SET7/9 exhibits sigmoidal kinetics on nucleosomes, hyperbolic kinetics on histones by an ordered sequential mechanism, and methylates lysine and arginine
Bibliographic record
Abstract
SET7/9 (SETD7) is a SET domain protein lysine methyltransferase (PKMT). We characterized its activity using a mass spectrometry (MS) assay, showing that it follows an ordered sequential enzyme kinetic mechanism where SAM is the first substrate to bind, followed by histone H3, and mono-methylated histone H3 is the first product to dissociate, followed by SAH. Full-length histones H2A, H2B, and H4 are also substrates for SET7/9. We found that SET7/9 methylates nucleosome core particles (NCP), histone H2BK120 ubiquitinated nucleosome core particles (Ub-NCP) as well as histone octamers, exhibiting sigmoidal kinetics, and suggesting an allosteric interaction that was not observed with free histones, which follow hyperbolic (Michaelis-Menten) kinetics. Using low (25 nM) SET7/9, we only detect monomethyl-lysine with all substrates except Ub-NCP, which produces mono- and di-methyllysine at equal rates. Proteomic analysis shows that SET7/9 catalyzes multiple sites and types of, methylation on histones, depending on if they are free histones, or within an octamer. Free histone H3 is methylated at multiple N-terminal sites (including H3K4) that are not methylated in the octamer. Some C-terminal methylation sites were discovered that can also be ubiquitinated including H2BK120. Since lysine methylation and ubiquitination are mutually exclusive such methylation by SET7/9 may serve to prevent ubiquitination. At high enzyme and substrate concentrations and extended incubation times, we show that SET7/9 can catalyze the formation of dimethyl- and trimethyllysine on H2B, H3 and histone octamers and, most remarkably, the formation of monomethyl- and dimethylarginine on histone H3 and within octamers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".