Distinctive Binding of Avibactam to Penicillin-Binding Proteins of Gram-Negative and Gram-Positive Bacteria
Bibliographic record
Abstract
Avibactam is a novel non-β-lactam β-lactamase inhibitor that covalently acylates a variety of β-lactamases, causing inhibition. Although avibactam presents limited antibacterial activity, its acylation ability toward bacterial penicillin-binding proteins (PBPs) was investigated. Staphylococcus aureus was of particular interest due to the reported β-lactamase activity of PBP4. The binding of avibactam to PBPs was measured by adding increasing concentrations to membrane preparations of a variety of Gram-positive and Gram-negative bacteria prior to addition of the fluorescent reagent Bocillin FL. Relative binding (measured here as the 50% inhibitory concentration [IC50]) to PBPs was estimated by quantification of fluorescence after gel electrophoresis. Avibactam was found to selectively bind to some PBPs. In Escherichia coli, Pseudomonas aeruginosa, Haemophilus influenzae, and S. aureus, avibactam primarily bound to PBP2, with IC50s of 0.92, 1.1, 3.0, and 51 μg/ml, respectively, whereas binding to PBP3 was observed in Streptococcus pneumoniae (IC50, 8.1 μg/ml). Interestingly, avibactam was able to significantly enhance labeling of S. aureus PBP4 by Bocillin FL. In PBP competition assays with S. aureus, where avibactam was used at a fixed concentration in combination with varied amounts of ceftazidime, the apparent IC50 of ceftazidime was found to be very similar to that determined for ceftazidime when used alone. In conclusion, avibactam is able to covalently bind to some bacterial PBPs. Identification of those PBP targets may allow the development of new diazabicyclooctane derivatives with improved affinity for PBPs or new combination therapies that act on multiple PBP targets.
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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 | 0.001 |
| 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 | 0.001 | 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".