An ESI‐MS/MS Method for Screening of Small‐Molecule Mixtures against Glycogen Synthase Kinase‐3β (GSK‐3β)
Bibliographic record
Abstract
Glycogen synthase kinase-3beta (GSK-3beta) is involved in the hyperphosphorylation of previously phosphorylated (primed) substrates, and is currently assayed using an approach based on the incorporation of gamma-(32)P-radiolabelled isotopes into substrate peptides. The requirement to detect hyperphosphorylation of a primed substrate poses a particular challenge for development of a high-throughput screening assay, as many current kinase assays are designed to produce a signal in the presence of any phosphorylation site, and thus are only suitable for beta-unphosphorylated substrates. Herein, we have developed an electrospray-ionization tandem mass spectrometry (ESI-MS/MS) assay to allow for direct detection of a hyperphosphorylated product which is formed in a solution reaction involving a primed peptide substrate (GSM peptide) and GSK-3beta. Optimum reaction conditions (level of Mg(2+), buffer type, ionic strength, pH, enzyme concentration, and reaction time) were established to both maintain the activity of GSK-3beta and allow for substrate and product quantification through ESI/MS/MS. We show that the MS-based assay allows for rapid determination of GSK-3beta activity from reaction volumes of approximately 40 microL and that it can be used to assess IC(50) values and the site of action of known inhibitors. It also can be used for automated screening of small-molecules mixtures to identify inhibitors of GSK-3beta.
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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 | 0.000 |
| 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".