A Sol−Gel-Derived Acetylcholinesterase Microarray for Nanovolume Small-Molecule Screening
Bibliographic record
Abstract
A fluorimetric acetylcholinesterase (AChE) assay was developed and characterized both in solution and with the enzyme entrapped in sol-gel-derived silica. The assay is based on a disulfide-thiol interchange reaction between the intramolecularly quenched dimeric dye BODIPY FL l-cystine and thiocholine generated by the AChE-catalyzed hydrolysis of acetylthiocholine (ATCh), which results in a brightly fluorescent monomeric product owing to the cleavage of the disulfide-coupled form of the dye. The new assay was validated by comparison with the Ellman assay performed under parallel conditions and was used in both kinetic and end point assays. The assay was extended to the fabrication of functional AChE microarrays using contact pin-printing of sol-gel-derived silica. A total of 392 sol-gel formulations were screened for gelation times and 192 of these were further evaluated for array fabrication on four different surfaces using a factor analysis approach. Of these, 66 sol-gel/surface combinations produced robust microarrays, while 26 sol-gel/surface combinations were identified that could produce highly active AChE microarrays. The Z' factor for the on-array assay using an optimal sol-gel/surface combination, which considers both signal variability and difference in signals between positive and negative controls, was determined to be 0.60, which is above the minimum level required for applicability to screening. By overprinting nanoliter volumes of solutions containing the dye, ATCh, and potential inhibitors, these microarrays could be used to screen two libraries of small molecules, one composed of newly synthesized alkaloids and another consisting of ∼1000 known bioactive compounds, both as discrete compounds and mixtures thereof, for activity against AChE. IC(50) values were obtained on microarrays for compounds showing significant inhibitory activity, demonstrating the utility of arrays for quantitative inhibition assays.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".