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发展，全原子分子动力学 (MD)模拟技术作为研究蛋白质结构的重要工具， 动力学然而，蛮力MD不能充分采样大多数功能相关的 生物分子过程，如大规模的蛋白质构象变化。了各种方法 在过去的三十年里，为了解决阻碍MD在真实的中使用的“时间尺度差距”， 世界应用。自由能计算方法，增强的采样技术和路径查找 算法是描述这些方法中的许多方法的总括术语的示例。这个项目具体来说 旨在采用、裁剪和微调最先进的增强采样和路径查找 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 开发和采用强大和实用的采样和分析协议，以研究功能相关的 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。我们 建议的方法框架特别利用（1）强大的理论形式主义 植根于非平衡统计力学和微分几何;（2）系统特定增强 采样协议是可调的具体问题在手;和（3）和综合和协同 实验（特别是smFRET）和计算（特别是MD）技术的方法。一些 本文拟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，大细胞机械敏感通道 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。 所有这些项目的共同主题是， 这些蛋白质的功能。成功使用本项目中提出的方法将使 在分子水平上表征这些构象变化，并为 在真实的世界生物研究中常规应用最先进的增强取样技术 问题