Reaction of<i>Mycobacterium tuberculosis</i>Cytochrome P450 Enzymes with Nitric Oxide
Bibliographic record
Abstract
During the initial growth infection stage of Mycobacterium tuberculosis (Mtb), (*)NO produced by host macrophages inhibits heme-containing terminal cytochrome oxidases, inactivates iron/sulfur proteins, and promotes entry into latency. Here we evaluate the potential of (*)NO as an inhibitor of Mtb cytochrome P450 enzymes, as represented by CYP130, CYP51, and the two previously uncharacterized enzymes CYP125 and CYP142. Using UV-visible absorption, resonance Raman, and stopped-flow spectroscopy, we investigated the reactions of (*)NO with these heme proteins in their ferric resting form. (*)NO coordinates tightly to CYP125 and CYP142 (submicromolar) and with a lower affinity (micromolar) to CYP130 and CYP51. Anaerobic reduction of the ferric-NO species with sodium dithionite led to the formation of two spectrally distinct classes of five-coordinate ferrous-NO complexes. Exposure of these species to O(2) revealed that the ferrous-NO forms of CYP125 and CYP142 are labile and convert back to the ferric state within a few minutes, whereas ferrous CYP130 and CYP51 bind (*)NO almost irreversibly. This work clearly indicates that, at physiological concentrations (approximately 1 microM), (*)NO would impair the activity of CYP130 and CYP51, whereas CYP125 and CYP142 are more resistant. Selective P450 inhibition may contribute to the inhibitory effects of (*)NO on Mtb growth.
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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".