Interpretation of biomolecular NMR spin relaxation parametersThis paper is one of a selection of papers published in this special issue entitled “Canadian Society of Biochemistry, Molecular & Cellular Biology 52nd Annual Meeting — Protein Folding: Principles and Diseases” and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
Biomolecular nuclear magnetic resonance (NMR) spin relaxation experiments provide exquisite information on the picosecond to nanosecond timescale motions of bond vectors. Spin-lattice (T1) and spin-spin (T2) relaxation times and the steady-state nuclear Overhauser effect (NOE) are the first set of parameters extracted from typical 15N or 13C NMR relaxation experiments. Therefore, verifying that T1, T2, and NOE are consistent with theoretical predictions is an important step before carrying out the more detailed model-free and reduced spectral density mapping analyses commonly employed. In this mini-review, we discuss the essential motional parameters used to describe biomolecular dynamics in the context of a variety of examples of folded and intrinsically disordered proteins and peptides in aqueous and membrane mimetic environments. Estimates of these parameters can be used as input for an online interface, introduced herein, allowing plotting of trends of T1, T2, and NOE with magnetic field strength. The plots may serve as a first-check to the spectroscopist preparing to embark on a detailed NMR relaxation analysis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".