Competitive inhibition of histone deacetylase activity by trichostatin A and butyrate
Bibliographic record
Abstract
Histone deacetylases (HDACs) play a pivotal role in gene expression through their involvement in chromatin remodeling. The abnormal targeting or retention of HDACs to DNA regulatory regions is observed in many cancers, and hence HDAC inhibitors are being tested as promising anti-tumor agents. The results of previous kinetic studies, characterizing trichostatin A (TSA), as well as butyrate, as HDAC noncompetitive inhibitors, conflict with crystallographic and homology modeling data suggesting that TSA should act as a competitive inhibitor. Our results demonstrate that each of the HDAC inhibitors TSA and butyrate inhibits HDAC activity in a competitive fashion. Co-immunoprecipitation studies show that the inhibition of HDAC1 and HDAC2 activity by TSA does not disturb the extensive level of their association in the human breast cancer cell line MCF-7. Moreover, the inhibition of HDAC activity by TSA does not interfere with the interaction of HDAC1 and HDAC2 with Sin3A, a core component of the Sin3 complex. Thus, repressor complexes such as Sin3, appear to be stable in the presence of TSA. The association of HDAC2 with transcription factor Sp1 is also not affected by TSA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".