Bipartite syntaxin 1A interactions mediate CaV2.2 calcium channel regulation
Bibliographic record
Abstract
Functional interactions between syntaxin 1A and Ca(V)2 calcium channels are critical for fast neurotransmitter release in the mammalian brain, and coexpression of syntaxin 1A with these channels not only regulates channel availability, but also promotes G-protein inhibition. Both the syntaxin 1A C-terminal H3 domain, and N-terminal Ha domain have been shown to interact with the Ca(V)2.2 channel synprint region, suggesting a bipartite model of functional interaction, however the molecular determinants of this interaction have not been closely investigated. We used in vitro binding assays to assess interactions of syntaxin 1A truncation mutants with Ca(V)2.2 synprint and Ca(V)2.3 II-III linker regions. We identified two distinct interactions between the Ca(V)2.2 synprint region and syntaxin 1A: the first between C-terminal H3c domain of syntaxin 1A and residues 822-872 of Ca(V)2.2; and the second between the N-terminal 10 residues of the syntaxin 1A Ha region and residues 718-771 of Ca(V)2.2. The N-terminal syntaxin 1A fragment also interacted with the Ca(V)2.3 II-III linker. We then performed whole cell patch clamp recordings to test the effects of a putative interacting syntaxin 1A N-terminus peptide with Ca(V)2.2 and Ca(V)2.3 channels in a recombinant expression system. A YFP-tagged peptide corresponding to the N-terminal 10 residues of the syntaxin 1A Ha domain was sufficient to allosterically inhibit both Ca(V)2.2 and Ca(V)2.3 channel function but had no effect on G-protein mediated inhibition. Our results support a model of bipartite functional interactions between syntaxin 1A and Ca(V)2.2 channels and add accuracy to the two putative interacting domains, consistent with previous studies. Furthermore, we highlight the syntaxin 1A N-terminus as the minimal determinant for functional regulation of Ca(V)2.2 and Ca(V)2.3 channels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".