bioPROTACs as versatile modulators of intracellular therapeutic targets including proliferating cell nuclear antigen (PCNA)
Bibliographic record
Abstract
Targeted degradation approaches such as proteolysis targeting chimeras (PROTACs) offer new ways to address disease through tackling challenging targets and with greater potency, efficacy, and specificity over traditional approaches. However, identification of high-affinity ligands to serve as PROTAC starting points remains challenging. As a complementary approach, we describe a class of molecules termed biological PROTACs (bioPROTACs)-engineered intracellular proteins consisting of a target-binding domain directly fused to an E3 ubiquitin ligase. Using GFP-tagged proteins as model substrates, we show that there is considerable flexibility in both the choice of substrate binders (binding positions, scaffold-class) and the E3 ligases. We then identified a highly effective bioPROTAC against an oncology target, proliferating cell nuclear antigen (PCNA) to elicit rapid and robust PCNA degradation and associated effects on DNA synthesis and cell cycle progression. Overall, bioPROTACs are powerful tools for interrogating degradation approaches, target biology, and potentially for making therapeutic impacts.
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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".