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Updated: Sep 20, 2025

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基于人工智能的结构预测使人类核孔的整合性结构分析成为可能
Shyamal Mosalaganti1,2,3, Agnieszka Obarska-Kosinska1,4, Marc Siggel4,5,6
1Department of Molecular Sociology, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany.
概括
这项研究介绍了人类核孔综合体 (NPC) 支架的详细原子分辨率模型. 使用人工智能和冷电磁, 它揭示了NPC动态和膜相互作用, 推动我们对核细胞质运输的理解.
科学领域:
- 结构生物学
- 分子细胞生物学
- 生物物理
背景情况:
- 细胞核受到核外的保护,通过核孔复合体 (NPC) 进行核细胞质运输.
- 人类NPC是由核波林 (NUP) 组成的大型蛋白质复合体 (~120 MDa),分为支架和内在无序类型.
- NPC 架构是动态的,因应核外的紧张而发生形态变化,这对高分辨率的结构确定构成了挑战.
研究的目的:
- 在原子分辨率上阐明人类NPC架构, 提高对其功能和动态的理解.
- 克服以前的结构模型中的挑战,包括人类NUP的有限覆盖范围,难以表征无序链接器,以及NPC的膜协会.
主要方法:
- 基于人工智能 (AI) 的预测,以生成人类NUP和子综合体的结构模型.
- 用冷电子断层扫描 (冷ET) 来获得高分辨率的NPC形状图 (收缩和扩展).
- 整合模型将AI预测的NUP结构融入冷ET图中,包括链接器NUP和膜相关的NUP.
- 模拟分子动力学以分析NPC支架在膜环境中的行为.
主要成果:
- 为人类NUP生成了广泛的精确结构模型,涵盖了以前未被描述的领域和接口.
- 在狭窄和扩展状态下获得了人类NPC的高分辨率冷ET图,使NUP结构能够详细适应.
- 开发了一个全面的建筑模型,使NPC支架的结构覆盖率翻倍,并揭示了无序NUP的精确位.
- 模拟显示NPC支架可以防止膜融合孔的过度收缩.
结论:
- 已经建立了一个70MDa的原子分辨模型,覆盖了90%的人类NPC支架.
- 该模型捕捉了NPC的形状变化,并准确地确定了内在无序的NUP的位.
- 人工智能驱动的结构预测显著加速了复杂的亚细胞结构在原子分辨率的阐明.
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