Targeted Data-Independent Acquisition and Mining Strategy for Trace Drug Metabolite Identification Using Liquid Chromatography Coupled with Tandem Mass Spectrometry.

Detection and identification of unknown or low-level drug-related metabolites in complex biological materials is an ongoing challenge. A highly selective and sensitive method could be a possible solution. Here, we proposed a targeted data-independent acquisition and mining (TDIAM) strategy for the rapid identification of trace drug metabolites using ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UHPLC-HRMS/MS). In this strategy, raw data is acquired by a novel tm-MS scan, which contains an interleaved full MS scan with a targeted mass range and a product ion scan by selecting all ions in the targeted mass range as precursor ions. For efficient discovery of metabolites, raw data are analyzed by a new postacquisition processing method, Molecule- and Fragmentation-driven Mass Defect Filters (MF-MDFs), which was developed based on the fragmentation of parent drug to pick out molecular ions and fragment ions of potential metabolites from the complex matrix. ...