(M1030-08-49) Automated Workflow to Study Microsomal Clearance and Analysis of Metabolites Using Collision-Induced Dissociation and Electron-Activated Dissociation

Purpose: Studies of in vitro metabolism of drugs in human and animal tissues help to predict the metabolic clearance rate of compounds and identify major metabolism pathways ("soft spots"). For such studies, metabolite identification is critical and is often software-aided to ensure proper metrics are used for confident identification and prediction of the metabolism site. A software-aided methodology was developed to quantitatively study microsomal clearance and qualitatively identify the soft-spots for metabolism, aiding in the acceleration of the early drug discovery process. Datasets from collision induced dissociation (CID) and electron activated dissociation (EAD) were applied to predict the sites of metabolism.
Methods: Various drugs were incubated at 37°C in human hepatocytes and rat liver microsomes at starting concentrations of 1-5µM. Samples were quenched with acetonitrile at 0-, 30-, 60-, 90-, 120- and 240-minute intervals. Separation was performed on a Phenomenex Kinetex Polar C18 column (2.1 x 100 mm, 2.6 µm, 100 Å) operated at 40°C. Mobile phase A was 0.1% formic acid in water and mobile phase B was 0.1% formic acid in acetonitrile. The sample injection volume was 5 µL. Analysis was performed using a data-dependent acquisition (DDA) method with traditional fragmentation (Zeno CID) and orthogonal fragmentation (Zeno EAD) on the ZenoTOF 7600 system. The Molecule Profiler software was used for the analysis of microsomal clearance and prediction of biotransformation sites.

Results: The DDA data provided excellent MS/MS coverage of TOF MS peaks of interest for both Zeno CID and Zeno EAD acquisitions. Automatic prediction of metabolites based on MS1 data and structural elucidation using the precursor and metabolite-specific fragment ions were performed with the Molecule Profiler software. Several phase 1 and phase 2 metabolites were identified and studied using Zeno CID and Zeno EAD MS/MS data. The Molecule Profiler software enabled processing and analysis of both Zeno CID and Zeno EAD data in a single file. The interpretation of the site of metabolism was enabled by the automated assignment of the structures by the software based on the relative weighting of Zeno EAD and Zeno CID MS/MS spectra on the scale of 1-100%. A correlation analysis was performed for drugs and metabolites by processing result table files from various time points to visualize a decrease in drug concentration relative to an increase in various metabolite concentrations. Correlation analysis and DDA acquisition enabled parent and metabolite product ion analysis to find the most prominent metabolites and provide a visual summary of metabolism. Metabolite and fragment identification were performed with less than 5 ppm error. The mass accuracy enabled the confident prediction of metabolites present in an in vitro metabolism study.

Conclusion: A quick software-aided analysis of microsomal clearance and identification of metabolites using collision-induced dissociation and electron-activated dissociation MS/MS data.