Distinct modulation of K<sub>v</sub>1.2 channel gating by wild type, but not open form, of syntaxin-1A
Bibliographic record
Abstract
SNARE proteins, syntaxin-1A (Syn-1A) and SNAP-25, inhibit delayed rectifier K(+) channels, K(v)1.1 and K(v)2.1, in secretory cells. We showed previously that the mutant open conformation of Syn-1A (Syn-1A L165A/E166A) inhibits K(v)2.1 channels more optimally than wild-type Syn-1A. In this report we examined whether Syn-1A in its wild-type and open conformations would exhibit similar differential actions on the gating of K(v)1.2, a major delayed rectifier K(+) channel in nonsecretory smooth muscle cells and some neuronal tissues. In coexpression and acute dialysis studies, wild-type Syn-1A inhibited K(v)1.2 current magnitude. Of interest, wild-type Syn-1A caused a right shift in the activation curves of K(v)1.2 without affecting its steady-state availability, an inhibition profile opposite to its effects on K(v)2.1 (steady-state availability reduction without changes in voltage dependence of activation). Also, although both wild-type and open-form Syn-1A bound equally well to K(v)1.2 in an expression system, open-form Syn-1A failed to reduce K(v)1.2 current magnitude or affect its gating. This is in contrast to the reported more potent effect of open-form Syn-1A on K(v)2.1 channels in secretory cells. This finding together with the absence of Munc18 and/or 13-1 in smooth muscles suggested that a change to an open conformation Syn-1A, normally facilitated by Munc18/13-1, is not required in nonsecretory smooth muscle cells. Taken together with previous reports, our results demonstrate the multiplicity of gating inhibition of different K(v) channels by Syn-1A and is compatible with versatility of Syn-1A modulation of repolarization in various secretory and nonsecretory (smooth muscle) cell types.
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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 | 0.001 |
| 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".