Regulation of Catalytic and Non-catalytic Functions of the Drosophila Ste20 Kinase Slik by Activation Segment Phosphorylation
Bibliographic record
Abstract
Protein kinases carry out important functions in cells both by phosphorylating substrates and by means of regulated non-catalytic activities. Such non-catalytic functions have been ascribed to many kinases, including some members of the Ste20 family. The Drosophila Ste20 kinase Slik phosphorylates and activates Moesin in developing epithelial tissues to promote epithelial tissue integrity. It also functions non-catalytically to promote epithelial cell proliferation and tissue growth. We carried out a structure-function analysis to determine how these two distinct activities of Slik are controlled. We find that the conserved C-terminal coiled-coil domain of Slik, which is necessary and sufficient for apical localization of the kinase in epithelial cells, is not required for Moesin phosphorylation but is critical for the growth-promoting function of Slik. Slik is auto- and trans-phosphorylated in vivo. Phosphorylation of at least two of three conserved sites in the activation segment is required for both efficient catalytic activity and non-catalytic signaling. Slik function is thus dependent upon proper localization of the kinase via the C-terminal coiled-coil domain and activation via activation segment phosphorylation, which enhances both phosphorylation of substrates like Moesin and engagement of effectors of its non-catalytic growth-promoting activity.
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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".