Mps1 Activation Loop Autophosphorylation Enhances Kinase Activity
Bibliographic record
Abstract
The Mps1 protein kinase is required for proper assembly of the mitotic spindle, checkpoint signaling, and several other aspects of cell growth and differentiation. Mps1 regulation is mediated by cell cycle-dependent changes in transcription and protein level. There is also a strong correlation between hyperphosphorylated mitotic forms of Mps1 and increased kinase activity. We investigated the role that autophosphorylation plays in regulating human Mps1 (hMps1) protein kinase activity. Here we report that hyperphosphorylated hMps1 forms are not the only active forms of the kinase. However, autophosphorylation of hMps1 within the activation loop is required for full activity in vitro. Mass spectrometry analysis of de novo synthesized enzyme in Escherichia coli identified autophosphorylation sites at residues Thr(675), Thr(676), and Thr(686), but phosphatase-treated and reactivated enzyme was only phosphorylated on Thr(676). Mutation of Thr(676) in hMps1 or the corresponding Thr(591) residue within yeast Mps1 reduces kinase activity in vitro. We find that overexpression of an hMps1-T676A mutation inhibits centrosome duplication in RPE1 cells. Likewise, yeast cells harboring mps1-T591A as the sole MPS1 allele are not viable. Our data strongly support the conclusion that site-specific Mps1 autophosphorylation within the activation loop is required for full activity in vitro and function in vivo.
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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) | 0.002 | 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".