Structural investigations connect the disordered N‐terminal extension of <scp>HypB</scp> to the activities of <scp>HypB</scp> and <scp>SlyD</scp> in <i>E. coli</i>
Bibliographic record
Abstract
The activities of [NiFe]-hydrogenase enzymes, which are critical to many microbes, require insertion of a Ni(II) ion into the bimetallic catalytic center. Delivery of Ni(II) to [NiFe]-hydrogenases depends, in part, on the metallochaperone HypB, which lies at the center of a Ni(II) transfer pathway that includes the metal storage protein SlyD and the metallochaperone HypA. SlyD is a source of Ni(II) ions for HypB, whereas Ni(II) from HypB is transferred to HypA. In this work, we examine how the intrinsically disordered N-terminal extension (NTE) of HypB modulates the action of the HypB GTPase domain (G-domain). The NTE contains a high-affinity Ni(II) binding site, while the G-domain contains a lower affinity Ni(II) binding site that is affected by binding of guanine nucleotides. The HypB G-domain is also affected by SlyD and provides Ni(II) to HypA. Our NMR data show that, although disordered, the HypB NTE possesses residual structure and makes transient interactions with the HypB G-domain and with SlyD. A set of common residues in the center of the NTE are affected by SlyD and G-domain binding, and also by binding of Ni(II) to the high-affinity site located at the N terminus of the protein. The NTE interacts with residues in or near the Ni(II)- and GDP-binding sites in the G-domain, which are also affected when SlyD binds the NTE. Thus, the data showcase a complex interaction network between HypB and SlyD, and provide molecular details regarding how the HypB NTE links the activities of the HypB G-domain and SlyD.
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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 | 0.001 |
| 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".