New Algorithms for Cryogenic Electron Microscopy

低温电子显微镜的新算法

• 批准号: 10543569
• 负责人: Hemant D Tagare
• 金额: $ 41.88万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10543569
• 关键词: Address; Affect; Algorithms; Biological; Cryoelectron Microscopy; Data; Face; Instruction; Mathematics; Methodology; Methods; Molecular Conformation; Molecular Weight; National Institute of General Medical Sciences; Noise; Proteins; Research; Resolution; Structure; Work; detector; macromolecule; next generation; particle; protein structure; reconstruction; statistics; structural biology; success; three dimensional structure

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.

项目摘要/摘要 低温电子显微镜（Cryo-EM）是一种新的且快速发展的结构生物学方法。它是 成功是由于直接检测器摄像机和新算法的进步所致。该建议旨在发展 下一代算法的重点是重建小分子量蛋白的结构， 具有多种构象状态的蛋白质，并开发算法来解释为什么出现分辨率限制 在Cryo-Em中。 拟议的研究旨在解决上述问题中的重要瓶颈。首先，我们试图找到 有用的统计数据可检测所谓的“爱因斯坦 - 诺伊斯”问题。这个问题影响重建 小分子量蛋白质的蛋白质，可产生灾难性的重建。我们建议调查这一点 现象理论上和计算，以便可靠地检测到它。第二，我们试图发展 用于重建异质蛋白多种构象状态的下一代算法。 特别是，我们寻求稳定并提供高分辨率重建的算法 以生物学上有意义的方式组织。最后，我们试图探索Cryo-EM算法中的新方向。 我们建议开发一种方法，该方法解释了导致冷冻EM中解决方案限制的方法 重建。当前方法可以估计重建的分辨率，而无需提供任何理由 出于其原因。新方法将使用户能够更有效地使用数据和算法设置。 拟议的研究基于P.I.以前的裸体支持在单个粒子重建中的工作 冷冻em。