"Structural characterization of aminoglycoside modifying enzyme ANT(2"")-Ia"
Bibliographic record
Abstract
Aminoglycosides are a class of broad-spectrum antibiotics used in the treatment of serious Gram-negative bacterial infections, they target the 16S RNA subunit and upon binding cause errors in translation, eventually inducing a bactericidal effect [1]. Aminoglycoside nucleotidyltransferase (2")-Ia (ANT(2")-Ia) is an aminoglycoside modifying enzyme that prevents aminoglycosides from binding to the ribosomal subunit, making this enzyme a principle candidate structure-based drug design [2]. Characterization of ANT(2")-Ia has been proven to be difficult due to the low stability and solubility of overexpressed protein, where 95% of the protein being expressed is in the form of inclusion bodies [3]. We describe a protocol that has lead to successful expression and purification of ANT(2")-Ia. A successful enzymatic assay has also been adapted and the protein is active and stable under these conditions with a specific activity of 0.14 U/mg. Furthermore, nuclear magnetic resonance (NMR) studies have allowed for the assignment of 144 of the 176 non-proline backbone residues. Substrate binding NMR experiments have shown unique global chemical shift perturbations upon binding ATP and tobramycin, suggesting unique binding sites for each substrate. Structural determination of ANT(2")-Ia using NMR in conjunction with x-ray crystallography can be utilized in order to develop small molecules that will act as more effective aminoglycosides in order to inhibit ANT(2")-Ia from binding and modifying these antibiotics.
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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 | 0.000 |
| 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".