Inhibition of SCF ubiquitin ligases by engineered ubiquitin variants that target the Cul1 binding site on the Skp1–F-box interface
Bibliographic record
Abstract
Skp1-Cul1-F-box (SCF) E3 ligases play key roles in multiple cellular processes through ubiquitination and subsequent degradation of substrate proteins. Although Skp1 and Cul1 are invariant components of all SCF complexes, the 69 different human F-box proteins are variable substrate binding modules that determine specificity. SCF E3 ligases are activated in many cancers and inhibitors could have therapeutic potential. Here, we used phage display to develop specific ubiquitin-based inhibitors against two F-box proteins, Fbw7 and Fbw11. Unexpectedly, the ubiquitin variants bind at the interface of Skp1 and F-box proteins and inhibit ligase activity by preventing Cul1 binding to the same surface. Using structure-based design and phage display, we modified the initial inhibitors to generate broad-spectrum inhibitors that targeted many SCF ligases, or conversely, a highly specific inhibitor that discriminated between even the close homologs Fbw11 and Fbw1. We propose that most F-box proteins can be targeted by this approach for basic research and for potential cancer therapies.
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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 | 0.000 |
| 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 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".