A Direct Fluorescent Activity Assay for Glycosyltransferases Enables Convenient High‐Throughput Screening: Application to <i>O</i>‐GlcNAc Transferase
Bibliographic record
Abstract
Abstract Glycosyltransferases carry out important cellular functions in species ranging from bacteria to humans. Despite their essential roles in biology, simple and robust activity assays that can be easily applied to high‐throughput screening for inhibitors of these enzymes have been challenging to develop. Herein, we report a bead‐based strategy to measure the group‐transfer activity of glycosyltransferases sensitively using simple fluorescence measurements, without the need for coupled enzymes or secondary reactions. We validate the performance and accuracy of the assay using O‐GlcNAc transferase (OGT) as a model system through detailed Michaelis–Menten kinetic analysis of various substrates and inhibitors. Optimization of this assay and application to high‐throughput screening enabled screening for inhibitors of OGT, leading to a novel inhibitory scaffold. We believe this assay will prove valuable not only for the study of OGT, but also more widely as a general approach for the screening of glycosyltransferases and other group‐transfer enzymes.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".