Induced ubiquitination of the partially disordered Estrogen Receptor alpha protein via a 14-3-3-directed molecular glue-based PROTAC design
Bibliographic record
Abstract
Abstract Proteins lacking defined ligandable pockets remain challenging drug targets. Here, we develop a molecular glue-based PROTAC ( MG PROTACs) approach that chemically conjugates a molecular glue stabilizer to a VHL-recruiting ligand to capture and ubiquitinate the 14-3-3/Estrogen Receptor α (ERα) complex. Our designed MG PROTACs engage a composite interface between 14-3-3 and the disordered F-domain of ERα, promoting cooperative complex formation and target ubiquitination. Biophysical characterization revealed distinct linker-dependent cooperativities across the MG PROTAC series, which influenced both cellular permeability and ubiquitination efficiency. Cryo-EM of the most cooperative MG PROTAC uncovers de novo VHL–14-3-3ζ contacts, while molecular dynamics simulations rationalize the stabilizing interactions underlying cooperativity. Strikingly, fine-tuning linker design enables selective ubiquitination of distinct complex subunits. These findings establish a structural and mechanistic framework for integrating molecular glue and PROTAC principles, expanding the scope of drug discovery to previously intractable protein complexes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".