Rapid Assembly of a Library of Lipophilic Iminosugars via the Thiol–Ene Reaction Yields Promising Pharmacological Chaperones for the Treatment of Gaucher Disease
Bibliographic record
Abstract
A highly divergent route to lipophilic iminosugars that utilizes the thiol-ene reaction was developed to enable the rapid synthesis of a collection of 16 dideoxyiminoxylitols bearing various different lipophilic substituents. Enzyme kinetic analyses revealed that a number of these products are potent, low-nanomolar inhibitors of human glucocerebrosidase that stabilize the enzyme to thermal denaturation by up to 20 K. Cell based assays conducted on Gaucher disease patient derived fibroblasts demonstrated that administration of the compounds can increase lysosomal glucocerebrosidase activity levels by therapeutically relevant amounts, as much as 3.2-fold in cells homozygous for the p.N370S mutation and 1.4-fold in cells homozygous for the p.L444P mutation. Several compounds elicited this increase in enzyme activity over a relatively wide dosage range. The data assembled here illustrate how the lipophilic moiety common to many glucocerebrosidase inhibitors might be used to optimize a lead compound's ability to chaperone the protein in cellulo. The flexibility of this synthetic strategy makes it an attractive approach to the rapid optimization of glycosidase inhibitor potency and pharmacokinetic behavior.
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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 | 0.000 | 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) | 0.001 | 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".