Natural Abundance ^13 C Kies on Glucoside Hydrolysis by NMR
Bibliographic record
Abstract
Kinetic isotope effect (KIE) study of enzymatic mechanisms has the potential for aiding the design of tight binding inhibitors, but is hampered by the need for isotopically labeled substrates. Recently, however, methods for measuring ¹³C and ²H KIEs at natural abundance by NMR spectroscopy have been developed, allowing KIEs to be measured at every NMR resolvable nucleus without isotopic substitution. Until this study, this technique had yet to be applied to an enzymatic system. KIEs provide information about transition states (TS) and since enzymes tightly bind structures resembling the TS, TS analogs can be used as powerful inhibitors and potential drugs. Glycosidases are enzymes that hydrolyze the acetals of carbohydrates. Inhibition of glycosidases has a large potential for therapeutic value. Methyl glucoside hydrolysis was used as a model substrate in the measurement of natural abundance KIEs. ¹³C KIEs were successfully measured on the acid and glucosidase catalyzed hydrolysis of methyl glucosides. The values of the primary ¹³C KIEs show that hydrolysis of β-methyl glucoside by β-glucosidase a more concerted ANON reaction. KIEs on the corresponding α-anomer suggest the opposite result, a ON*AN reaction. The experimental KIEs also matched well with calculated equilibrium isotope effects, lending support for the accuracy of the measurements.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".