An inventory of crosstalk between ubiquitination and other post-translational modifications in orchestrating cellular processes
Bibliographic record
Abstract
Ubiquitination is an important post-translational modification (PTM) that regulates a large spectrum of cellular processes in eukaryotes. Abnormalities in ubiquitin signaling underlie numerous human pathologies including cancer and neurodegeneration. Much progress has been made during the last three decades in understanding how ubiquitin ligases recognize their substrates and how ubiquitination is orchestrated. Several mechanisms of regulation have evolved to prevent promiscuity including the assembly of ubiquitin ligases in multi-protein complexes with dedicated subunits and specific post-translational modifications of these enzymes and their co-factors. Here, we outline another layer of complexity involving the coordinated access of E3 ligases to substrates. We provide an extensive inventory of ubiquitination crosstalk with multiple PTMs including SUMOylation, phosphorylation, methylation, acetylation, hydroxylation, prolyl isomerization, PARylation, and O-GlcNAcylation. We discuss molecular mechanisms by which PTMs orchestrate ubiquitination, thus increasing its specificity as well as its crosstalk with other signaling pathways to ensure cell homeostasis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".