Effect of solvent and protein dynamics in ligand recognition and inhibition of aminoglycoside adenyltransferase 2″‐Ia
Bibliographic record
Abstract
The aminoglycoside modifying enzyme (AME) ANT(2″)-Ia is a significant target for next generation antibiotic development. Structural studies of a related aminoglycoside-modifying enzyme, ANT(3″)(9), revealed this enzyme contains dynamic, disordered, and well-defined segments that modulate thermodynamically before and after antibiotic binding. Characterizing these structural dynamics is critical for in situ screening, design, and development of contemporary antibiotics that can be implemented in a clinical setting to treat potentially lethal, antibiotic resistant, human infections. Here, the first NMR structural ensembles of ANT(2″)-Ia are presented, and suggest that ATP-aminoglycoside binding repositions the nucleotidyltransferase (NT) and C-terminal domains for catalysis to efficiently occur. Residues involved in ligand recognition were assessed by site-directed mutagenesis. In vitro activity assays indicate a critical role for I129 toward aminoglycoside modification in addition to known catalytic D44, D46, and D48 residues. These observations support previous claims that ANT aminoglycoside sub-class promiscuity is not solely due to binding cleft size, or inherent partial disorder, but can be controlled by ligand modulation on distinct dynamic and thermodynamic properties of ANTs under cellular conditions. Hydrophobic interactions in the substrate binding cleft, as well as solution dynamics in the C-terminal tail of ANT(2″)-Ia, advocate toward design of kanamycin-derived cationic lipid aminoglycoside analogs, some of which have already shown antimicrobial activity in vivo against kanamycin and gentamicin-resistant P. aeruginosa. This data will drive additional in silico, next generation antibiotic development for future human use to combat increasingly prevalent antimicrobial resistance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 | 0.000 |
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 teacher head, 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".