Enzymatically modified peptide surfaces: towards general electrochemical sensor platform for protein kinase catalyzed phosphorylations
Bibliographic record
Abstract
We hereby present an electrochemical approach for monitoring the three protein kinases sarcoma-related kinase (Src), extracellular signal-regulated kinase 1 (Erk1), and cyclin A-dependent kinase 2 (CDK2/cyclin A). The electrochemical sensor is based on the ability of kinases to transfer a redox-labeled phosphoryl group to surface-bound peptides that are highly specific substrates for the particular protein kinase (EGIYDVP, EPLTPSG, and HHASPRK, respectively). The detection method relies on the use of 5'-γ-ferrocenoyl-ATP (Fc-ATP) as a co-substrate for peptide phosphorylation. The peptides themselves are attached to a Au substrate, which acts as the working electrode. In this process a Fc-phosphoryl group is transferred to the peptide and the presence of the redox active Fc group is detected electrochemically. All peptide films were fully characterized by cyclic voltammetry (CV), square wave voltammetry (SWV), and electrochemical impedance spectroscopy (EIS). Particular attention was given to the electron transfer rates, k(ET), in peptide films after Fc-phosphorylation which were found to be on the order of seconds. The slow ET kinetics is presumably a result of the negative charge on the phosphoryl group. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) and X-ray photoelectron spectroscopy (XPS) experiments based on the peptide modified Au surfaces reveal significant ferrocene and phosphate group content introduced using the kinase-catalyzed phosphorylation reaction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".