Mechanism of Action of Peptidoglycan <i>O</i>-Acetyltransferase B Involves a Ser-His-Asp Catalytic Triad
Bibliographic record
Abstract
The O-acetylation of the essential cell wall polymer peptidoglycan is essential in many bacteria for their integrity and survival, and it is catalyzed by peptidoglycan O-acetlytransferase B (PatB). Using PatB from Neisseria gonorrhoeae as the model, we have shown previously that the enzyme has specificity for polymeric muropeptides that possess tri- and tetrapeptide stems and that rates of reaction increase with increasing degrees of polymerization. Here, we present the catalytic mechanism of action of PatB, the first to be described for an O-acetyltransferase of any bacterial exopolysaccharide. The influence of pH on PatB activity was investigated, and pKa values of 6.4-6.45 and 6.25-6.35 for the enzyme-substrate complex (kcat vs pH) and the free enzyme (kcat·KM(-1) vs pH), respectively, were determined for the respective cosubstrates. The enzyme is partially inactivated by sulfonyl fluorides but not by EDTA, suggesting the participation of a serine residue in its catalytic mechanism. Alignment of the known and hypothetical PatB amino acid sequences identified Ser133, Asp302, and His305 as three invariant amino acid residues that could potentially serve as a catalytic triad. Replacement of Asp302 with Ala resulted in an enzyme with less than 20% residual activity, whereas activity was barely detectable with (His305 → Ala)PatB and (Ser133 → Ala)PatB was totally inactive. The reaction intermediate of the transferase reaction involving acetyl- and propionyl-acyl donors was trapped on both the wild-type and (Asp302 → Ala) enzymes and LC-MS/MS analysis of tryptic peptides identified Ser133 as the catalytic nucleophile. A transacetylase mechanism is proposed based on the mechanism of action of serine esterases.
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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) | 0.001 | 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) | 0.000 | 0.001 |
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".