Anisotropic Covalency Contributions to Superexchange Pathways in Type One Copper Active Sites
Bibliographic record
Abstract
Type one (T1) Cu sites deliver electrons to catalytic Cu active sites: the mononuclear type two (T2) Cu site in nitrite reductases (NiRs) and the trinuclear Cu cluster in the multicopper oxidases (MCOs). The T1 Cu and the remote catalytic sites are connected via a Cys-His intramolecular electron-transfer (ET) bridge, which contains two potential ET pathways: P1 through the protein backbone and P2 through the H-bond between the Cys and the His. The high covalency of the T1 Cu-S(Cys) bond is shown here to activate the T1 Cu site for hole superexchange via occupied valence orbitals of the bridge. This covalency-activated electronic coupling (H(DA)) facilitates long-range ET through both pathways. These pathways can be selectively activated depending on the geometric and electronic structure of the T1 Cu site and thus the anisotropic covalency of the T1 Cu-S(Cys) bond. In NiRs, blue (π-type) T1 sites utilize P1 and green (σ-type) T1 sites utilize P2, with P2 being more efficient. Comparing the MCOs to NiRs, the second-sphere environment changes the conformation of the Cys-His pathway, which selectively activates HDA for superexchange by blue π sites for efficient turnover in catalysis. These studies show that a given protein bridge, here Cys-His, provides different superexchange pathways and electronic couplings depending on the anisotropic covalencies of the donor and acceptor metal sites.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".