Structural Comparison of Human Mammalian Ste20-Like Kinases
Bibliographic record
Abstract
BACKGROUND: The serine/threonine mammalian Ste-20 like kinases (MSTs) are key regulators of apoptosis, cellular proliferation as well as polarization. Deregulation of MSTs has been associated with disease progression in prostate and colorectal cancer. The four human MSTs are regulated differently by C-terminal regions flanking the catalytic domains. PRINCIPAL FINDINGS: We have determined the crystal structure of kinase domain of MST4 in complex with an ATP-mimetic inhibitor. This is the first structure of an inactive conformation of a member of the MST kinase family. Comparison with active structures of MST3 and MST1 revealed a dimeric association of MST4 suggesting an activation loop exchanged mechanism of MST4 auto-activation. Together with a homology model of MST2 we provide a comparative analysis of the kinase domains for all four members of the human MST family. SIGNIFICANCE: The comparative analysis identified new structural features in the MST ATP binding pocket and has also defined the mechanism for autophosphorylation. Both structural features may be further explored for inhibitors design. ENHANCED VERSION: This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1.
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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) | 0.004 | 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".