Kinase Inhibitor Selectivity Profiling Using Differential Scanning Fluorimetry
Why this work is in the frame
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Bibliographic record
Abstract
Fast, robust, and inexpensive screening methods are the heart of drug discovery processes. Moreover, it is useful to have access to several established assay formats, for validation purposes. If a targeted protein is an enzyme, the logical and widely used approach is the direct measurement of the effect of the added ligands on its activity. A variety of enzymatic assay formats have been successfully applied for inhibitor screening of protein kinases. However, enzymatic assays require an active enzyme with a known substrate and often time-consuming assay optimization. Several alternative approaches have been recently developed that detect binding of ligands to proteins. This chapter overviews and provides the experimental protocol of the successful application of differential scanning fluorimetry (DSF) in our laboratory for fast and robust screening of medium-sized (<10,000) inhibitor libraries. DSF monitors the thermal stabilization of the native protein structure upon ligand binding. It allows selectivity profiling of any protein kinase without prior knowledge of either substrate or activity of the kinase under investigation. Comparative studies revealed that generated data is highly reproducible and correlates well with the results from other ligand binding methodologies, direct binding constants as well as enzymatic assays.
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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 | 0.001 | 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 it