An Activity-Based Oxaziridine Platform for Identifying and Developing Covalent Ligands for Functional Allosteric Methionine Sites: Redox-Dependent Inhibition of Cyclin-Dependent Kinase 4
Bibliographic record
Abstract
Activity-based protein profiling (ABPP) is a versatile strategy for enabling identification and characterization of new functional protein sites and discovery of lead compounds for therapeutic development. Yet, the vast majority of ABPP methods applied for covalent drug discovery target highly nucleophilic amino acids such as cysteine or lysine. Here, we report a methionine-directed ABPP platform using Redox-Activated Chemical Tagging (ReACT), which leverages a biomimetic oxidative ligation strategy for selective methionine modification. Application of ReACT to the cancer-driver protein cyclin-dependent kinase 4 (CDK4) as a representative high-value drug target identified three new hyperreactive, ligandable methionine residues, including an allosteric M169 site that is proximal to an activating T172 phosphorylation site. With this information in hand, we designed and synthesized a new methionine-targeting covalent ligand library based on oxaziridine fragments bearing a diverse array of heterocyclic, heteroatom, and stereochemically-rich substituents. ABPP screening of this focused library against a clickable broad-spectrum ReACT probe identified 1oxF11 as a covalent modifier of the CDK4/Cyclin-D1 heterodimer at the M169 site. This compound inhibited CDK4 kinase activity in a dose-dependent manner on purified protein and in live cells. Further biochemical analyses with a phospho-specific CDK4 antibody revealed crosstalk between M169 oxidation and T172 phosphorylation upon 1oxF11 treatment, where M169 oxidation prevented phosphorylation of the activating T172 site on CDK4 and blocked cell cycle progression at the S-phase checkpoint. By identifying a new mechanism for allosteric methionine redox regulation on CDK4 and developing a unique modality for its therapeutic intervention, this work showcases a generalizable platform that provides a starting point for engaging in broader chemoproteomics and protein ligand discovery efforts to find and target previously undruggable methionine sites.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".