Rational Design of Broad Spectrum Antibacterial Activity Based on a Clinically Relevant Enoyl-Acyl Carrier Protein (ACP) Reductase Inhibitor
Bibliographic record
Abstract
Determining the molecular basis for target selectivity is of particular importance in drug discovery. The ideal antibiotic should be active against a broad spectrum of pathogenic organisms with a minimal effect on human targets. CG400549, a Staphylococcus-specific 2-pyridone compound that inhibits the enoyl-acyl carrier protein reductase (FabI), has recently been shown to possess human efficacy for the treatment of methicillin-resistant Staphylococcus aureus infections, which constitute a serious threat to human health. In this study, we solved the structures of three different FabI homologues in complex with several pyridone inhibitors, including CG400549. Based on these structures, we rationalize the 65-fold reduced affinity of CG400549 toward Escherichia coli versus S. aureus FabI and implement concepts to improve the spectrum of antibacterial activity. The identification of different conformational states along the reaction coordinate of the enzymatic hydride transfer provides an elegant visual depiction of the relationship between catalysis and inhibition, which facilitates rational inhibitor design. Ultimately, we developed the novel 4-pyridone-based FabI inhibitor PT166 that retained favorable pharmacokinetics and efficacy in a mouse model of S. aureus infection with extended activity against Gram-negative and mycobacterial organisms.
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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".