Dipolar Chemical Shift Correlation Spectroscopy for Homonuclear Carbon Distance Measurements in Proteins in the Solid State: Application to Structure Determination and Refinement
Bibliographic record
Abstract
High-resolution solid-state NMR spectroscopy has become a promising tool for protein structure determination. Here, we describe a new dipolar-chemical shift correlation experiment for the measurement of homonuclear 13C-13C distances in uniformly 13C,15N-labeled proteins and demonstrate its suitability for protein structure determination and refinement. The experiments were carried out on the beta1 immunoglobulin binding domain of protein G (GB1). Both intraresidue and interresidue distances between carbonyl atoms and atoms in the aliphatic side chains were collected using a three-dimensional chemical shift correlation spectroscopy experiment that uses homogeneously broadened rotational resonance recoupling for carbon mixing. A steady-state approximation for the polarization transfer function was employed in data analysis, and a total of 100 intramolecular distances were determined, all in the range 2.5-5.5 A. An additional 41 dipolar contacts were detected, but the corresponding distances could not be accurately quantified. Additional distance and torsional restraints were derived from the proton-driven spin diffusion measurements and from the chemical shift analysis, respectively. Using all these restraints, it was possible to refine the structure of GB1 to a root-mean square deviation of 0.8 A. The approach is of general applicability for peptides and small proteins and can be easily incorporated into a structure determination and refinement protocol.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".