Deoxygenated analogs of 2-deoxy-2,3-didehydro-N-acetyl neuraminic acid as inhibitors of human neuraminidase enzymes
Bibliographic record
Abstract
There is increasing interest in carbohydrate analogs for drug development, and the polar nature of these targets presents a challenge for medicinal chemistry. Multiple substrate hydroxy groups are typically required for enzyme active site recognition. Not all of these polar groups will have the same importance in recognition. A common strategy is to replace or remove these groups and compare the activity of the resulting analogs. If hydroxy groups are non-essential, or if their removal results in increased potency they may form the basis of improved inhibitors or substrates. In our studies of human neuraminidase enzymes (NEU), we have identified modifications at the C5 and C9 positions of the 2-deoxy-2,3-didehydro-N-acetyl neuraminic (DANA) scaffold that provide potent and selective inhibitors. In this study, we sought to test the requirements of each of the four human NEU isoenzymes for the presence of O4, O7, O8, or O9 hydroxy groups found in DANA. We synthesized the corresponding mono- (4, 7, 8, and 9) and di-deoxy (7,9; 7,8; and 8,9) analogs of DANA and tested their potency against human NEU. We found that 8-deoxy compounds increased potency against NEU2 and NEU3. Additionally, several di-deoxy analogs were tolerated by NEU1, NEU2, and NEU3. Finally, we generated known selective inhibitors of NEU3 and NEU4 and tested their 8-deoxy analogs. Combination of these features did not improve overall potency, suggesting deoxygenated analogs will require additional optimization.
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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) | 0.001 | 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".