Bibliographic record
Abstract
[NiFe]-hydrogenases catalyze the reversible conversion of hydrogen gas into protons and electrons and are vital metabolic components of many species of bacteria and archaea. At the core of this enzyme is a sophisticated catalytic center comprising nickel and iron, as well as cyanide and carbon monoxide ligands, which is anchored to the large hydrogenase subunit through cysteine residues. The production of this multicomponent active site is accomplished by a collection of accessory proteins and can be divided into discrete stages. The iron component is fashioned by the proteins HypC, HypD, HypE, and HypF, which functionalize iron with cyanide and carbon monoxide. Insertion of the iron center signals to the metallochaperones HypA, HypB, and SlyD to selectively deliver the nickel to the active site. A specific protease recognizes the completed metal cluster and then cleaves the C-terminus of the large subunit, resulting in a conformational change that locks the active site in place. Finally, the large subunit associates with the small subunit, and the complete holoenzyme translocates to its final cellular position. Beyond this broad overview of the [NiFe]-hydrogenase maturation process, biochemical and structural studies are revealing the fundamental underlying molecular mechanisms. Here, we review recent work illuminating how the accessory proteins contribute to the maturation of [NiFe]-hydrogenase and discuss some of the outstanding questions that remain to be resolved.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".