Kinetic and Structural Analysis of Bisubstrate Inhibition of the <i>Salmonella enterica </i>Aminoglycoside 6‘-<i>N</i>-Acetyltransferase<sup>,</sup>
Bibliographic record
Abstract
Aminoglycosides are antibacterial compounds that act by binding to the A site of the small 30S bacterial ribosomal subunit and inhibiting protein translation. Clinical resistance to aminoglycosides is generally the result of the expression of enzymes that covalently modify the antibiotic, including phosphorylation, adenylylation, and acetylation. Bisubstrate analogs for the aminoglycoside N-acetyltransferases are nanomolar inhibitors of Enterococcus faecium AAC(6')-Ii. However, in the case of the Salmonella enterica aac(6')-Iy-encoded aminoglycoside N-acetyltransferase, we demonstrate that a series of bisubstrate analogs are only micromolar inhibitors. In contrast to studies with AAC(6')-Ii, the inhibition constants toward AAC(6')-Iy are essentially independent of both the identity of the aminoglycoside component of the bisubstrate and the number of carbon atoms that are used to link the CoA and aminoglycoside components. The patterns of inhibition suggest that the CoA portion of the bisubstrate analog can bind to the enzyme-aminoglycoside substrate complex and that the aminoglycoside portion can bind to the enzyme-CoA product complex. However, at the high concentrations of bisubstrate analog used in crystallization experiments, we could crystallize and solve the three-dimensional structure of the enzyme-bisubstrate complex. The structure reveals that both the CoA and aminoglycoside portions bind in essentially the same positions as those previously observed for the enzyme-CoA-ribostamycin complex, with only a modest adjustment to accommodate the "linker". These results are compared to previous studies of the interaction of similar bisubstrate analogs with other aminoglycoside N-acetyltransferases.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".