Targeted protein degradation (TPD) is a promising new drug modality to remove specific cellular proteins. The assessment of degraders for TPD via mass spectrometry (MS)-based proteomics is particularly appealing for the unbiased discovery of novel targets for molecular glues, since rational drug design proves challenging for those molecules. Once identified by global proteomics, such drug target candidates need to be mechanistically validated, for example by demonstrating drug-induced target protein ubiquitination. We present a global ubiquitinomics workflow for detecting degrader drug induced protein ubiquitinations of ultra-low protein input samples, by combining an improved ubiquitin-remnant peptide enrichment workflow with single-shot LC-MS on the timsTOF Ultra, and a custom-made statistical analysis pipeline.

All samples were analyzed using a nanoElute® 2 (Bruker Daltonics) equipped with an Aurora Ultimate CSI 25 cm column (IonOpticks) coupled to either a timsTOF HT (Bruker Daltonics) or timsTOF Ultra (Bruker Daltonics). Chromatographic separation was done at 50°C on a 38 min active gradient with 45 min total runtime and a flow rate of 250 nL/min. The mass spectrometers were operated in dia-PASEF® mode using a slice-PASEF (1 frame - 15 windows) scheme. Raw data processing was performed using dia-NN 1.8.2 beta 22 and an in-house developed pipeline was used for downstream statistical analysis.

Quadruplicates of degrader drug-treated samples of low protein input (100 µg, no proteasome inhibitor added) were enriched for ubiquitin-remnant peptides (diGly of K-GG peptides) and split into three before data acquisition by slice-PASEF, on both the timsTOF HT and the timsTOF Ultra. Additionally, injection triplicates of samples with higher protein input (300 µg) were acquired on both systems. Peptides were separated on an Aurora Ultimate CSI 25 cm column and a nanoElute 2 nano-LC in both cases.

Using a predicted spectral library in dia-NN, sample measurements on the timsTOF HT resulted in 14,500-17,600 identified K-GG peptides when excluding the samples of higher protein input. By including the high input samples to the data processing with match between runs (MBR), the number of identified K-GG peptides was increased to 16,600-23,500.

Strikingly, when comparing the low-input samples without MBR, the number of identified K-GG peptides was increased by 52% on average on the timsTOF Ultra. Inclusion of high-input samples for MBRs led to increased K-GG peptide identifications to 27,000-34,000, corresponding to an increase of 46% as compared to the timsTOF HT. The high scanning speed (FWHM in scans: 4.5) of the timsTOF instruments resulted in an excellent quantitative precision (CVs between 7.1% and 8.6% per condition, on protein level)

Finally, a direct comparison of both LS-MS platforms revealed a much better sensitivity of the timsTOF Ultra for detecting degrader drug-induced ubiquitination events.