AI-based structure prediction empowers integrative structural analysis of human nuclear pores
AI-based structure prediction empowers integrative structural analysis of human nuclear pores
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DOI：
10.1126/science.abm9506
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发表时间：
2022-06-10
期刊：
影响因子：
56.9
通讯作者：
Beck, Martin
中科院分区：
文献类型：
--
作者：
Mosalaganti, Shyamal;Obarska-Kosinska, Agnieszka;Beck, Martin
核孔复合物（NPC）介导核细胞质运输。它们复杂的 120 兆道尔顿架构仍未完全被了解。在这里，我们报告了一个 70 兆道尔顿的人类 NPC 支架模型，具有明确的膜和多种构象状态。我们将基于人工智能 (AI) 的结构预测与原位和细胞冷冻电子断层扫描以及集成建模相结合。我们表明，连接核孔蛋白在子复合物内部和子复合物之间空间组织支架，以建立高阶结构。微秒长的分子动力学模拟表明，支架不需要稳定内外核膜融合，而是加宽中心孔。我们的工作举例说明了基于人工智能的建模如何与原位结构生物学相结合，以了解跨空间组织层面的亚细胞结构。
Nuclear pore complexes (NPCs) mediate nucleocytoplasmic transport. Their intricate 120-megadalton architecture remains incompletely understood. Here, we report a 70-megadalton model of the human NPC scaffold with explicit membrane and in multiple conformational states. We combined artificial intelligence (AI)-based structure prediction with in situ and in cellulo cryo-electron tomography and integrative modeling. We show that linker nucleoporins spatially organize the scaffold within and across subcomplexes to establish the higher-order structure. Microsecond-long molecular dynamics simulations suggest that the scaffold is not required to stabilize the inner and outer nuclear membrane fusion but rather widens the central pore. Our work exemplifies how AI-based modeling can be integrated with in situ structural biology to understand subcellular architecture across spatial organization levels.