Discovery of YSR734: A Covalent HDAC Inhibitor with Cellular Activity in Acute Myeloid Leukemia and Duchenne Muscular Dystrophy
Bibliographic record
Abstract
Histone deacetylases (HDACs) have emerged as powerful epigenetic modifiers of histone/non-histone proteins via catalyzing the deacetylation of ε- N -acetyl lysines. The dysregulated activity of these Zn 2+ -dependent hydrolases has been broadly implicated in disease, notably cancer. Clinically, the recurring dose-limiting toxicities of first-generation HDACi sparked a paradigm shift toward safer isoform-specific molecules. With pervasive roles in aggressive diseases, there remains a need for novel approaches to target these enzymes. Herein, we report the discovery of YSR734, a first-in-class covalent HDACi, with a 2-aminobenzanilide Zn 2+ chelate and a pentafluorobenzenesulfonamide electrophile. This class I selective proof of concept modified HDAC2 Cys274 (catalytic domain), with nM potency against HDAC1–3, sub-μM activity in MV4–11 cells, and limited cytotoxicity in MRC-9 fibroblasts. In C2C12 myoblasts, YSR734 activated muscle-specific biomarkers myogenin/Cav3, causing potent differentiation into myotubes (applications in Duchenne Muscular Dystrophy). Current efforts are focused on improving in vivo ADME toward a preclinical covalent HDACi.
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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) | 0.000 | 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) | 0.001 | 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".