Conformational flexibility of the glycosidase NagZ allows it to bind structurally diverse inhibitors to suppress β‐lactam antibiotic resistance
Bibliographic record
Abstract
NagZ is an N-acetyl-β-d-glucosaminidase that participates in the peptidoglycan (PG) recycling pathway of Gram-negative bacteria by removing N-acetyl-glucosamine (GlcNAc) from PG fragments that have been excised from the cell wall during growth. The 1,6-anhydromuramoyl-peptide products generated by NagZ activate β-lactam resistance in many Gram-negative bacteria by inducing the expression of AmpC β-lactamase. Blocking NagZ activity can thereby suppress β-lactam antibiotic resistance in these bacteria. The NagZ active site is dynamic and it accommodates distortion of the glycan substrate during catalysis using a mobile catalytic loop that carries a histidine residue which serves as the active site general acid/base catalyst. Here, we show that flexibility of this catalytic loop also accommodates structural differences in small molecule inhibitors of NagZ, which could be exploited to improve inhibitor specificity. X-ray structures of NagZ bound to the potent yet non-selective N-acetyl-β-glucosaminidase inhibitor PUGNAc (O-(2-acetamido-2-deoxy-d-glucopyranosylidene) amino-N-phenylcarbamate), and two NagZ-selective inhibitors - EtBuPUG, a PUGNAc derivative bearing a 2-N-ethylbutyryl group, and MM-156, a 3-N-butyryl trihydroxyazepane, revealed that the phenylcarbamate moiety of PUGNAc and EtBuPUG completely displaces the catalytic loop from the NagZ active site to yield a catalytically incompetent form of the enzyme. In contrast, the catalytic loop was found positioned in the catalytically active conformation within the NagZ active site when bound to MM-156, which lacks the phenylcarbamate extension. Displacement of the catalytic loop by PUGNAc and its N-acyl derivative EtBuPUG alters the active site conformation of NagZ, which presents an additional strategy to improve the potency and specificity of NagZ inhibitors.
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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".