Parameter-Based Prioritization of Time-Resolved LC-HRMS Ion Tracks for Untargeted Reaction Monitoring

Herein, an automated, parameter-based workflow is introduced for processing time-resolved high-resolution mass spectrometry (HRMS) data. Its utility is demonstrated using the reaction between the ABTS^•+ radical cation and the polyphenolic antioxidant naringenin. Data were collected using HRMS coupled to high-performance liquid chromatography (HPLC) in negative ion mode. The algorithm compares sequential time-resolved HRMS measurements to generate kinetic curves and calculate parameters for every detected species. Based on these curves and parameters, we can tentatively classify each species as a reagent, intermediate, or product. The algorithm was implemented as Java-based software. As a result, extensive data arrays of 1.3 million m/z-intensity pairs per experimental series were processed automatically. The workflow generated manageable candidate sets in each replicate series. Cross-replicate matching using a 5 ppm mass tolerance retained 29 ion tracks consistently detected in all three reaction runs for subsequent analysis. These ions can then be examined manually to identify compound structures. Overall, the approach provides a screening tool for untargeted reaction monitoring and supports subsequent structural annotation in complex chemical systems.