Photocatalytic Hydrogen Evolution by a De Novo Designed Metalloprotein that Undergoes Ni‐Mediated Oligomerization Shift
Bibliographic record
Abstract
Abstract De novo metalloprotein design involves the construction of proteins guided by specific repeat patterns of polar and apolar residues, which, upon self‐assembly, provide a suitable environment to bind metals and produce artificial metalloenzymes. While a wide range of functionalities have been realized in de novo designed metalloproteins, the functional repertoire of such constructs towards alternative energy‐relevant catalysis is currently limited. Here we show the application of de novo approach to design a functional H2 evolving protein. The design involved the assembly of an amphiphilic peptide featuring cysteines at tandem a/d sites of each helix. Intriguingly, upon NiII addition, the oligomers shift from a major trimeric assembly to a mix of dimers and trimers. The metalloprotein produced H2 photocatalytically with a bell‐shape pH dependence, having a maximum activity at pH 5.5. Transient absorption spectroscopy is used to determine the timescales of electron transfer as a function of pH. Selective outer sphere mutations are made to probe how the local environment tunes activity. A preferential enhancement of activity is observed via steric modulation above the NiII site, towards the N‐termini, compared to below the NiII site towards the C‐termini.
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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) | 0.000 | 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 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".