addition, it is highly sensitive and selective, allowing detection of trace metabolites even in the presence of a complex matrix. As an example of application, we present the studies of the in vivo metabolism of the compound MEN 15916 (1). The method allowed identification of monohydroxy ([M + H](+) = m/z 655), dihydroxy ([M + H](+) = m/z 671), and trihydroxy ([M + H](+) = m/z 687) metabolites, as well as some unexpected biotransformation products such as a carboxylic acid ([M + H](+) = m/z 669), a N-dealkylated metabolite ([M + H](+) = m/z 541), and its hydroxy-analog ([M + H](+) = m/z 557).