Solid-state NMR spectroscopy based atomistic view of a membrane protein unfolding pathway
Bibliographic record
Abstract
Membrane protein folding, structure, and function strongly depend on a cell membrane environment, yet detailed characterization of folding within a lipid bilayer is challenging. Studies of reversible unfolding yield valuable information on the energetics of folding and on the hierarchy of interactions contributing to protein stability. Here, we devise a methodology that combines hydrogen-deuterium (H/D) exchange and solid-state NMR (SSNMR) to follow membrane protein unfolding in lipid membranes at atomic resolution through detecting changes in the protein water-accessible surface, and concurrently monitoring the reversibility of unfolding. We obtain atomistic description of the reversible part of a thermally induced unfolding pathway of a seven-helical photoreceptor. The pathway is visualized through SSNMR-detected snapshots of H/D exchange patterns as a function of temperature, revealing the unfolding intermediate and its stabilizing factors. Our approach is transferable to other membrane proteins, and opens additional ways to characterize their unfolding and stabilizing interactions with atomic resolution.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".