Protein Binding and Orientation Matter: Bias-Induced Conductance Switching in a Mutated Azurin Junction
Bibliographic record
Abstract
Abstract We observe reversible, bias-induced switching of conductance via a blue copper protein azurin mutant, N42C Az, with a nearly 10-fold increase at |V| > 0.8 V than at lower bias. No such switching is found for wild-type azurin, WT Az, up to |1.2 V|, beyond which irreversible changes occur. The N42C Az mutant will, when positioned between electrodes in a solid-state Au–protein–Au junction, have an orientation opposite that of WT Az with respect to the electrodes. Current(s) via both proteins are temperature-independent, consistent with quantum mechanical tunneling as dominant transport mechanism. No noticeable difference is resolved between the two proteins in conductance and inelastic electron tunneling spectra at <|0.5 V| bias voltages. Switching behavior persists from 15 K up to room temperature. The conductance peak is consistent with the system switching in and out of resonance with the changing bias. With further input from UV photoemission measurements on Au–protein systems, these striking differences in conductance are rationalized by having the location of the Cu(II) coordination sphere in the N42C Az mutant, proximal to the (larger) substrate-electrode, to which the protein is chemically bound, while for the WT Az that coordination sphere is closest to the other Au electrode, with which only physical contact is made. Our results establish the key roles that a protein’s orientation and binding nature to the electrodes play in determining the electron transport tunnel barrier.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".