Influence of Molecular Dipole Moment on the Redox-Induced Reorganization of α-Helical Peptide Self-Assembled Monolayers: An Electrochemical SPR Investigation
Bibliographic record
Abstract
Self-assembled monolayers (SAMs) of ferrocene-labeled α-helical peptides were prepared on gold surfaces and studied using electrochemical surface plasmon resonance (EC-SPR). The leucine-rich peptides were synthesized with a cysteine sulfhydryl group either at the C- or N-terminus, enabling their immobilization onto gold surfaces with control of the direction of the molecular dipole moment. Two electroactive SAMs were studied, one in which all of the peptide dipole moments are oriented in the same direction (SAM1), and the other in which the peptide dipole moment of one peptide is aligned in the opposite direction to that of its surrounding peptide molecules (SAM2). Cyclic voltammetry combined with SPR measurements revealed that SAM reorientations concomitant with the oxidation of the ferrocene label were more significant in SAM2 than in SAM1. The substantially greater change in the peptide film thickness in the case of SAM2 is attributed to the electrostatic repulsion between the electrogenerated ferrocinium moiety and the positively charged gold surface. The greater permeability of SAM1 to electrolyte anions, on the other hand, appears to effectively neutralize this electrostatic repulsion. The film thickness change in SAM2 was estimated to be 0.25 ± 0.05 nm using numerical simulation. The timescale of the redox-induced SPR changes was established by chronoamperometry and time-resolved SPR measurements, followed by fitting of the SPR response to a stretched exponential function. The time constants measured for the anodic process were 16 and 6 ms for SAM1 and SAM2 respectively, indicating that the SAM thickness changes are notably fast.
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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".