Systematic Optimization\nof Activity-Based Protein\nProfiling for Identification of Polysorbate-Degradative Enzymes in\nBiotherapeutic Drug Substance down to 10 ppb

The identification and control of high-risk host cell\nproteins\n(HCPs) in biotherapeutics development are crucial for ensuring product\nquality and shelf life. Specifically, HCPs with hydrolase activity\ncan cause the degradation of excipient polysorbates (PS), leading\nto a decrease in the shelf life of the drug product. In this study,\nwe systematically optimized every step of an activity-based protein\nprofiling (ABPP) workflow to identify trace amounts of active polysorbate-degradative\nenzymes (PSDEs) in biotherapeutic process intermediates. Evaluation\nof various parameters during sample preparation pinpointed the optimal\npH level and fluorophosphonate (FP)-biotin concentration. Moreover,\nthe combined use of a short liquid chromatography gradient and the\nfast-scanning parallel accumulation–serial fragmentation (PASEF)\nmethodology increased sample throughput without compromising identification\ncoverage. Tuning the trapped ion mobility spectrometry (TIMS) parameters\nfurther enhanced sensitivity. In addition, we evaluated various data\nacquisition modes, including PASEF combined with data-dependent acquisition\n(DDA PASEF), data-independent acquisition (diaPASEF), or parallel\nreaction monitoring (prm-PASEF). By employing the newly optimized\nABPP workflow, we successfully identified PSDEs at a concentration\nas low as 10 ppb in a drug substance sample. Finally, the new workflow\nenabled us to detect a PSDE that could not be detected with the original\nworkflow during a PS degradation root-cause investigation.