Coupling of tandem Smad ubiquitination regulatory factor (Smurf) WW domains modulates target specificity
Bibliographic record
Abstract
Smad ubiquitination regulatory factor 2 (Smurf2) is an E3 ubiquitin ligase that participates in degradation of TGF-β receptors and other targets. Smurf2 WW domains recognize PPXY (PY) motifs on ubiquitin ligase target proteins or on adapters, such as Smad7, that bind to E3 target proteins. We previously demonstrated that the isolated WW3 domain of Smurf2, but not the WW2 domain, can directly bind to a Smad7 PY motif. We show here that the WW2 augments this interaction by binding to the WW3 and making auxiliary contacts with the PY motif and a novel E/D-S/T-P motif, which is N-terminal to all Smad PY motifs. The WW2 likely enhances the selectivity of Smurf2 for the Smad proteins. NMR titrations confirm that Smad1 and Smad2 are bound by Smurf2 with the same coupled WW domain arrangement used to bind Smad7. The analogous WW domains in the short isoform of Smurf1 recognize the Smad7 PY peptide using the same coupled mechanism. However, a longer Smurf1 isoform, which has an additional 26 residues in the inter-WW domain linker, is only partially able to use the coupled WW domain binding mechanism. The longer linker results in a decrease in affinity for the Smad7 peptide. Interdomain coupling of WW domains enhances selectivity and enables the tuning of interactions by isoform switching.
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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) | 0.002 | 0.001 |
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".