Characterizing the target space of molecular glues and bifunctional degraders in cells and animal models by bottom-up proteomics

Targeted protein degradation facilitates the development of selective therapies against protein targets that were previously deemed "undruggable" by conventional inhibitors, for instance because they lack a distinctive active site. Characterizing the biological activity of degrader compounds, including proteolysis-targeting chimeras (PROTACs®) and molecular glues, is both easy and hard: While degrader targets can be readily identified by global quantitative proteomics, the effects can be highly tissue-specific, as they depend not only on the main target but also on the simultaneous expression, activity, and localization of a ubiquitin ligase complex. Therefore, it is desirable to validate target degradation and search for potential off-targets across many different biological models ranging from cell culture and primary cells to tissues from animal models. Such experiments with large cohorts and often limited sample amounts require high throughput analytics with good sensitivity.

Here, we present a streamlined and largely automated bottom-up proteomics workflow quantifying up to 9,000 proteins at a throughput of 30 samples per day. As a proof-of-concept, we confirmed the (off-) targets of the clinical compounds Indisulam, Lenalidomide, and Pomalidomide in a human T-cell model. To narrow down the main targets and rule out secondary effects, we performed further experiments in dose-response, with a time course, and with pharmacological co-treatments to selectively inhibit proteasomal degradation or Cullin-RING ligases.

To demonstrate applicability for more complex biological models, we studied a bifunctional degrader in murine liver, spleen, and adipose tissue and in human peripheral blood mononuclear cells (PBMCs). Our data successfully confirmed target engagement in all four matrices including the sample-limited PBMCs and was key in the discovery of a previously unknown off-target. Furthermore, we characterized a PROTAC® in a patient-derived xenograft (PDX) model at four time points, each at four different doses. After 48 h of MS analysis time, we obtained global proteome data with time- and dose-resolution that helped us to validate target degradation and identify potential off-targets.

Taken together, we established a global degrader target identification method that can be universally applied to a range of relevant disease models and offers relatively high throughput und sensitivity. We anticipate that our method will accelerate drug discovery by providing a detailed picture of the target landscapes of degrader modalities, regardless whether they come from phenotypic screens or from rational drug design.