Ligand‐Directed Chemistry on Glycoside Hydrolases – A Proof of Concept Study
Bibliographic record
Abstract
Selective covalent labelling of enzymes using small molecule probes has advanced the scopes of protein profiling. The covalent bond formation to a specific target is the key step of activity-based protein profiling (ABPP), a method which has become an indispensable tool for measuring enzyme activity in complex matrices. With respect to carbohydrate processing enzymes, strategies for ABPP so far involve labelling the active site of the enzyme, which results in permanent loss of activity. Here, we report in a proof of concept study the use of ligand-directed chemistry (LDC) for labelling glycoside hydrolases near - but not in - the active site. During the labelling process, the competitive inhibitor is cleaved from the probe, departs the active site and the enzyme maintains its catalytic activity. To this end, we designed a building block synthetic concept for small molecule probes containing iminosugar-based reversible inhibitors for labelling of two model β-glucosidases. The results indicate that the LDC approach can be adaptable for covalent proximity labelling of glycoside hydrolases.
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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 | 0.001 |
| 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) | 0.001 | 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".