Inverse H‐C <i>ex situ</i> HRMAS NMR experiments for solid‐phase peptide synthesis
Bibliographic record
Abstract
The growing importance of solid-phase peptide synthesis (SPPS) has necessitated the development of spectroscopic experiments that can be used to obtain structural and conformational information on resin-bound peptides. Despite the utility of two-dimensional high-resolution magic angle spinning (HRMAS) NMR experiments that provide homonuclear shift correlations, experiments that provide heteronuclear shift correlations are necessary for complex conformational and structural elucidatory problems. Here we report the optimization and implementation of non-gradient inverse NMR experiments for acquiring the 1H-13C shift correlations of resin-bound peptides. The use of non-gradient experiments is advantageous as many magic angle spinning (MAS) probes do not possess gradient coils. An HRMAS BIRD-HMQC experiment with a reduced 1JCH constant has proven very suitable for obtaining one-bond correlations. Long-range correlations can be interpolated by using a non-gradient HRMAS CT-HMBC-1 experiment where the resulting data is processed with forward linear prediction. It has been shown that removing the effects of 1H-1H J-modulation is crucial in order to view cross peaks that correspond to long-range correlations. Additionally, both experiments prove extremely useful over routine one-dimensional 13C HRMAS experiments for extracting carbon chemical shift data. The non-gradient HRMAS BIRD-HMQC and CT-HMBC-1 experiments can be used to assist in conformational analysis and to identify and deconvolute situations where accidental equivalence and seemingly correlated isochronous signals arise.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".