Targeted Degradation of 53BP1 Using Ubiquitin Variant Induced Proximity
Bibliographic record
Abstract
In recent years, researchers have leveraged the ubiquitin-proteasome system (UPS) to induce selective degradation of proteins by E3 ubiquitin ligases, which has great potential as novel therapeutics for human diseases, including cancer and neurodegenerative disorders. However, despite extensive efforts, only a handful of ~600 human E3 ligases were utilized, and numerous protein-protein interaction surfaces on E3 ligases were not explored. To tackle these problems, we leveraged a structure-based protein engineering technology to develop a multi-domain fusion protein bringing functional E3 ligases to the proximity of a target protein to trigger its proteasomal degradation, which we termed Ubiquitin Variant Induced Proximity (UbVIP). We first generated non-inhibitory synthetic UbV binders for a selected group of human E3 ligases. With these UbVs employed as E3 ligase engagers, we designed a library of UbVIPs targeting a DNA damage response protein 53BP1. We observed that two UbVIPs recruiting RFWD3 and NEDD4L could effectively induce proteasome degradation of 53BP1 in human cell lines. This provides a proof-of-principle that UbVs can act as a means of targeted degradation for nucleus-localized proteins. Our work demonstrated that UbV technology is suitable to develop protein-based molecules for targeted degradation and can help identify novel E3 ligases for future therapeutic development.
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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".