Solid-State NMR Provides Evidence for Small-Amplitude Slow Domain Motions in a Multispanning Transmembrane α-Helical Protein
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Proteins are dynamic entities and populate ensembles of conformations. Transitions between states within a conformational ensemble occur over a broad spectrum of amplitude and time scales, and are often related to biological function. Whereas solid-state NMR (SSNMR) spectroscopy has recently been used to characterize conformational ensembles of proteins in the microcrystalline states, its applications to membrane proteins remain limited. Here we use SSNMR to study conformational dynamics of a seven-helical transmembrane (TM) protein, Anabaena Sensory Rhodopsin (ASR) reconstituted in lipids. We report on site-specific measurements of the 15 N longitudinal R 1 and rotating frame R 1ρ relaxation rates at two fields of 600 and 800 MHz and at two temperatures of 7 and 30 °C. Quantitative analysis of the R 1 and R 1ρ values and of their field and temperature dependencies provides evidence of motions on at least two time scales. We modeled these motions as fast local motions and slower collective motions of TM helices and of structured loops, and used the simple model-free and extended model-free analyses to fit the data and estimate the amplitudes, time scales and activation energies. Faster picosecond (tens to hundreds of picoseconds) local motions occur throughout the protein and are dominant in the middle portions of the TM helices. In contrast, the amplitudes of the slower collective motions occurring on the nanosecond (tens to hundreds of nanoseconds) time scales, are smaller in the central parts of helices, but increase toward their cytoplasmic sides as well as in the interhelical loops. ASR interacts with a soluble transducer protein on its cytoplasmic surface, and its binding affinity is modulated by light. The larger amplitude of motions on the cytoplasmic side of the TM helices correlates with the ability of ASR to undergo large conformational changes in the process of binding/unbinding the transducer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".