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.

项目概要 随着结构生物学和超级计算技术的最新进展，全原子分子动力学 （MD）模拟技术作为蛋白质结构研究的重要工具已获得发展势头 然而，暴力 MD 无法充分采样最相关的功能。 生物分子过程，例如大规模蛋白质构象变化，已经有多种方法。 过去三十年来发展起来的目的是解决阻碍MD实际使用的“时间尺度差距” 世界应用。自由能计算方法、增强采样技术和寻路。 算法是专门描述该项目中许多方法的总括术语的示例。 旨在采用、定制和微调最先进的增强采样和寻路 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标是 开发并采用稳健且实用的采样和分析协议来研究功能相关性 从成纤维细胞生长因子到冠状病毒刺突蛋白的各种蛋白质的构象变化。 所提出的方法框架特别利用了（1）稳健的理论形式主义 (2)系统特定增强 可针对当前具体问题进行调整的采样方案；以及 (3) 综合性和协同性； 实验（特别是 smFRET）和计算（特别是 MD）技术的方法。 建议在此研究的系统包括质子偶联寡肽转运蛋白、流感病毒 血凝素、ATP 结合转运蛋白、冠状病毒刺突蛋白、大分子机械敏感通道 电导、膜插入酶 YidC、血清素转运蛋白和成纤维细胞生长因子 (FGF) 蛋白。 所有这些项目的共同主题是涉及的大规模构象变化 这些蛋白质的功能。在该项目中成功使用所提出的方法将允许 在分子水平上表征这些构象变化，并为 最先进的增强采样技术在现实世界生物学研究中的常规应用 问题。