Comparison of substrate specificity of the ubiquitin ligases Nedd4 and Nedd4‐2 using proteome arrays
Bibliographic record
Abstract
Target recognition by the ubiquitin system is mediated by E3 ubiquitin ligases. Nedd4 family members are E3 ligases comprised of a C2 domain, 2-4 WW domains that bind PY motifs (L/PPxY) and a ubiquitin ligase HECT domain. The nine Nedd4 family proteins in mammals include two close relatives: Nedd4 (Nedd4-1) and Nedd4L (Nedd4-2), but their global substrate recognition or differences in substrate specificity are unknown. We performed in vitro ubiquitylation and binding assays of human Nedd4-1 and Nedd4-2, and rat-Nedd4-1, using protein microarrays spotted with approximately 8200 human proteins. Top hits (substrates) for the ubiquitylation and binding assays mostly contain PY motifs. Although several substrates were recognized by both Nedd4-1 and Nedd4-2, others were specific to only one, with several Tyr kinases preferred by Nedd4-1 and some ion channels by Nedd4-2; this was subsequently validated in vivo. Accordingly, Nedd4-1 knockdown or knockout in cells led to sustained signalling via some of its substrate Tyr kinases (e.g. FGFR), suggesting Nedd4-1 suppresses their signalling. These results demonstrate the feasibility of identifying substrates and deciphering substrate specificity of mammalian E3 ligases.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".