Structure-based design generated novel hydroxamic acid based preferential HDAC6 lead inhibitor with on-target cytotoxic activity against primary choroid plexus carcinoma
Bibliographic record
Abstract
Histone deacetylase 6 (HDAC6) is an attractive target for cancer therapeutic intervention. Selective HDAC6 inhibitors is important to minimise the side effects of pan inhibition. Thus, new class of hydroxamic acid-based derivatives were designed on structural basis to perform preferential activity against HDAC6 targeting solid tumours. Interestingly, 1-benzylbenzimidazole-2-thio-N-hydroxybutanamide 10a showed impressive preference with submicromolar potency against HDAC6 (IC50 = 510 nM). 10a showed cytotoxic activity with interesting profile against CCHE-45 at (IC50 = 112.76 µM) when compared to standard inhibitor Tubacin (IC50 = 20 µM). Western blot analysis of acetylated-α-tubulin verified the HDAC6 inhibiting activity of 10a. Moreover, the insignificant difference in acetylated-α-tubulin induced by 10a and Tubacin implied the on-target cytotoxic activity of 10a. Docking of 10a in the binding site of HDAC6 attributed the activity of 10a to π-π stacking with the amino acids of the hydrophobic channel of HDAC6 and capture of zinc metal in bidentate fashion. The therapeutic usefulness besides the on-target activity may define 10a as an interesting safe-lead inhibitor for future 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) | 0.003 | 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".