Structural mimicry of UM171 and neomorphic cancer mutants co-opts E3 ligase KBTBD4 for HDAC1/2 recruitment
Bibliographic record
Abstract
Neomorphic mutations and drugs can elicit unanticipated effects that require mechanistic understanding to inform clinical practice. Recurrent indel mutations in the Kelch domain of the KBTBD4 E3 ligase rewire epigenetic programs for stemness in medulloblastoma by recruiting LSD1-CoREST-HDAC1/2 complexes as neo-substrates for ubiquitination and degradation. UM171, an investigational drug for haematopoietic stem cell transplantation, was found to degrade LSD1-CoREST-HDAC1/2 complexes in a wild-type KBTBD4-dependent manner, suggesting a potential common mode of action. Here, we identify that these neomorphic interactions are mediated by the HDAC deacetylase domain. Cryo-EM studies of both wild-type and mutant KBTBD4 capture 2:1 and 2:2 KBTBD4-HDAC2 complexes, as well as a 2:1:1 KBTBD4-HDAC2-CoREST1 complex, at resolutions spanning 2.7 to 3.3 Å. The mutant and drug-induced complexes adopt similar structural assemblies requiring both Kelch domains in the KBTBD4 dimer for each HDAC2 interaction. UM171 is identified as a bona fide molecular glue binding across the ternary interface. Most strikingly, the indel mutation reshapes the same surface of KBTBD4 providing an example of a natural mimic of a molecular glue. Together, the structures provide mechanistic understanding of neomorphic KBTBD4, while structure-activity relationship (SAR) analysis of UM171 reveals analog S234984 as a more potent molecular glue for future studies.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".