Structural Basis for Substrate Preference of SMYD3, a SET Domain-containing Protein Lysine Methyltransferase
Bibliographic record
Abstract
SMYD3 is a SET domain-containing N-lysine methyltransferase associated with multiple cancers. Its reported substrates include histones (H3K4 and H4K5), vascular endothelial growth factor receptor 1 (VEGFR1 Lys(831)) and MAP3 kinase kinase (MAP3K2 Lys(260)). To reveal the structural basis for substrate preference and the catalytic mechanism of SMYD3, we have solved its co-crystal structures with VEGFR1 and MAP3K2 peptides. Our structural and biochemical analyses show that MAP3K2 serves as a robust substrate of SMYD3 because of the presence of a phenylalanine residue at the -2 position. A shallow hydrophobic pocket on SMYD3 accommodates the binding of the phenylalanine and promotes efficient catalytic activities of SMYD3. By contrast, SMYD3 displayed a weak activity toward a VEGFR1 peptide, and the location of the acceptor lysine in the folded kinase domain of VEGFR1 requires drastic conformational rearrangements for juxtaposition of the acceptor lysine with the enzymatic active site. Our results clearly revealed structural determinants for the substrate preference of SMYD3 and provided mechanistic insights into lysine methylation of MAP3K2. The knowledge should be useful for the development of SMYD3 inhibitors in the fight against MAP3K2 and Ras-driven cancer.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".