Improved Pharmacokinetic Profiles of HDAC6 Inhibitors via Cap Group Modifications
Bibliographic record
Abstract
Abstract Hydroxamic acid (HA)-based HDAC inhibitors often suffer from poor pharmacokinetic (PK) profiles, limiting their in vivo applications. Cap group modification offers a promising strategy to address these challenges. Here, we optimized the cap group of TO-317, a selective HDAC6 inhibitor with a bisected cap structure, generating 26 analogs with comparable or improved HDAC6 binding affinity and selectivity. Replacing the redundant tetrafluorobenzene sulfonamide cap while retaining the essential picolyl cap group preserved the critical H614 hydrogen bond, as confirmed by X-ray crystallography (1.24–1.27 Å resolution) of five analogs. Analog 14, featuring a 2-chlorobenzene sulfonamide cap, demonstrated a 120-fold enhancement in plasma concentration in mice compared to that of TO-317. Preclinical studies showed that analog 14 achieved 56% tumor growth inhibition in an SM1 melanoma murine model without observed toxicity. These findings highlight cap group optimization as a powerful approach to enhance HA-based HDAC inhibitors for advanced preclinical and clinical development.
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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".