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一个重叠的MYC/Miz-1接口的AlphaFold引导的发现使MYC/MAX的皮模拟性破坏成为可能

Brecht D Ellenbroek^1,2, Amardhiko S S Tirtosentono¹, Sebastian J Pomplun^1,2

¹Leiden University, Leiden, 2333 CC, The Netherlands.

|October 26, 2025

概括

人工智能驱动的结构预测通过揭示其与Miz-1的相互作用来确定致癌MYC蛋白的新治疗点. 这一突破使得开发新型药物能够针对内在失序的蛋白相互作用.

科学领域:

在瘤学瘤学.
结构生物学结构生物学
药物发现药物发现药物发现

背景情况:

内在无序蛋白质 (IDP) 缺乏明确的结构,这对治疗向提出了挑战.
MYC是一种致癌转录因子,具有至关重要的,但尚未探索的蛋白质-蛋白质相互作用.

研究的目的:

通过基于AI的结构预测来研究MYC/Miz-1蛋白-蛋白相互作用.
为治疗干预设计和验证针对MYC/Miz-1和MYC/MAX接口的型模仿药.

主要方法:

使用AlphaFold-Multimer来预测MYC/Miz-1复合体的结构.
设计和合成了针对已识别的相互作用部位的合皮相仿药.
采用氨酸扫描来绘制结合热点并优化药物变体.
在实验室中评估了MYC/MAX和MAX/DNA复合体形成的破坏.

主要成果:

AlphaFold-Multimer预测Miz-1与MYC结合在一个重叠MYC/MAX二分化域的位置.
开发了类仿制药,其中Mizmetic 2显示了亚微分子功效.
优化的变种有效地破坏了MYC/MAX复合体的形成和MYC/DNA结合.
确定了MYC上的关键绑定热点,用于未来的药物开发.

结论:

基于人工智能的结构预测可以揭示内在无序蛋白质的可药物接口.
针对MYC/Miz-1相互作用为MYC驱动的癌症提供了一个有前途的治疗策略.
这项概念验证研究为开发针对具有挑战性的瘤标的药物开辟了新的途径.

关键词:

在AlphaFold-Multimer中使用.马克斯马克斯马克斯马克斯我的世界 MYC 与MYC相互作用的指1

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