Side Chain Assignments of Ile δ1 Methyl Groups in High Molecular Weight Proteins: an Application to a 46 ns Tumbling Molecule
Bibliographic record
Abstract
A sensitive 3D NMR pulse scheme, (H)C(CA)NH-COSY, is presented for the assignment of (13)C(delta)(1) Ile chemical shifts in large perdeuterated, methyl-protonated proteins. The nonlinearity of branched amino acids, such as Ile, significantly degrades the quality of TOCSY schemes which transfer magnetization from methyl carbons to the backbone (13)C(alpha) positions, and in applications to high molecular weight proteins (correlation times on the order of 40-50 ns), this compromises the sensitivity of spectra used for methyl assignment. The experiment presented utilizes COSY-based transfer steps and refocuses undesirable (13)C-(13)C scalar couplings that degrade the efficiency of TOCSY transfers. The (H)C(CA)NH-COSY scheme is tested on an (15)N,(13)C,(2)H-[Leu, Val, Ile (delta 1 only)]-methyl-protonated maltose binding protein (MBP)/beta-cyclodextrin complex at 5 degrees C (molecular tumbling time 46 +/- 2 ns), facilitating the assignment of (13)C(delta 1) chemical shifts for 18 of the 19 Ile residues for which backbone assignments were previously obtained. Both sensitivity and resolution of the resulting spectra are shown to be significantly better than those for a similar TOCSY-based approach.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".