Phosphorylation Impacts N-end Rule Degradation of the Proteolytically Activated Form of BMX Kinase
Bibliographic record
Abstract
Cellular signaling leading to the initiation of apoptosis typically results in the activation of caspases, which in turn leads to the proteolytic generation of protein fragments with new or altered cellular functions. Increasing numbers of reports are demonstrating that the activity of many of these proteolytically activated protein fragments can be attenuated by their selective degradation by the N-end rule pathway. Here we report the first evidence that selective degradation of a caspase product by the N-end rule pathway can be modulated by phosphorylation. We demonstrate that the pro-apoptotic fragment of the bone marrow kinase on chromosome X (BMX) generated by caspase cleavage in the prostate cancer-derived PC3 cell line is metabolically unstable in cells because its N-terminal tryptophan targets it for proteasomal degradation via the N-end rule pathway. In addition, we have demonstrated that phosphorylation of tyrosine 566 relatively inhibits degradation of the C-terminal BMX catalytic fragment, and this phosphorylation is crucial for its pro-apoptotic function. Overall, our results demonstrate that cleaved BMX is a novel N-end rule substrate, and its degradation exhibits a novel interplay between substrate phosphorylation and N-end rule degradation, revealing an increasing complex regulatory network of apoptotic proteolytic signaling cascades.
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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) | 0.001 | 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".