The CDC42 effector protein MRCKβ autophosphorylates on Threonine 1108
Bibliographic record
Abstract
The CDC42 small GTPase is a major influence on actin-myosin cytoskeleton organization and dynamics, signalling via effector proteins including the Myotonic dystrophy related CDC42-binding protein kinases (MRCK) α and β. We previously identified Serine 1003 of MRCKα as a site of autophosphorylation, and showed that a phosphorylation-sensitive antibody raised against this site could be used as a surrogate indicator of kinase activity. In this study, a kinase-dead version of MRCKβ was established by mutation of the conserved Lysine 105 to Methionine (K105M), which was then used for mass spectrometry analysis to identify phosphorylation events that occurred in catalytically-competent MRCKβ but not in the kinase-dead form. A total of ten phosphorylations were identified on wild-type MRCKβ, of which the previously undescribed Threonine 1108 (Thr1108) was not found on kinase-dead MRCKβ K105M, consistent with this being due to autophosphorylation. Mutation of Thr1108 to non-phosphorylatable Alanine (T1108A) or phosphomimetic Glutamate (T1108E) did not affect the ability of MRCKβ to phosphorylate recombinant myosin light chain in vitro, or observably alter the subcellular localization of green fluorescent protein (GFP)-tagged MRCKβ expressed in MDA MB 231 human breast cancer cells. Although phosphorylation of Thr1108 did not appear to contribute to MRCKβ function or regulation, the identification of this phosphorylation does make it possible to characterize whether this site could be used as a surrogate biomarker of kinase activity and inhibitor efficacy as we previously demonstrated for Ser 1003 in MRCKα.
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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 | 0.001 |
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".