Methyl TROSY: explanation and experimental verification
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Bibliographic record
Abstract
Abstract In TROSY experiments, relaxation interference effects are exploited to produce spectra with improved resolution and signal‐to‐noise. Such experiments cannot be explained using the standard product operator formalism, but must instead be analyzed at the level of individual density matrix elements. Herein we illustrate this point using an example from our recent work on a TROSY 1 H– 13 C correlation experiment for methyl groups in large proteins. Methyl groups are useful spectroscopic probes of protein structure and dynamics because they are found throughout the critical core region of a folded protein and their resonances are intense and well dispersed. Additionally, it is relatively easy to produce highly deuterated protein samples that are 1 H, 13 C labeled at selected methyl positions, facilitating studies of high molecular weight systems. Methyl groups are relaxed by a network of 1 H– 1 H and 1 H– 13 C dipolar interactions, and in the macromolecular limit the destructive interference of these interactions leads to unusually slow relaxation for certain density matrix elements. It is this slow relaxation that forms the basis for TROSY experiments. We present a detailed analysis of evolution and relaxation during HSQC and HMQC pulse schemes for the case of a 13 C 1 H 3 spin system attached to a macromolecule. We show that the HMQC sequence is already optimal with respect to the TROSY effect, offering a significant sensitivity enhancement over HSQC at any spectrometer field strength. The gain in sensitivity is established experimentally using samples of two large proteins, malate synthase G (81.4 kDa) and ClpP protease (305 kDa), both highly deuterated and selectively 1 H, 13 C‐labeled at isoleucine δ methyl positions. Copyright © 2003 John Wiley & Sons, Ltd.
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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 it