Electrochemical Quantitation of Supramolecular Complexation upon “Clicking” Cucurbit[7]uril Hosts on the Surface: From Drug Excipients to Steroids
Bibliographic record
Abstract
Cucurbit[7]uril (CB[7]), which is highly favorable for binding ferrocene (Fc) derivatives in solution and on the surface, has stood out as a promising electrochemical sensing motif due to its readily quantifiable redox responses. Given that understanding the complexation between CB[7] and drug candidates or steroids is crucial for pharmaceutical and steroidal applications, we report herein our electrochemical investigation to quantitate the affinity between surface-bound CB[7] and nonredox-active guests through competitive binding against ferrocene methanol (FcMeOH). The immobilization of the supramolecular host relies on the formation of azide-terminated alkanethiolate self-assembled monolayers (SAMs) on gold and subsequent copper(I)-catalyzed azide–alkyne cycloaddition (CuAAC) with alkyne-modified CB[7]. By incubating FcMeOH and subsequently a drug/steroid molecule, the competitive binding between CB[7]@drug/steroid and CB[7]@ferrocene complexes on the surface can be quantified with cyclic voltammetry, despite the nonredox-active nature of drug or steroid compounds. The formation constants of CB[7]@drug/steroid complexes are obtained with high accuracy, and a quantitative assay method is developed by establishing a linear relationship between the electrochemical signal and the guest concentration. Not only are the determined binding constants consistent with the literature values from conventional instrumental analyses (e.g., HPLC), but the obtained limits of detection (LODs) are also remarkable (i.e., from sub to low μM range).
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".