Inhibition of zipper-interacting protein kinase function in smooth muscle by a myosin light chain kinase pseudosubstrate peptide
Bibliographic record
Abstract
As a regulator of smooth muscle contractility, zipper-interacting protein kinase (ZIPK) appears to phosphorylate the regulatory myosin light chain (RLC20), directly or indirectly, at Ser19 and Thr18 in a Ca(2+)-independent manner. The calmodulin-binding and autoinhibitory domain of myosin light chain kinase (MLCK) shares similarity to a sequence found in ZIPK. This similarity in sequence prompted an investigation of the SM1 peptide, which is derived from the autoinhibitory region of MLCK, as a potential inhibitor of ZIPK. In vitro studies showed that SM1 is a competitive inhibitor of a constitutively active 32-kDa form of ZIPK with an apparent K(i) value of 3.4 microM. Experiments confirmed that the SM1 peptide is also active against full-length ZIPK. In addition, ZIPK autophosphorylation was reduced by SM1. ZIPK activity is independent of calmodulin; however, calmodulin suppressed the in vitro inhibitory potential of SM1, likely as a result of nonspecific binding of the peptide to calmodulin. Treatment of ileal smooth muscle with exogenous ZIPK was accompanied by an increase in RLC20 diphosphorylation, distinguishing between ZIPK [and integrin-linked kinase (ILK)] and MLCK actions. Administration of SM1 suppressed steady-state muscle tension developed by the addition of exogenous ZIPK to Triton-skinned rat ileal muscle strips with or without calmodulin depletion by trifluoperazine. The decrease in contractile force was associated with decreases in both RLC20 mono- and diphosphorylation. In summary, we present the SM1 peptide as a novel inhibitor of ZIPK. We also conclude that the SM1 peptide, which has no effect on ILK, can be used to distinguish between ZIPK and ILK effects in smooth muscle tissues.
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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".