报告题目：Imaging nonequilibrium dynamics of bio-soft matter by 4D cryo-EM

报 告 人：毛有东 教授（北京大学物理学院）

报告时间：2023年10月18日（周三）下午2:00

报告地点：新葡萄88805官网新楼五楼多功能厅

报告摘要：

The cellular functions are executed by biological macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving the conformational continuum of important bio-soft matter at the atomic level is essential to understanding their functional mechanisms. In this talk, we will discuss on our recent cutting-edge studies at the interface between artificial intelligence and bio-soft matter physics. We recently developed a deep manifold learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy (cryo-EM) reconstructions that approximately visualize the conformational space of biomolecular machinery of interest. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of pseudo-energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. In blind assessments using simulated heterogeneous datasets, AlphaCryo4D achieved 3D classification accuracy three times those of alternative methods and reconstructed continuous conformational changes of a 130-kDa protein at sub-3 Å resolution. By applying this approach to analyze several experimental datasets of the proteasome, ribosome and spliceosome, we demonstrate its potential generality in exploring hidden conformational space or transient states of macromolecular complexes that remain hitherto invisible. Integration of this approach with time-resolved cryo-EM allows visualization of hitherto inaccessible functional dynamics in a nonequilibrium regime at the atomic level, thus potentially enabling therapeutic discovery against highly dynamic biomolecular targets.

报告人简介：

毛有东，北京大学物理学院博雅特聘终身教授，博士生导师，北大清华联合生命科学中心、北大定量生物学中心、国家生物医学成像科学中心资深PI，北大深圳研究生院智慧科学（AI for Science）研究院（筹）副院长，多模态跨尺度生物医学成像国家基础设施装置负责人，国家重点研发计划项目负责人。1999在新葡萄88805官网物理学院获得学士学位，2005年获得北京大学物理学院理学博士学位，2007年赴美国哈佛大学医学院深造，历任博士后、Instructor、研究组长PI和访问教授。2015年回国工作前曾任哈佛医学院Dana-Farber 癌症研究所Intel并行计算结构生物学中心主任。他的研究团队发展了基于人工智能的高精度时间分辨冷冻电镜分析和动力学重建新方法，在国际上首次实现非平衡态复合超分子机器连续构象变化的原子分辨四维重建，利用这些新方法系统研究了人源蛋白酶体全酶功能动力学，揭示了其底物降解及其环状马达的普适性工作原理、复合动力学调控和重编程机制，发现了分子伴侣p28对蛋白酶体自组装的动态构象选择机制，解析了炎症小体的高分辨结构、相变成核和认证活化的动态结构机制，开发了具有重大潜在临床价值的多种小分子抑制剂。发表论文60余篇，其中通讯作者代表性成果有10多篇部发表在《自然》和《科学》及CNS子刊。获授权美国、国际和中国发明专利9项。

代表性论著：

1. Zhang S, Zou S, Yin D, Zhao L, Finley D, Wu Z, Mao Y*. USP14-regulated allostery of the human proteasome by time-resolved cryo-EM. Nature 2022; 605: 567-574.
https://doi.org/10.1038/s41586-022-04671-8

2. Wu Z, Chen E, Zhang S, Liu C, Yin CC, Ma Y, Mao Y*. Visualizing conformational space of functional biomolecular complexes by deep manifold learning. Int. J. Mol. Sci. 2022; 23: 8872. https://doi.org/10.3390/ijms23168872

3. Dong Y, Zhang S, Wu Z, Li X, Wang W, Zhu Y, Stoilova-McPhie S, Lu Y, Finley D, Mao Y*. Cryo-EM structures and dynamics of substrate-engaged human 26S proteasome. Nature 2019; 565: 49-55. https://doi.org/10.1038/s41586-018-0736-4

4. Sharif H, Wang L, Wang WL, Magupalli VG, Andreeva L, Qiao Q, Hauenstein AV, Wu Z, Nunez G, Mao Y*, Wu H*. Structural mechanism for NEK7-licensed NLRP3 inflammasome activation. Nature 2019; 570: 338-343. https://doi.org/10.1038/s41586-019-1295-z

5. Zhang L^#, Chen S^#, Ruan J, Wu J, Tong AB, Yin Q, Li Y, David L, Lu A, Wang WL, Marks C, Ouyang Q, Zhang X, Mao Y*, Wu H*. Cryo-EM structure of the activated NAIP2-NLRC4 inflammasome reveals nucleated polymerization. Science 2015; 350: 404-409. https://doi.org/10.1126/science.aac5789

邀 请 方：物理学院130周年院庆筹备组