Rapid screening and characterization of drug metabolites using multiple ion monitoring dependent product ion scan and postacquisition data mining on a hybrid triple quadrupole-linear ion trap mass spectrometer.

Multiple ion monitoring (MIM)-dependent acquisition with a triple quadrupole-linear ion trap mass spectrometer (Q-trap) was previously developed for drug metabolite profiling. In the analysis, multiple predicted metabolite ions are monitored in both Q1 and Q3 regardless of their fragmentations. The collision energy in Q2 is set to a low value to minimize fragmentation. Once an expected metabolite is detected by MIM, enhanced product ion (EPI) spectral acquisition of the metabolite is triggered. To analyze in vitro metabolites, MIM-EPI retains the sensitivity and selectivity similar to that of multiple reaction monitoring (MRM)-EPI in the analysis of in vitro metabolites. Here we present an improved approach utilizing MIM-EPI for data acquisition and multiple data mining techniques for detection of metabolite ions and recovery of their MS/MS spectra. The postacquisition data processing tools included extracted ion chromatographic analysis, product ion filtering and neutral loss filtering. The effectiveness of this approach was evaluated by analyzing oxidative metabolites of indinavir and glutathione (GSH) conjugates of clozapine and 4-ethylphenol in liver microsome incubations. Results showed that the MIM-EPI-based data mining approach allowed for comprehensive detection of metabolites based on predicted protonated molecules, product ions or neutral losses without predetermination of the parent drug MS/MS spectra. Additionally, it enabled metabolite detection and MS/MS acquisition in a single injection. This approach is potentially useful in high-throughout screening of metabolic soft spots and reactive metabolites at the drug discovery stage.