Three αSNAP and 10 ATP Molecules Are Used in SNARE Complex Disassembly by N-ethylmaleimide-sensitive Factor (NSF)
Bibliographic record
Abstract
The fusion of intracellular membranes is driven by the formation of a highly stable four-helix bundle of SNARE proteins embedded in the vesicle and target membranes. N -Ethylmaleimide sensitive factor recycles SNAREs after fusion by binding to the SNARE complex through an adaptor protein, αSNAP, and using the energy of ATP hydrolysis to disassemble the complex. Although only a single molecule of αSNAP binds to a soluble form of the SNARE complex, we find that three molecules of αSNAP are used for SNARE complex disassembly. We describe an engineered αSNAP trimer that supports more efficient SNARE complex disassembly than monomeric αSNAP. Using the trimerized αSNAP, we find that N -ethylmaleimide-sensitive factor hydrolyzes 10 ATP molecules on average to disassemble a single SNARE complex.The ATPase NSF works with the adaptor protein αSNAP to disassemble SNARE protein complexes involved in membrane fusion. Results Kinetic assays demonstrate that three αSNAP and 10 ATP molecules are required to disassemble a SNARE complex. Conclusion The energy requirements and functional stoichiometry of αSNAP in SNARE complex disassembly are established. Significance The results suggest models of NSF action.
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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".