Molecular Mechanisms of Lysine Methylation
Bibliographic record
Abstract
SET domain lysine methyltransferases (KMTs) are S‐adenosylmethionine (AdoMet)‐dependent enzymes that catalyze the site‐specific methylation of lysine residues in histones, transcription factors, and other protein substrates. SET domain KMTs also display product specificity, which is defined as their ability to catalyze different degrees of methylation of the lysine‐epsilon amine group, thus imparting an additional hierarchy in methyllysine signaling. To understand the mechanism underlying product specificity, we have characterized two active site mutants of the monomethylase SET7/9 that alter its specificity to a dimethylase and a trimethylase, respectively. Structures of the SET7/9 mutants in complex with peptides bearing unmodified, mono‐, di‐, and trimethylated lysines reveal that water molecules within the active site function as place holders that linearly align the lysine epsilon‐amine group with the methyl group of AdoMet to promote methyltransfer. As the methylation state of the lysine substrate increases during successive reactions, the water molecules dissociate from the active site, thereby enlarging the lysine binding channel to accommodate the increasing bulk of the methylated epsilon‐amine group. Collectively, our findings illuminate the catalytic roles of active site water molecules in facilitating lysine multiple methylation by SET domain KMTs.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".