The septin Sept5/CDCrel-1 competes with α-SNAP for binding to the SNARE complex
Bibliographic record
Abstract
SNARE (soluble N-ethylmaleimide-sensitive fusion protein attachment protein receptor) proteins are supposed to mediate the docking and/or fusion of the vesicle with the plasma membrane. However, it is not clearly understood how this process is regulated. In a search for potential SNARE regulators, we recently identified septin 5 (Sept5) as a novel SNARE interacting protein. Septins were first identified as filamentous proteins required for cytokinesis in yeast. Several septins have now been identified in mammals but little is known about their functions. We have previously shown that Sept5 is predominantly expressed in the brain, where it associates with vesicles and membranes through its interaction with the SNARE domain of syntaxin 1A. Furthermore, Sept5 appears to inhibit exocytosis, possibly by regulating vesicle targeting and/or fusion events. To gain insight into the role of Sept5, we have mapped the Sept5 domains important for syntaxin binding. We also investigated the ability of Sept5 to bind to syntaxin when in various protein complexes. Although Sept5 cannot bind an nSec1-syntaxin complex, it can bind syntaxin in a SNARE complex. This interaction is occluded by the binding of alpha-SNAP, suggesting that Sept5 may regulate the availability of SNARE proteins through its interaction with syntaxin and the 7 S complex.
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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".