Structure-Based Optimization of a Small Molecule Antagonist of the Interaction Between WD Repeat-Containing Protein 5 (WDR5) and Mixed-Lineage Leukemia 1 (MLL1)
Bibliographic record
Abstract
WD repeat-containing protein 5 (WDR5) is an important component of the multiprotein complex essential for activating mixed-lineage leukemia 1 (MLL1). Rearrangement of the MLL1 gene is associated with onset and progression of acute myeloid and lymphoblastic leukemias, and targeting the WDR5-MLL1 interaction may result in new cancer therapeutics. Our previous work showed that binding of small molecule ligands to WDR5 can modulate its interaction with MLL1, suppressing MLL1 methyltransferase activity. Initial structure-activity relationship studies identified N-(2-(4-methylpiperazin-1-yl)-5-substituted-phenyl) benzamides as potent and selective antagonists of this protein-protein interaction. Guided by crystal structure data and supported by in silico library design, we optimized the scaffold by varying the C-1 benzamide and C-5 substituents. This allowed us to develop the first highly potent (Kdisp < 100 nM) small molecule antagonists of the WDR5-MLL1 interaction and demonstrate that N-(4-(4-methylpiperazin-1-yl)-3'-(morpholinomethyl)-[1,1'-biphenyl]-3-yl)-6-oxo-4-(trifluoromethyl)-1,6-dihydropyridine-3-carboxamide 16d (OICR-9429) is a potent and selective chemical probe suitable to help dissect the biological role of WDR5.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".