Hit-to-Lead Optimization of Acetazolamide-Based Bacterial Carbonic Anhydrase Inhibitors with Efficacy In Vivo for Treatment of Vancomycin-Resistant Enterococci Septicemia
Bibliographic record
Abstract
Abstract As one of the leading causes of hospital-acquired infections reported by the National Healthcare Safety Network, vancomycin-resistant enterococci (VRE) continue to afflict patients in healthcare facilities, with limited FDA-approved drugs available for treating systemic infections. Our group previously showed the 1,3,4-thiadiazole acetazolamide human carbonic anhydrase inhibitor scaffold can be repositioned with potent in vitro efficacy against enterococcal pathogens. However, only acetazolamide has been explored for in vivo efficacy in murine septicemia models. Herein, we report a hit-to-lead account in which we expand the structure–activity relationship for the 1,3,4-thiadiazole scaffold, identified lead candidates with favorable in vitro ADME profiles, and advanced a promising lead analog forward into in vivo pharmacokinetic studies. Ultimately, we demonstrated efficacy in a murine septicemic peritonitis infection model after oral dosing. Overall, we demonstrate a successful example of an acetazolamide-based lead compound with in vivo therapeutic potential for the treatment of septicemic vancomycin-resistant VRE infection.
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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) | 0.001 | 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) | 0.002 | 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".