Diversity-oriented synthesis of glycomimetics
Bibliographic record
Abstract
Glycomimetics are structural mimics of naturally occurring carbohydrates and represent important therapeutic leads in several disease treatments. However, the structural and stereochemical complexity inherent to glycomimetics often challenges medicinal chemistry efforts and is incompatible with diversity-oriented synthesis approaches. Here, we describe a one-pot proline-catalyzed aldehyde α-functionalization/aldol reaction that produces an array of stereochemically well-defined glycomimetic building blocks containing fluoro, chloro, bromo, trifluoromethylthio and azodicarboxylate functional groups. Using density functional theory calculations, we demonstrate both steric and electrostatic interactions play key diastereodiscriminating roles in the dynamic kinetic resolution. The utility of this simple process for generating large and diverse libraries of glycomimetics is demonstrated in the rapid production of iminosugars, nucleoside analogues, carbasugars and carbohydrates from common intermediates.
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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 | 0.001 |
| 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".