Discovery of a Low Toxicity O-GlcNAc Transferase (OGT) Inhibitor by Structure-based Virtual Screening of Natural Products
Bibliographic record
Abstract
O-GlcNAc transferase (OGT) plays an important role in regulating numerous cellular processes through reversible post-translational modification of nuclear and cytoplasmic proteins. However, the function of O-GlcNAcylation is still not well understood. Cell permeable OGT inhibitors are needed to manipulate O-GlcNAcylation levels and clarify the regulatory mechanism of this modification. Here, we report a specific natural-product OGT inhibitor (L01), which was identified from a structure-based virtual screening analysis. L01 inhibited O-GlcNAcylation both in vitro and in cells without significantly altering cell surface glycans. Molecular dynamics and site-directed mutagenesis indicated a new binding mechanism in which L01 could interact with Asn557 near the UDP binding pocket of OGT. This residue may contribute to the specificity of L01. Furthermore, as a specific OGT inhibitor, L01 produced low toxicity in cellular and zebrafish models. The identification of L01 validates structure-based virtual screening approaches for the discovery of OGT inhibitors. L01 can also serve as a chemical tool to further characterize O-GlcNAcylation functions or a new molecular core for structure-activity relationship studies to optimize the biochemical potencies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".