Effects of Metal on the Biochemical Properties of <i>Helicobacter pylori</i> HypB, a Maturation Factor of [NiFe]-Hydrogenase and Urease
Bibliographic record
Abstract
The biosyntheses of the [NiFe]-hydrogenase and urease enzymes in Helicobacter pylori require several accessory proteins for proper construction of the nickel-containing metallocenters. The hydrogenase accessory proteins HypA and HypB, a GTPase, have been implicated in the nickel delivery steps of both enzymes. In this study, the metal-binding properties of H. pylori HypB were characterized, and the effects of metal binding on the biochemical behavior of the protein were examined. The protein can bind stoichiometric amounts of Zn(II) or Ni(II), each with nanomolar affinity. Mutation of Cys106 and His107, which are located between two major GTPase motifs, results in undetectable Ni(II) binding, and the Zn(II) affinity is weakened by 2 orders of magnitude. These two residues are also required for the metal-dependent dimerization observed in the presence of Ni(II) but not Zn(II). The addition of metals to the protein has distinct impacts on GTPase activity, with zinc significantly reducing GTP hydrolysis to below detectable levels and nickel only slightly altering the k(cat) and K(m) of the reaction. The regulation of HypB activities by metal binding may contribute to the maturation of the nickel-containing enzymes.
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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) | 0.000 | 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) | 0.001 | 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 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".