ArticleChemMedChem2025
AlphaFold-Guided Discovery of an Overlapping MYC/Miz-1 Interface Enables Peptidomimetic Disruption of MYC/MAX.
Article in ChemMedChem, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The trial behind it
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Who cites it
3 citing papers in PubMed.
- Targeting MYC-Driven Cancers: From Oncogenic Addiction to Therapeutic Vulnerability.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026Review
- Tumor-infiltrating lymphocytes in triple-negative breast cancer: molecular mechanisms, spatial regulation, and therapeutic implications.Breast cancer research : BCR · 2026Review
- AlphaFold-Guided Discovery of an Overlapping MYC/Miz-1 Interface Enables Peptidomimetic Disruption of MYC/MAX.ChemMedChem · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
Intrinsically disordered proteins (IDPs) lack stable structure and classical binding pockets, making them remarkably difficult to drug. However, upon interacting with partner proteins, IDPs can form transient yet specific and defined interfaces, which, if discovered, can become exploitable footholds for therapeutic intervention. Here, AlphaFold-Multimer is used to shine light on the underexplored oncogenic protein-protein interaction between MYC and Miz-1. Notably, AlphaFold-Multimer predicts that Miz-1 binds at a site overlapping with the MYC/MAX dimerization domain, which is MYC's best-characterized oncogenic interface. Guided by this prediction, stapled peptidomimetics are designed and synthesized, targeting the MYC/Miz-1 and MYC/MAX interface. The best variant, Mizmetic 2, binds MYC and alanine scanning identifies key binding hotspots and promising sites for beneficial substitutions. The optimized variants disrupt MYC/MAX complex formation and prevents MYC from binding its canonical E-box DNA elements in vitro, with submicromolar potency. MAX/MAX DNA complex formation is also reduced, likely indicating some degree of unspecific binding. While still at a proof-of-concept stage, the findings showcase how AI-based structure prediction can illuminate disordered protein interactions and reveal new targetable sites on MYC.
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Registered trials
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