<sup>51</sup>V magic angle spinning NMR spectroscopy and quantum chemical calculations in vanadium bio-inorganic systems: current perspective
Bibliographic record
Abstract
In recent years, 51V magic angle spinning (MAS) NMR spectroscopy has been widely used to characterize vanadium centers in biology, biomimetic complexes, and inorganic compounds of medicinal and industrial relevance. It has been demonstrated that 51V NMR parameters are sensitive probes of the coordination geometry and chemical environment of the metal center, beyond the first coordination sphere. To establish the relationships between NMR parameters and structure of the vanadium centers, over the past decade a large series of coordination complexes have been analyzed by MAS NMR spectroscopy. It has been demonstrated that the interpretation of the NMR parameters requires the use of theoretical methods, such as density functional (DFT) theory, whereby the experimental NMR observables are linked to the electronic and structural properties of a molecule. DFT calculations have been successfully employed to not only predict NMR parameters but to also yield valuable information regarding the structure and function of various vanadium compounds. In this report, we review the current state of the field, and present a survey of bioinorganic vanadium complexes as well as vanadium-dependent haloperoxidases analyzed using 51V MAS NMR spectroscopy and DFT calculations, to illustrate the rich information content available from such a combined 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".