Phosphorylation of caldesmon by myosin light chain kinase increases its binding affinity for phosphorylated myosin filaments
Bibliographic record
Abstract
Phosphorylation of myosin by myosin light chain kinase (MLCK) is essential for smooth muscle contraction. In this study we show that caldesmon (CaD) is also phosphorylated in vitro by MLCK. The phosphorylation is calcium- and calmodulin (CaM)-dependent and requires a MLCK concentration close to that found in vivo. On average, approximately 2 mol P(i) per mol of CaD are incorporated at Thr-626 and Thr-693, with additional partial phosphorylation at Ser-658 and Ser-702. The phosphorylation rate for CaD is 20- to 50-fold slower than that for filamentous myosin; faster relative rates were obtained with CaD added to purified actomyosin or myosin preparations containing endogenous MLCK/CaM complex. Addition of CaM also augmented CaD phosphorylation. We further demonstrate that [³²P] labeled CaD binds much more readily to phosphorylated filamentous myosin than to unphosphorylated myosin. For actomyosin, CaD binding affinity doubles after myosin phosphorylation, without a significant change in binding stoichiometry (approx. one CaD per myosin molecule). Unphosphorylated CaD is ineffective in competing with the phosphorylated protein for the binding site(s) on myosin filaments. The ATPase activity of reconstituted actomyosin is inhibited by unphosphorylated CaD, and this inhibition was removed by CaD phosphorylation. Our results suggest that CaD phosphorylation plays a role in modifying actomyosin interaction in vivo, particularly during prolonged muscle activation.
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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 | 0.000 |
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".