The catalytic mechanism for NO production by the mitochondrial enzyme, sulfite oxidase
Bibliographic record
Abstract
Abstract Recently, Guenter Schwarz and colleagues published an elegant study in the Biochemical Journal (2019) 476, 1805–1815 which combines kinetic and spectroscopic studies with protein engineering to provide a mechanism for sulfite oxidase (SO)-catalyzed nitrite reduction that yields nitric oxide (NO). This work is noteworthy as it demonstrates that (i) for NO generation, both sulfite and nitrite must bind to the same molybdenum (Mo) center; (ii) upon sulfite reduction, Mo is reduced from +6 (MoVI) to +4 (MoIV) and MoIV reduces nitrite to NO yielding MoV; (iii) the heme moiety, linked to the Mo-center by an 11 amino acid residue tether, gets reduced by intramolecular electron transfer (IET) resulting in MoV being oxidized to MoVI; (iv) the reduced heme transfers its electron to a second nitrite molecule converting it to NO; (v) the authors demonstrate steady-state NO production in the presence of the natural electron acceptor cytochrome c; (vi) Finally, the authors use protein engineering to shorten the heme tether to reduce the heme-Mo-center distance with the aim of increasing NO production. Consequently, the rate of IET to cytochrome c is decreased but the enzymatic turnover rate for NO production is increased by ∼10-fold. This paper is unique as it provides strong evidence for a novel mechanism for steady-state NO production for human mitochondrial SO and serves as a potential template for studying NO production mechanisms in other enzymes by integrating the information gained from enzyme kinetics with EPR and UV/vis spectroscopy and protein engineering.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".