DARPins as a novel tool to detect and degrade p73
Bibliographic record
Abstract
The concept of Targeted Protein Degradation (TPD) has been introduced as an attractive alternative to the development of classical inhibitors. TPD can extend the range of proteins that can be pharmacologically targeted beyond the classical targets for small molecule inhibitors, as a binding pocket is required but its occupancy does not need to lead to inhibition. The method is based on either small molecules that simultaneously bind to a protein of interest and to a cellular E3 ligase and bring them in close proximity (molecular glue) or a bi-functional molecule synthesized from the chemical linkage of a target protein-specific small molecule and one that binds to an E3 ligase (Proteolysis Targeting Chimeras (PROTAC)). The further extension of this approach to bioPROTACs, in which a small protein-based binding module is fused directly to an E3 ligase or an E3 ligase adaptor protein, makes virtually all proteins amenable to targeted degradation, as this method eliminates the requirement for binding pockets for small molecules. Designed Ankyrin Repeat Proteins (DARPins) represent a very attractive class of small protein-based binding modules that can be used for the development of bioPTOTACS. Here we describe the characterization of two DARPins generated against the oligomerization domain and the SAM domain of the transcription factor p73, a member of the p53 protein family. The DARPins can be used for (isoform-)selective pulldown experiments both in cell culture as well as primary tissue lysates. We also demonstrate that they can be used for staining in cell culture experiments. Fusing them to the speckle type POZ protein (SPOP), an adaptor protein for cullin-3 E3 ligase complexes, yields highly selective and effective degraders. We demonstrate that selective degradation of the ΔNp73α isoform reactivates p53.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".