New Algorithms for Cryogenic Electron Microscopy

项目总结/摘要 低温电子显微镜（Cryo-EM）是一种快速发展的结构生物学新方法。其 成功是由于直接探测器照相机和新算法的进步。该提案旨在发展 下一代算法集中于重构小分子量蛋白质的结构， 具有多种构象状态的蛋白质，并开发解释分辨率限制发生原因的算法 在冷冻电镜中 拟议的研究旨在解决上述问题中的重要瓶颈。首先，我们要找到 有用的统计数据来检测所谓的“噪声中的爱因斯坦”问题。这个问题影响了重建 小分子量的蛋白质，造成灾难性的重建。我们建议对此进行调查 理论上和计算上的现象，使其能够可靠地检测。第二，我们寻求发展 下一代的算法用于重建异质蛋白质的多个构象状态。 特别是，我们寻求算法是稳定的，并给出高分辨率的重建，可以是 以生物学意义的方式组织起来。最后，我们试图探索一个新的方向，在冷冻EM算法。 我们建议开发一种方法，解释是什么原因导致在冷冻EM分辨率限制 重建目前的方法可以估计重建的分辨率，而不提供任何理由 为了它的事业。新方法将使用户能够更有效地使用数据和算法设置。 这项研究建立在P.I.以前的NIGMS支持单粒子重建工作， 冷冻EM

Project Summary/Abstract Cryogenic electron-microscopy (Cryo-EM) is a new and rapidly evolving methodology for structural biology. Its success is due to advances in Direct Detector Cameras and new algorithms. This proposal seeks to develop the next generation of algorithms focused on reconstructing the structure of small molecular weight proteins, proteins with multiple conformational states, and developing algorithms that explain why resolution limits occur in Cryo-EM. The proposed research seeks to address important bottlenecks in the above problems. First, we seek to find useful statistics to detect the so-called “Einstein-from-noise” problem. This problem affects the reconstruction of small molecular weight proteins, giving catastrophically bad reconstructions. We propose to investigate this phenomenon theoretically and computationally, so that it can be detected reliably. Second, we seek to develop the next generation of algorithms for reconstructing multiple conformational states of a heterogeneous protein. In particular, we seek algorithms which are stable and which give high resolution reconstructions that can be organized in biologically meaningful ways. Finally, we seek to explore a new direction in Cryo-EM algorithms. We propose to develop a methodology which explains what causes resolution limits in a Cryo-EM reconstruction. Current methods can estimate the resolution of a reconstruction without providing any rationale for its cause. The new methodology will enable users to use data and algorithm settings more effectively. The proposed research builds on the P.I. previous NIGMS supported work on single particle reconstruction in Cryo-EM.