Selective Characterization of Microsecond Motions in Proteins by NMR Relaxation
Bibliographic record
Abstract
The three-dimensional structures of macromolecules fluctuate over a wide range of time-scales. Separating the individual dynamic processes according to frequency is of importance in relating protein motions to biological function and stability. We present here a general NMR method for the specific characterization of microsecond motions at backbone positions in proteins even in the presence of other dynamics such as large-amplitude nanosecond motions and millisecond chemical exchange processes. The method is based on measurement of relaxation rates of four bilinear coherences and relies on the ability of strong continuous radio frequency fields to quench millisecond chemical exchange. The utility of the methodology is demonstrated and validated through two specific examples focusing on the thermo-stable proteins, ubiquitin and protein L, where it is found that small-amplitude microsecond dynamics are more pervasive than previously thought. Specifically, these motions are localized to alpha helices, loop regions, and regions along the rim of beta sheets in both of the proteins examined. A third example focuses on a 28 kDa ternary complex of the chaperone Chz1 and the histones H2A.Z/H2B, where it is established that pervasive microsecond motions are localized to a region of the chaperone that is important for stabilizing the complex. It is further shown that these motions can be well separated from extensive millisecond dynamics that are also present and that derive from exchange of Chz1 between bound and free states. The methodology is straightforward to implement, and data recorded at only a single static magnetic field are required.
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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 | 0.000 |
| 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 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".