Antibiotic Activity and Characterization of BB-3497, a Novel Peptide Deformylase Inhibitor
Bibliographic record
Abstract
Peptide deformylase (PDF) is an essential bacterial metalloenzyme which deformylates the N-formylmethionine of newly synthesized polypeptides and as such represents a novel target for antibacterial chemotherapy. To identify novel PDF inhibitors, we screened a metalloenzyme inhibitor library and identified an N-formyl-hydroxylamine derivative, BB-3497, and a related natural hydroxamic acid antibiotic, actinonin, as potent and selective inhibitors of PDF. To elucidate the interactions that contribute to the binding affinity of these inhibitors, we determined the crystal structures of BB-3497 and actinonin bound to Escherichia coli PDF at resolutions of 2.1 and 1.75 A, respectively. In both complexes, the active-site metal atom was pentacoordinated by the side chains of Cys 90, His 132, and His 136 and the two oxygen atoms of N-formyl-hydroxylamine or hydroxamate. BB-3497 had activity against gram-positive bacteria, including methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus faecalis, and activity against some gram-negative bacteria. Time-kill analysis showed that the mode of action of BB-3497 was primarily bacteriostatic. The mechanism of resistance was via mutations within the formyltransferase gene, as previously described for actinonin. While actinonin and its derivatives have not been used clinically because of their poor pharmacokinetic properties, BB-3497 was shown to be orally bioavailable. A single oral dose of BB-3497 given 1 h after intraperitoneal injection of S. aureus Smith or methicillin-resistant S. aureus protected mice from infection with median effective doses of 8 and 14 mg/kg of body weight, respectively. These data validate PDF as a novel target for the design of a new generation of antibacterial agents.
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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".