Nanovolume Kinase Inhibition Assay Using a Sol−Gel-Derived Multicomponent Microarray
Bibliographic record
Abstract
We report on the development of a new class of kinase microarrays based on the coimmobilization of both kinase and substrate components within a single pin-printed sol-gel microarray element and the use of such arrays for nanovolume inhibition assays. We successfully immobilized the alpha-catalytic subunit of cAMP-dependent protein kinase (PKA) and the peptide substrate kemptide within sol-gel-derived microarrays for the purpose of monitoring phosphorylation and inhibition. Using Pro-Q Diamond stain as an end-point indicator of phosphorylation, we demonstrate the selective detection of phosphoproteins over nonphosphorylated controls and the ability to detect phosphorylated proteins over a 500-fold concentration range. Limits of detection for the phosphoprotein beta-casein were 7.5 pg, and the detectable signal remained linear up to 3.75 ng of protein per array spot. PKA is demonstrated to be active when coentrapped with two different substrates, and inhibition assays for PKA with the inhibitors H7 and H89 demonstrate the ability to detect kinase inhibition as well as derive IC50 plots from a single array using an overprinting method to deliver approximately 0.6 nL of reagent per array element, or a total of 72 nL of reagents to generate a full, 12-point IC50 curve in pentuplicate.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".