Proton-Based Ultrafast Magic Angle Spinning Solid-State NMR Spectroscopy
Bibliographic record
Abstract
Conspectus Protons are vastly abundant in a wide range of exciting macromolecules and thus can be a powerful probe to investigate the structure and dynamics at atomic resolution using solid-state NMR (ssNMR) spectroscopy. Unfortunately, the high signal sensitivity, afforded by the high natural-abundance and high gyromagnetic ratio of protons, is greatly compromised by severe line broadening due to the very strong 1 H– 1 H dipolar couplings. As a result, protons are rarely used, in spite of the desperate need for enhancing the sensitivity of ssNMR to study a variety of systems that are not amenable for high resolution investigation using other techniques including X-ray crystallography, cryo-electron microscopy, and solution NMR spectroscopy. Thanks to the remarkable improvement in proton spectral resolution afforded by the significant advances in magic-angle-spinning (MAS) probe technology, 1 H ssNMR spectroscopy has recently attracted considerable attention in the structural and dynamics studies of various molecular systems. However, it still remains a challenge to obtain narrow 1 H spectral lines, especially from proteins, without resorting to deuteration. In this Account, we review recent proton-based ssNMR strategies that have been developed in our laboratory to further improve proton spectral resolution without resorting to chemical deuteration for the purposes of gaining atomistic-level insights into molecular structures of various crystalline solid systems, using small molecules and peptides as illustrative examples. The proton spectral resolution enhancement afforded by the ultrafast MAS frequencies up to 120 kHz is initially discussed, followed by a description of an ensemble of multidimensional NMR pulse sequences, all based on proton detection, that have been developed to obtain in-depth information from dipolar couplings and chemical shift anisotropy (CSA). Simple single channel multidimensional proton NMR experiments could be performed to probe the proximity of protons for structure determination using 1 H– 1 H dipolar couplings and to evaluate the changes in chemical environments as well as the relative orientation to the external magnetic field using proton CSA. Due to the boost in signal sensitivity enabled by proton detection under ultrafast MAS, by virtue of high proton natural abundance and gyromagnetic ratio, proton-detected multidimensional experiments involving low-γ nuclei can now be accomplished within a reasonable time, while the higher dimension also offers additional resolution enhancement. In addition, the application of proton-based ssNMR spectroscopy under ultrafast MAS in various challenging and crystalline systems is also presented. Finally, we briefly discuss the limitations and challenges pertaining to proton-based ssNMR spectroscopy under ultrafast MAS conditions, such as the presence of high-order dipolar couplings, friction-induced sample heating, and limited sample volume. Although there are still a number of challenges that must be circumvented by further developments in radio frequency pulse sequences, MAS probe technology and approaches to prepare NMR-friendly samples, proton-based ssNMR has already gained much popularity in various research domains, especially in proteins where uniform or site-selective deuteration can be relatively easily achieved. In addition, implementation of the recently developed fast data acquisition approaches would also enable further developments in the design and applications of proton-based ultrafast MAS multidimensional ssNMR techniques.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".