Systematic Optimization of Activity-Based Protein Profiling for Identification of Polysorbate-Degradative Enzymes in Biotherapeutic Drug Substance down to 10 ppb.

Abstract

The identification and control of high-risk host cell proteins (HCPs) in biotherapeutics development are crucial for ensuring product quality and shelf life. Specifically, HCPs with hydrolase activity can cause the degradation of excipient polysorbates (PS), leading to a decrease in the shelf life of the drug product. In this study, we systematically optimized every step of an activity-based protein profiling (ABPP) workflow to identify trace amounts of active polysorbate-degradative enzymes (PSDEs) in biotherapeutic process intermediates. Evaluation of various parameters during sample preparation pinpointed the optimal pH level and fluorophosphonate (FP)-biotin concentration. Moreover, the combined use of a short liquid chromatography gradient and the fast-scanning parallel accumulation-serial fragmentation (PASEF) methodology increased sample throughput without compromising identification coverage. Tuning the trapped ion mobility spectrometry (TIMS) parameters further enhanced sensitivity. In addition, we evaluated various data acquisition modes, including PASEF combined with data-dependent acquisition (DDA PASEF), data-independent acquisition (diaPASEF), or parallel reaction monitoring (prm-PASEF). By employing the newly optimized ABPP workflow, we successfully identified PSDEs at a concentration as low as 10 ppb in a drug substance sample. Finally, the new workflow enabled us to detect a PSDE that could not be detected with the original workflow during a PS degradation root-cause investigation.