C-Glycosides and Aza-C-Glycosides as Potential Glycosidase and Glycosyltransferase Inhibitors
Bibliographic record
Abstract
Glycosylation as one of most important post-translational modification of gene products is often critical to specific cellular biological functions. Since elevated glycoprocessing enzyme activities have been implicated in the development of various diseases including cancer metastasis, glycosidases and glycosyltransferases are considered as therapeutic targets. Azasugars, the first generation of enzyme inhibitors, have been extensively investigated and two azasugar-based drugs (Miglitol and Miglustat) have been approved. Aza-C-glycosides, molecules with an azasugar core and various C-aglycons attached at the pseudo anomeric center, have the potential to become the second-generation inhibitors with improved specificity and membrane permeability. In this review, C-glycosides, aza-C-glycosides, and aza-C-disaccharides are introduced as glycoprocessing enzyme inhibitors. The synthetic approaches toward those molecules are described based on the key reactions, which include reductive amination, nucleophilic ring opening of epoxides, nucleophilic addition to imines (C=N), and hetero-Michael additions. Aza-C-glycoside-based libraries are also described for the discovery of promising second-generation inhibitors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".