Exploring Phosphorylation-independent Pathway of STAT5 Activation for Development of Small Molecule Inhibitors of STAT5
Bibliographic record
Abstract
STAT5B is critical in the molecular pathogenesis of multiple blood cancers. The activation of STAT5B involves cytokine stimulation of a cell surface receptor. The intracellular receptor tail recruits a tyrosine kinase, which phosphorylates a tyrosine residue that is C-terminal to the SH2 domain of STAT5B followed by dimerization of STAT5B, and subsequent translocation to the nucleus to regulate gene expression. Currently, several therapeutic strategies are designed around inhibiting STAT5B phosphorylation, thereby preventing dimerization and downstream activation. However, recent studies have suggested a phosphorylation-independent mode of dimerization for STATs. Here we have examined the paradigm of phosphorylation-independent STAT5B dimerization. These studies suggest that in-vitro STAT5B dimerization is cysteine-mediated. We examined phosphorylation-dependent dimerization of STAT5B and utilized this to develop biophysical assays for screening differences in inhibitor binding. Finally, we examined the structural changes in the most frequently occurring disease-causing missense mutation, STAT5BN642H, which promotes phosphatase resistance and therefore enhances dimer lifetime.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".