O-GlcNAc modification: why so intimately associated with phosphorylation?
Bibliographic record
Abstract
Post-translational modification of proteins at serine and threonine side chains by β-N-acetylglucosamine (O-GlcNAc) mediated by the enzyme β-N-acetylglucosamine transferase has been emerging as a fundamental regulatory mechanism encompassing a wide range of proteins involved in cell division, metabolism, transcription and cell signaling. Furthermore, an extensive interplay between O-GlcNAc modification and serine/threonine phosphorylation in a variety of proteins has been reported to exist. However, our understanding of the regulatory mechanisms involved in O-GlcNAc modification and its interplay with serine/threonine phosphorylation in proteins is still elusive. Recent success in the mapping of O-GlcNAc modification sites in proteins as a result of technological advancement in mass spectrometry have revealed two important clues which may be inherently connected to the regulation of O-GlcNAc modification and its interplay with phosphorylation in proteins. First, almost all O-GlcNAc modified proteins are known phospho proteins. Second, the prevalence of tyrosine phosphorylation among O-GlcNAc modified proteins is exceptionally higher (~68%) than its normal occurrence (~2%) alone. We hypothesize that phosphorylation may be a requisite for O-GlcNAc modification and tyrosine phosphorylation plays a role in the interplay between O-GlcNAc modification and serine/threonine phosphorylation in proteins. In other words, the interplay between O-GlcNAc modification and phosphorylation is not limited to serine/threonine phosphorylation but also includes tyrosine phosphorylation. Our hypothesis provides an opportunity to understand the underlying mechanism involved in O-GlcNAc modification and its interplay with serine/threonine phosphorylation in proteins. Furthermore, implication of our hypothesis extends to tyrosine kinase signaling.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".