Analysis of Kinetic Isotope Effects in Enzymatic Carbon–Hydrogen Cleavage Reactions
Bibliographic record
Abstract
The instanton approach, as previously applied to proton tunneling in molecular systems, is adapted to carbon-hydrogen bond cleavage catalyzed by enzymes. To compensate for the complexity of enzymatic reactions, simplifications are introduced based on the observation in numerous X-ray measurements that enzymes tend to form compact structures, which is assumed to have led toward optimization of specific parameters that govern the tunneling rate in the instanton formalism. On this basis, semiempirical equations are derived that link observed kinetic data directly to these parameters. These equations provide an analytical relation between the kinetic isotope effect and its temperature dependence for each hydrogen isotope, from which mechanistic and structural information can be extracted, including the nature of the hydrogen acceptor, the magnitude of the hydrogen transfer distance, the presence of endothermicity, and the contribution and frequency of skeletal vibrations that assist the tunneling. The method is used to analyze kinetic data reported for eight enzymatic CH-cleavage reactions; the enzymes or models thereof studied include methylmalonyl-coenzyme A mutase (coenzyme B(12)), galactose oxidase, lipoxygenase-1 with six mutants, methylamine dehydrogenase, an oxoiron(IV)porphyrin radical cation, phenylalanine hydroxylase, a bis(μ-oxo)dicopper complex, and rice α-oxygenase.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".