The-N-End Rule: The Beginning Determines the End
Bibliographic record
Abstract
In eukaryotic cells, regulated protein degradation of intracellular proteins is mediated largely by the ubiquitin proteasome system (UPS). UPS-mediated protein degradation regulates virtually all crucial aspects of cellular physiology, such as cell proliferation, cell division, cell differentiation, and cell death. Concomitantly, the deregulation by the UPS contributes to human disorders including cancer. Cellular regulation by UPS- mediated protein degradation is a highly specific and selective process that depends on time (e.g. cell cycle) and location (nucleus, mitochondria or endoplasmic reticulum). An ongoing challenge in the protein degradation field is identification of degradation signals for specific proteins that trigger their degradation by the proteasome. More than 25 years ago, the first degradation signal was discovered and defined as destabilizing N-terminal amino-acid residue (or N-degron) of protein substrates. The discovery and subsequent detailed analysis of N-degrons gave rise to the so called N-end rule, which states that the half-life time of a protein is determined by the identity of its N-terminal amino-acid residue. The N-end rule pathway recognizes proteins containing N-terminal destabilizing residues and mediates their polyubiquitination and subsequent degradation in the proteasome. Recent investigations have revealed a role for N-terminal acetylation on the recognition of N-degrons by the N-end rule pathway. Here we summarize these recent findings and highlight the impact on our understanding of the N-end rule pathway with respect to cellular physiology.
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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 | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".