Processive ATP-driven Substrate Disassembly by the N-Ethylmaleimide-sensitive Factor (NSF) Molecular Machine
Bibliographic record
Abstract
SNARE proteins promote membrane fusion by forming a four-stranded parallel helical bundle that brings the membranes into close proximity. Post-fusion, the complex is disassembled by an AAA+ ATPase called N -ethylmaleimide-sensitive factor (NSF). We present evidence that NSF uses a processive unwinding mechanism to disassemble SNARE proteins. Using a real-time disassembly assay based on fluorescence dequenching, we correlate NSF-driven disassembly rates with the SNARE-activated ATPase activity of NSF. Neuronal SNAREs activate the ATPase rate of NSF by ∼26-fold. One SNARE complex takes an average of ∼5 s to disassemble in a process that consumes ∼50 ATP. Investigations of substrate requirements show that NSF is capable of disassembling a truncated SNARE substrate consisting of only the core SNARE domain, but not an unrelated four-stranded coiled-coil. NSF can also disassemble an engineered double-length SNARE complex, suggesting a processive unwinding mechanism. We further investigated processivity using single-turnover experiments, which show that SNAREs can be unwound in a single encounter with NSF. We propose a processive helicase-like mechanism for NSF in which ∼1 residue is unwound for every hydrolyzed ATP molecule. Background: NSF is an AAA+ protein that recycles the post-fusion SNARE complex during the membrane fusion cycle. Results: NSF disassembles the SNARE complex processively in vitro and consumes dozens of ATP molecules per SNARE. Conclusion: NSF is a processive motor that progressively unwinds the SNARE complex. Significance: The physical mechanism of this poorly understood machine is illuminated using new assays and new measurements of ATP coupling ratios and processivity.
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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) | 0.000 | 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".