Novel Hydroxamate and Anilide Derivatives as Potent Histone Deacetylase Inhibitors: Synthesis and Antiproliferative Evaluation
Bibliographic record
Abstract
There is a currently growing interest in the development of histone deacetylase inhibitors (HDACs) as anticancer agents. Histone deacetylases are critically important in the functional regulation of gene transcription as well as in chromatin structure remodeling. A number of small molecule inhibitors of HDAC, such as the naturally occurring trichostatin A (TSA), as well as synthetic compounds, such as suberoylanilide hydroxamic acid (SAHA), scriptaid, oxamflatin or MS-275, have been reported to induce differentiation of several cancer cell lines and suppress cell proliferation. This article will review the recent progress being made in our laboratories in the development of two new families of potent HDAC inhibitors: sulfonamide hydroxamic acids and anilides, as well as TSA-like straight chain derivatives. Some of these compounds inhibit partially purified recombinant human HDAC enzymes with IC(50)'s in the micromolar to low nanomolar range and can induce hyperacetylation of histones in human cancer cells. These compounds significantly inhibit proliferation, induce expression of p21(WAF1/Cip1), and cause cell cycle arrest in various human cancer cells. The lead candidates were screened in a panel of human tumor and normal cell lines. The inhibition of HDAC activity represents a novel approach for intervening in cell cycle regulation and may be used in future cancer therapies. The structure-activity relationships, the antiproliferative activity and the in vivo efficacy are discussed.
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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) | 0.000 | 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) | 0.003 | 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".