Glycosyl Cations versus Allylic Cations in Spontaneous and Enzymatic Hydrolysis
Bibliographic record
Abstract
Enzymatic prenyl and glycosyl transfer are seemingly unrelated reactions that yield molecules and protein modifications with disparate biological functions. However, both reactions employ diphosphate-activated donors and each proceed via cationic species: allylic cations and oxocarbenium ions, respectively. In this study, we explore the relationship between these processes by preparing valienyl ethers to serve as glycoside mimics that are capable of allylic rather than oxocarbenium cation stabilization. Rate constants for spontaneous hydrolysis of aryl glycosides and their analogous valienyl ethers were found to be almost identical, as were the corresponding activation enthalpies and entropies. This close similarity extended to the associated secondary kinetic isotope effects (KIEs), indicating very similar transition state stabilities and structures. Screening a library of over 100 β-glucosidases identified a number of enzymes that catalyze hydrolysis of these valienyl ethers with k cat values up to 20 s –1 . Detailed analysis of one such enzyme showed that ether hydrolysis occurs via the analogous mechanisms found for glycosides, and through a very similar transition state. This suggests that the generally lower rates of enzymatic cleavage of the cyclitol ethers reflects evolutionary specialization of these enzymes toward glycosides rather than inherent reactivity differences.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".