Synthesis and Glycosidase Inhibition Studies of Novel Exoglycals Targeting GH3 Family Enzymes: Insights from Comparative Analysis with Macrolide Antibiotics
Bibliographic record
Abstract
ABSTRACT Glycosidases are key enzymes involved in carbohydrate metabolism. Members of the GH3 family have emerged as therapeutic targets due to their roles in natural product biosynthesis and disease. Transition‐state analogues represent a powerful strategy for glycosidase inhibition, and exoglycals (C‐glycosylidenes) have gained interest as conformational mimics of glycosidic bond hydrolysis. Herein, we report the synthesis of novel exoglycals bearing diverse substituents, including terminal alkynes and thymidyl residues, via a modified Julia‐olefination strategy from sugar‐derived lactones and substituted sulfones. Selected alkyne‐containing exoglycals were further functionalized through cycloaddition with azidothymidine. Inhibition studies against EryBI, a GH3 glycosyl hydrolase, were performed. Kinetic analysis revealed diverse inhibitory mechanisms among the exoglycals, displaying competitive inhibition, with K i values spanning micromolar to millimolar affinities. To contextualize the inhibitory potential of exoglycals, we evaluated three clinically relevant macrolide antibiotics‐erythromycin, clarithromycin, and azithromycin. Intriguingly, these macrolides exhibited competitive or uncompetitive inhibition, contrasting with the consistent competitive behavior of exoglycals. This comparative analysis highlights the scaffold‐dependent selectivity of GH3 inhibition. Our results demonstrate exoglycals as tunable scaffolds for glycosidase inhibition of GH3 glycosidases and provide mechanistic distinctions between carbohydrate mimics and macrolide antibiotics. These insights could guide the development of next‐generation glycosidase inhibitors with improved specificity.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".