Catalase-peroxidases (KatG) Exhibit NADH Oxidase Activity
Bibliographic record
Abstract
Catalase-peroxidases (KatG) produced by Burkholderia pseudomallei, Escherichia coli, and Mycobacterium tuberculosis catalyze the oxidation of NADH to form NAD+ and either H2O2 or superoxide radical depending on pH. The NADH oxidase reaction requires molecular oxygen, does not require hydrogen peroxide, is not inhibited by superoxide dismutase or catalase, and has a pH optimum of 8.75, clearly differentiating it from the peroxidase and catalase reactions with pH optima of 5.5 and 6.5, respectively, and from the NADH peroxidase-oxidase reaction of horseradish peroxidase. B. pseudomallei KatG has a relatively high affinity for NADH (Km=12 microm), but the oxidase reaction is slow (kcat=0.54 min(-1)) compared with the peroxidase and catalase reactions. The catalase-peroxidases also catalyze the hydrazinolysis of isonicotinic acid hydrazide (INH) in an oxygen- and H2O2-independent reaction, and KatG-dependent radical generation from a mixture of NADH and INH is two to three times faster than the combined rates of separate reactions with NADH and INH alone. The major products from the coupled reaction, identified by high pressure liquid chromatography fractionation and mass spectrometry, are NAD+ and isonicotinoyl-NAD, the activated form of isoniazid that inhibits mycolic acid synthesis in M. tuberculosis. Isonicotinoyl-NAD synthesis from a mixture of NAD+ and INH is KatG-dependent and is activated by manganese ion. M. tuberculosis KatG catalyzes isonicotinoyl-NAD formation from NAD+ and INH more efficiently than B. pseudomallei KatG.
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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 | 0.000 |
| 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 | 0.000 |
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".