Mechanism and Diversity of the Erythromycin Esterase Family of Enzymes
Bibliographic record
Abstract
Macrolide antibiotics such as azithromycin and erythromycin are mainstays of modern antibacterial chemotherapy, and like all antibiotics, they are vulnerable to resistance. One mechanism of macrolide resistance is via drug inactivation: enzymatic hydrolysis of the macrolactone ring catalyzed by erythromycin esterases, EreA and EreB. A genomic enzymology approach was taken to gain insight into the catalytic mechanisms and origins of Ere enzymes. Our analysis reveals that erythromycin esterases comprise a separate group in the hydrolase superfamily, which includes homologues of uncharacterized function found on the chromosome of Bacillus cereus, Bcr135 and Bcr136, whose three-dimensional structures have been determined. Biochemical characterization of Bcr136 confirms that it is an esterase that is, however, unable to inactivate macrolides. Using steady-state kinetics, homology-based structure modeling, site-directed mutagenesis, solvent isotope effect studies, pH, and inhibitor profiling performed in various combinations for EreA, EreB, and Bcr136 enzymes, we identified the active site and gained insight into some catalytic features of this novel enzyme superfamily. We rule out the possibility of a Ser/Thr nucleophile and show that one histidine, H46 (EreB numbering), is essential for catalytic function. This residue is proposed to serve as a general base in activation of a water molecule as the reaction nucleophile. Furthermore, we show that EreA, EreB, and Bcr136 are distinct, with only EreA inhibited by chelating agents and hypothesized to contain a noncatalytic metal. Detailed characterization of these esterases allows for a direct comparison of the resistance determinants, EreA and EreB, with their prototype, Bcr136, and for the discussion of their potential connections.
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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 | 0.001 | 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".