Cost Effective, Synergistic Macromolecular Structure Determination, Analysis & Simulation

成本有效、协同的大分子结构测定、分析

• 批准号: 10016355
• 负责人: MICHAEL LEVITT
• 金额: $ 56.79万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10016355
• 关键词: Amino Acids; Area; Biology; Cell physiology; Collaborations; Community Services; Complex; Computational Biology; Cryoelectron Microscopy; DNA Polymerase II; DNA Structure; Data; Development; Eukaryota; Freedom; Heart; Hybrids; Intervention; Macromolecular Complexes; Manuals; Maps; Mentors; Methods; Modernization; Molecular Conformation; Molecular Machines; Molecular Structure; Motion; Movement; Pathway Analysis; Pathway interactions; Principal Investigator; RNA; RNA Polymerase II; Reaction; Research; Ribosomes; Running; Science; Scientist; Side; Structure; System; Testing; Time; Work; career; chaperonin; computer code; computer framework; cost effective; electron density; experimental study; fascinate; innovation; interest; molecular dynamics; novel strategies; outreach; protein structure; simulation; software development; tool

Project Summary (30 lines) Entitled “Cost Effective, Synergistic Macromolecular Structure Determination, Analysis & Simulation”, this proposal involves systems at the heart of biology: CCT Eukaryote Chaperonin, RNA Polymerase II, and the Ribosome, all of which our colleagues are studying experimentally. We will develop unbiased methods to solve structures with less data. Interested in how molecular machines move as they function, we map out their state-space using multi-scale hybrid methods. All our methods and curated data will be disseminated freely. This project is timely as these macromolecular machines carry out key cellular functions. The tools we develop for structure determination, analysis and simulation will aid others in advancing biomedicine. Michael Levitt, the Principal Investigator has a long career of independent scientific research that started in 1967 when he was one of the first to work in computational biology. His early work set up the conceptual, theoretical and computational framework for protein and DNA structure refinement, structure analysis and macromolecular simulations. He makes computer codes available and continues hands-on software development. He has been productive, scientifically rigorous and impactful for half a century. Particularly innovative is his work for the past five years leading to original methods to both solve biomedically significant structures and simulate functional motion. These areas are continued here by a PI committed to mentoring young scientists as well as engaging in sustained research-community service and public outreach. 1. Develop Novel Approaches to Determination and Refinement of Macromolecular Complexes. The first sub-area will deal with determining the identity of amino acid side chains. The second sub-area will involve a new approach to automatic structure determination requiring no manual intervention. Both methods will be adapted to cryo-EM electron density maps. 2. Develop Novel Approaches to Pathway Analysis of Structures. The first sub-area will deal with structure curation. Essential for ribosome work, it will be increasingly useful as structures accumulate for other macromolecular complexes. The second sub-area focuses on methods to find reaction pathways from multiple structures of such complexes. The third sub-area will test and develop new methods for structure morphing with few degrees of freedom. The forth sub-area will use Molten Zone molecular dynamics to study functional movement. 3. Determine the State-Space of Functional Motion in Chaperonin, RNA Pol II, and the Ribosome. We will identify key states, morph between these states to find reaction paths and run molecular dynamics. Studying these biomedically significant systems in collaboration with experimental colleagues will reveal fascinating details of biology in action. This work will elucidate the relationship between structure and function in large macromolecular machines, a keystone of modern biomedical science.

项目概要（30行） 题为“成本有效、协同的大分子结构测定、分析和模拟”， 提案涉及生物学核心的系统：CCT 真核生物伴侣蛋白、RNA 聚合酶 II 和 核糖体，我们的同事正在实验研究所有这些，我们将开发公正的方法。 为了用更少的数据解决结构问题，我们对分子机器如何运动感兴趣，绘制了地图。 他们的状态空间使用多尺度混合方法。我们所有的方法和整理的数据都将被传播。 这个项目是及时的，因为这些大分子机器执行关键的细胞功能。 我们开发的结构确定、分析和模拟将帮助其他人推进生物医学。 首席研究员迈克尔·莱维特 (Michael Levitt) 拥有长期的独立科学研究生涯，始于 1967 年，他是最早从事计算生物学工作的人之一，他的早期工作确立了这一概念： 蛋白质和 DNA 结构细化、结构分析和分析的理论和计算框架 他提供了计算机代码并继续实践软件。 半个世纪以来，他一直富有成效、科学严谨且具有影响力。 创新是他过去五年的工作，带来了解决生物医学重大问题的原创方法 结构和模拟功能运动在这里由致力于指导的 PI 继续。 年轻科学家以及参与持续的研究社区服务和公共宣传。 1. 开发大分子复合物测定和精制的新方法。 第一个子区域将处理确定氨基酸侧链的身份，第二个子区域将处理氨基酸侧链的身份。 涉及一种无需人工干预的自动结构确定的新方法。 方法将适用于冷冻电镜电子密度图。 2. 开发结构路径分析的新方法 第一个子区域将涉及。 结构管理对于核糖体工作至关重要，随着结构的积累，它将变得越来越有用。 其他大分子复合物的第二个子区域重点关注寻找反应途径的方法。 第三个子区域将测试和开发此类复合体的多种结构的新方法。 第四个子区域将使用 Molten Zone 分子进行结构变形。 动力学来研究功能运动。 3. 确定伴侣蛋白、RNA Pol II 和核糖体 We 中功能运动的状态空间。 将识别关键状态，在这些状态之间变形以找到反应路径并运行分子动力学。 与实验同事合作研究这些具有生物医学意义的系统将揭示 这项工作将阐明结构与生物学之间的关系。 大型高分子机器中的功能，是现代生物医学的基石。