The structural influence of the oncogenic driver mutation N642H in the STAT5B SH2 domain
Bibliographic record
Abstract
Abstract The point mutation N642H of the signal transducer and activator of transcription 5B (STAT5B) protein is associated with aggressive and drug-resistant forms of leukemia. This mutation is thought to promote cancer due to hyperactivation of STAT5B caused by increased stability of the active, parallel dimer state. However, the molecular mechanism leading to this stabilization is not well understood as there is currently no structure of the parallel dimer. To investigate the mutation’s mechanism of action, we conducted extensive all-atom molecular dynamics simula-tions of multiple oligomeric forms of both STAT5B and STAT5B N 642 H , including a model for the parallel dimer. The N642H mutation directly affects the hydrogen bonding network within the phosphotyrosine (pY)-binding pocket of the parallel dimer, enhancing the pY-binding in-teraction. The simulations indicate that apo STAT5B is highly flexible, exploring a diverse conformational space. In contrast, apo STAT5B N 642 H accesses two distinct conformational states, one of which resembles the conformation of the parallel dimer. The simulation predic-tions of the effects of the mutation on structure and dynamics are supported by the results of hydrogen-deuterium exchange (HDX) mass spectrometry measurements carried out on STAT5B and STAT5B N 642 H in which a phosphopeptide was used to mimic the effects of parallel dimer-ization on the SH2 domain. The molecular-level information uncovered in this work contributes to our understanding of STAT5B hyperactivation by the N642H mutation and could help pave the way for novel therapeutic strategies targeting this mutation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".