Conformational Dynamics of a Seven Transmembrane Helical Protein Anabaena Sensory Rhodopsin Probed by Solid-State NMR
Bibliographic record
Abstract
The ability to detect and characterize molecular motions represents one of the unique strengths of nuclear magnetic resonance (NMR) spectroscopy. In this study, we report solid-state NMR site-specific measurements of the dipolar order parameters and (15)N rotating frame spin-lattice (R1ρ) relaxation rates in a seven transmembrane helical protein Anabaena Sensory Rhodopsin reconstituted in lipids. The magnitudes of the observed order parameters indicate that both the well-defined transmembrane regions and the less structured intramembrane loops undergo restricted submicrosecond time scale motions. In contrast, the R1ρ rates, which were measured under fast magic angle spinning conditions, vary by an order of magnitude between the TM and exposed regions and suggest the presence of intermediate time scale motions. Using a simple model, which assumes a single exponential autocorrelation function, we estimated the time scales of dominant stochastic motions to be on the order of low tens of nanoseconds for most residues within the TM helices and tens to hundreds of nanoseconds for the extracellular B-C and F-G loops. These relatively slow time scales could be attributed to collective anisotropic motions. We used the 3D Gaussian axial fluctuations model to estimate amplitudes, directions, and time scales of overall motions for helices and the extracellular B-C and F-G loops. Within this model, the TM helices A,B,C,D,E,F undergo rigid body motions on a time scale of tens of nanoseconds, while the time scale for the seventh helix G approaches 100 ns. Similar time scales of roughly 100-200 ns are estimated for the B-C and F-G loops.
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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".