Abstract 3236: Discovery of hydrazide-based HDAC8 selective PROTACs
Bibliographic record
Abstract
Abstract HDAC8 plays crucial roles in biological processes and is a highly desirable target for therapeutic interventions. However, due to the conserved catalytic domain among HDACs, developing specific inhibitors for these isozymes has proven challenging. HDAC8 also has deacetylase-independent activity which cannot be blocked by an inhibitor. Previously we reported the discoveries of a potent HDAC3 degrader XZ9002 and an HDAC3/8 dual degrader YX968. In this study, we carried out further optimizations based on the warhead of YX968 through rational design, which led to the discovery of YX862 and YL246, novel hydrazide-based HDAC8 selective PROTAC degraders with single-digit nanomolar DC50 and excellent selectivity. We demonstrated that the degradation of HDAC8 affects its non-histone substrates; however, it does not trigger profound histone hyper-acetylation and gene expression alteration, highlighting the unique role of HDAC8. The PROTACs developed in this study are well-characterized HDAC8 degraders without triggering pan-HDAC inhibition which represent valuable tool compounds for exploring the biological and therapeutic potential of HDAC8 in cancers and beyond. Citation Format: Yufeng Xiao, Yi Liu, Nikee Awasthee, Chengcheng Meng, Michael He, Seth Hale, Rashmi Karki, Zongtao Lin, Robert Kridel, Daiqing Liao, Guangrong Zheng. Discovery of hydrazide-based HDAC8 selective PROTACs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3236.
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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) | 0.002 | 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".