Application of 2D-ITC to the Elucidation of the Enzymatic Mechanism of <i>N</i>-Acetylmuramic Acid/<i>N</i>-Acetylglucosamine Kinase (AmgK) from <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
Characterization of the turnover mechanism of bisubstrate enzymes is a tedious task. Molecular tools for studying the enzymatic mechanism are not readily available for all enzymes (e.g., radioactive substrates, substrate-competitive inhibitors, etc.). Wang and Mittermaier recently introduced two-dimensional isothermal titration calorimetry (2D-ITC) for determining the bisubstrate mechanism at high resolution while simultaneously quantifying the kinetic parameters for substrate turnover in a single reporter-free experiment. We demonstrate the utility of 2D-ITC in studying N -acetylmuramic acid/ N -acetylglucosamine kinase (AmgK) from Pseudomonas aeruginosa . This enzyme is involved in cytoplasmic cell-wall-recycling events as a step in the peptidoglycan salvage pathway. Furthermore, AmgK phosphorylates N -acetylglucosamine and N -acetylmuramic acid, linking the recycling events to de novo cell-wall synthesis. We document in a 2D-ITC experiment that AmgK follows an ordered-sequential mechanism, where ATP binds first and ADP is released last. We also show that classical enzyme kinetic methods support the results of 2D-ITC and that 2D-ITC could overcome the shortcomings of these classical methodologies. We provide evidence for inhibition of AmgK by the catalytic product ADP, but not by the phosphorylated sugar product. These results provide a full kinetic characterization of the bacterial kinase AmgK. This work highlights 2D-ITC as a versatile tool for the mechanistic evaluation of bisubstrate enzymes, as an alternative for classical methods.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".