Identification of NAE Inhibitors Exhibiting Potent Activity in Leukemia Cells: Exploring the Structural Determinants of NAE Specificity
Bibliographic record
Abstract
MLN4924 is a selective inhibitor of the NEDD8-activating enzyme (NAE) and has advanced into clinical trials for the treatment of both solid and hematological malignancies. In contrast, the structurally similar compound 1 (developed by Millennium: The Takeda Oncology Company) is a pan inhibitor of the E1 enzymes NAE, ubiquitin activating enzyme (UAE), and SUMO-activating enzyme (SAE) and is currently viewed as unsuitable for clinical use given its broad spectrum of E1 inhibition. Here, we sought to understand the determinants of NAE selectivity. A series of compound 1 analogues were synthesized through iterative functionalization of the purine C6 position and evaluated for NAE specificity. Optimal NAE specificity was achieved through substitution with primary N-alkyl groups, while bulky or secondary N-alkyl substituents were poorly tolerated. When assessed in vitro, inhibitors reduced the growth and viability of malignant K562 leukemia cells. Through this study, we have successfully identified a series of sub-10 nM NAE-specific inhibitors and thereby highlighted the functionalities that promote NAE selectivity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".