Design and synthesis of constrained bicyclic molecules as candidate inhibitors of influenza A neuraminidase
Bibliographic record
Abstract
The rise of drug-resistant influenza A virus strains motivates the development of new antiviral drugs, with different structural motifs and substitution. Recently, we explored the use of a bicyclic (bicyclo[3.1.0]hexane) analogue of sialic acid that was designed to mimic the conformation adopted during enzymatic cleavage within the neuraminidase (NA; sialidase) active site. Given that our first series of compounds were at least four orders of magnitude less active than available drugs, we hypothesized that the new carbon skeleton did not elicit the same interactions as the cyclohexene frameworks used previously. Herein, we tried to address this critical point with the aid of molecular modeling and we proposed new structures with different functionalization, such as the introduction of free ammonium and guanidinium groups and ether side chains other than the 3-pentyl side chain, the characteristic side chain in Oseltamivir. A highly simplified synthetic route was developed, starting from the cyclopropanation of cyclopentenone and followed by an aziridination and further functionalization of the five-member ring. This allowed the efficient preparation of a small library of new bicyclic ligands that were characterized by enzyme inhibition assays against influenza A neuraminidases N1, its H274Y mutant, and N2. The results show that none of the new structural variants synthesized, including those containing guanidinium groups rather than free ammonium ions, displayed activity against influenza A neuraminidases at concentrations less than 2 mM. We conclude that the choice and positioning of functional groups on the bicyclo[3.1.0]hexyl system still need to be properly tuned for producing complementary interactions within the catalytic site.
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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".