An Improved <sup>15</sup>N Relaxation Dispersion Experiment for the Measurement of Millisecond Time-Scale Dynamics in Proteins
Bibliographic record
Abstract
A new (15)N constant-time relaxation dispersion pulse scheme for the quantification of millisecond time-scale exchange dynamics in proteins is presented. The experiment differs from previously developed sequences in that it includes (1)H continuous-wave decoupling during the (15)N Carr-Purcell-Meiboom-Gill (CPMG) pulse train that significantly improves the relaxation properties of (15)N magnetization, leading to sensitivity gains in experiments. Moreover, it is shown that inclusion of an additional (15)N 180 degrees refocusing pulse (phase cycled +/- x) in the center of the CPMG pulse train, consisting of 1(5)N 180 degrees (y) pulses, provides compensation for pulse imperfections beyond the normal CPMG scheme. Relative to existing relaxation-compensated constant-time relaxation dispersion pulse schemes, nu(CPMG) values that are only half as large can be employed, offering increased sensitivity to slow time-scale exchange processes. The robustness of the methodology is illustrated with applications involving a pair of proteins: an SH3 domain that does not show millisecond time-scale exchange and an FF domain with significant chemical exchange contributions.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".