Physics-based characterization of functionally relevant protein conformational dynamics

功能相关蛋白质构象动力学的基于物理的表征

• 批准号: 10501664
• 负责人: Mahmoud Moradi
• 金额: $ 22.16万
• 依托单位: UNIVERSITY OF ARKANSAS AT FAYETTEVILLE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10501664
• 关键词: Address; Algorithms; Binding; Biological; Computing Methodologies; Coronavirus spike protein; Coupled; Fibroblast Growth Factor; Free Energy; Growth Factor; Hand; Human; Influenza Hemagglutinin; Membrane; Methodology; Methods; Molecular; Molecular Conformation; Oligopeptides; Physics; Plant Roots; Play; Process; Protein Conformation; Proteins; Protocols documentation; Protons; Role; Sampling; Statistical Mechanics; Supercomputing; System; Techniques; Technology; base; differential geometry; molecular dynamics; protein function; real world application; serotonin transporter; single-molecule FRET; structural biology; tool

PROJECT SUMMARY With recent advances in structural biology and supercomputing technology, all-atom molecular dynamics (MD) simulation technique has gained momentum as a prominent tool for the study of protein structural dynamics. Brute-force MD, however, is not capable of adequately sampling most functionally relevant biomolecular processes such as large-scale protein conformational changes. Various approaches have been developed over the last three decades to address the “timescale gap” that hinders the use of MD in real- world applications. Free energy calculation methods, enhanced sampling techniques, and path-finding algorithms are examples of umbrella terms that describe many of these methods. This project specifically aims at employing, tailoring, and fine-tuning state-of-the-art enhanced sampling and path-finding algorithms to address important biological and biomedical questions. The overall aim of this project is to develop and employ robust and practical sampling and analysis protocols to study functionally relevant conformational changes of various proteins from fibroblast growth factor to coronavirus spike protein. Our proposed methodological framework specifically takes advantage of (1) robust theoretical formalisms rooted in nonequilibrium statistical mechanics and differential geometry; (2) system-specific enhanced sampling protocols that are tunable for the specific problem at hand; and (3) and integrative and synergistic approach to experimental (specifically smFRET) and computational (specifically MD) techniques. Some of the systems proposed to be studied here include proton-coupled oligopeptide transporters, influenza hemagglutinin, ATP-binding transporters, coronavirus spike proteins, mechanosensitive channel of large conductance, membrane insertase YidC, serotonin transporter, and fibroblast growth factor (FGF) protein. The common theme in all of these projects is the large-scale conformational changes involved in the function of these proteins. The successful use of the methodology proposed in this project will allow the characterization of these conformational changes at the molecular level and pave the groundwork for the routine application of state-of-the-art enhanced sampling techniques in the study of real world biological problems.

项目摘要 随着结构生物学和超级计算技术的最新进展，全部原子分子动力学 （MD）模拟技术已获得动量，作为研究蛋白质结构的重要工具 动力学。但是，Brute-Force MD无法充分采样大多数功能相关的 生物分子过程，例如大规模蛋白质构象变化。各种方法已经 在过去的三十年中，开发了用于解决“时间尺度差距”，该差距阻碍了MD在现实中的使用 世界应用。自由能计算方法，增强的采样技术和路径找到 算法是描述其中许多方法的伞术语的示例。这个项目是专门的 旨在采用，裁缝和微调的最先进的采样和探路 解决重要的生物学和生物医学问题的算法。该项目的总体目的是 开发和采用健壮和实用的抽样和分析协议来研究功能相关 从成纤维细胞生长因子到冠状病毒峰值蛋白的各种蛋白质的构象变化。我们的 提出的方法学框架专门利用（1）强大的理论形式主义 植根于非平衡统计力学和差异几何形状； （2）特定于系统的增强 对当前特定问题可调整的采样协议； （3）以及综合和协同作用 实验（特别是SMFRET）和计算（特别是MD）技术的方法。一些 在此提议研究的系统中包括质子偶联的寡肽转运蛋白，影响力 血凝素，ATP结合转运蛋白，冠状病毒尖峰蛋白，大型机械敏感通道 电导，膜插入酶Yidc，5-羟色胺转运蛋白和成纤维细胞生长因子（FGF）蛋白。 所有这些项目中的共同主题是涉及的大规模构象变化 这些蛋白质的功能。该项目中提出的方法的成功使用将允许 这些构象变化在分子水平上的表征，并为 在现实世界生物学研究中，常规应用最先进的增强抽样技术 问题。