多重组设计和发现可编程蛋白质组编辑的近距离手柄
Chase C Suiter1,2,3, Green Ahn4,5,6, Melodie Chiu2
1Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA.
bioRxiv : the preprint server for biology
|November 24, 2025
概括
研究人员开发了一种使用蛋白质设计和选的新方法,以发现用于精确编辑蛋白质组的新型"效应器手柄",从而实现向蛋白质降解或稳定. 这加速了控制细胞内蛋白质水平的工具的开发.
科学领域:
- 分子生物学分子生物学
- 合成生物学 合成生物学
- 生物技术是生物技术.
背景情况:
- 基因组编辑工具是先进的,但蛋白质组操纵缺乏类似的灵活性和特异性.
- 像PROTACs这样的双功能分子显示出蛋白质组编辑的希望,但受到良好的特征效应器手柄稀缺的限制.
- 在发现针对蛋白质降解,稳定或重新定位的新手柄方面存在差距.
研究的目的:
- 通过开发一个框架来解决蛋白质组编辑的局限性,以发现新的效应器手柄.
- 通过使用de novo蛋白质设计和多重选加速发现用于细胞内蛋白质降解,稳定和重新定位的手柄.
主要方法:
- 使用 de novo 蛋白质设计与多重选框架 (LABEL-seq) 相结合,以发现效应器手柄.
- 选了9,715个新设计的候选效应因子手柄,以检测它们在无素-蛋白酶系统 (UPS) 或自途径中招募标蛋白的能力.
- 使用直角测定验证的结果,以确认细胞内蛋白质丰度的变化.
主要成果:
- 发现了数百个新设计的效应器手柄,包括277个用于降解和204个用于稳定记者蛋白.
- 确定了UPS (194) 和自 (287) 途径的有效手柄,证明了蛋白质组编辑的互补路径.
- 通过降低MCL1水平,向内源性标证明了泛化,并通过有针对性的重新定位显示了线粒体的功能干扰.
结论:
- 建立了一个可扩展,低成本的平台,将深度学习引导的蛋白质设计与功能性细胞读取联系起来,用于蛋白质组编辑.
- 产生了多种多样的效应器手柄来控制蛋白质的丰富性和定位.
- 为可编程蛋白质组编辑的一般框架铺平了道路.
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