Features of the Catalytic Domains and C Termini of the MAPK Signal-integrating Kinases Mnk1 and Mnk2 Determine Their Differing Activities and Regulatory Properties
Bibliographic record
Abstract
The MAPK signal-integrating kinases Mnk1 and Mnk2 are closely related but show marked differences in their basal activities and regulation. Both possess, within their C termini, motifs for binding to MAPKs, although these differ between Mnk1 and Mnk2. Mnk2 shows much higher activity in unstimulated cells than Mnk1, whose activity is greatly increased, e.g. by stimulation of the MEK/ERK pathway. Such increases are sensitive to blockade of that pathway, whereas the activation state of Mnk2 is relatively insensitive to inhibition of upstream signaling. Here we have studied the roles of features in their catalytic domains and C termini in determining their regulatory properties and basal activities. Mnk2 can bind to phosphorylated, active ERK, whereas Mnk1 cannot. Such binding apparently protects ERK against dephosphorylation and inactivation. The high basal activity of Mnk2 and its binding to (phospho)ERK requires features both of the catalytic domain and of the C terminus. For example, within the catalytic region an aspartate in Mnk2 plays a key role. Mutation to alanine inactivates Mnk2. In the C terminus, features within the MAPK-binding motif and to either side of it, including potential phosphorylation sites, affect MAPK binding and activity. The association of Mnks with the scaffold protein eukaryotic initiation factor 4G is negatively modulated by Mnk activity. These data indicate that multiple features determine the activities of the Mnks and thus impact on their ability to phosphorylate physiological substrates such as eukaryotic initiation factor 4E.
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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".