Laws of mechanics and function in proteins as evolved molecular machines

蛋白质作为进化分子机器的力学定律和功能

• 批准号: 10022123
• 负责人: Lauren McGough
• 金额: $ 6.53万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10022123
• 关键词: Allosteric Site; Biological; Biological Models; Biological Process; Charge; Communities; Comparative Study; Crystallization; Crystallography; Data; Data Analyses; Dimensions; Disease; Environment; Evolution; Exhibits; Family; Freedom; Heterogeneity; Human; Individual; Laws; Length; Life; Ligand Binding; Light; Measurement; Measures; Mechanics; Methods; Microscopic; Modeling; Molecular; Molecular Machines; Monte Carlo Method; Motion; Mutation; Pattern; Performance; Positioning Attribute; Process; Property; Protein Dynamics; Protein Engineering; Proteins; Reaction; Records; Research; Resolution; Route; Site; Source; Structure; Surface; System; Techniques; Temperature; Testing; Theoretical Studies; Time; Work; X ray diffraction analysis; X-Ray Crystallography; chemical reaction; comparative; design; electric field; electron density; engineering design; evidence base; expectation; experimental study; flexibility; high dimensionality; improved; innovation; macromolecule; man; mathematical analysis; mechanical force; member; molecular dynamics; mutant; novel; predictive test; pressure; programs; prospective; protein function; protein structure; response; simulation; theories; tool

PROJECT SUMMARY Proteins are the "machines" that carry out the chemical reactions necessary for life. Unlike man-made machines, proteins exhibit a unique combination of features: high performance with respect to specific biological functions, and adaptability to changes in their environment. The coincidence of these two properties suggests that there exist yet-unknown design principles which govern evolved machines. However, despite the clear implications of this observation for our understanding of evolution, proteins, and engineering, these design principles remain elusive due to the high-dimensionality of internal protein atomic motions and wide range of length- and time-scales associated with the problem. At present, molecular dynamics simulations have been the most useful tools for shedding light on the internal dynamics of proteins, but given the challenge in measuring the time-dependent internal motions a protein undergoing some biological process, these simulations are often not confirmable by experimental data. New experiments and analysis methods in our lab are able to measure internal motions within proteins at Angstrom-resolution. This provides an opportunity: I will carry out substantial experimentally-verified molecular dynamics simulations which model the new experiments. By carrying out these simulations using several different force fields and comparing a variety of quantities to their experimental values, I will construct new experimentally-motivated molecular dynamics “best practices” such that simulations and experiment imply consistent properties of the given protein. Using these “optimized” molecular dynamics methods along with data analysis methods such as dimensional reduction, I will study protein dynamics in multiple contexts, including electric-field stimulated X-ray crystallography (EFX), a novel technique by which an electric field is applied to a protein crystal and the resulting structure is measured using X-ray crystallography, and room-temperature X-ray crystallography (RTX), a new way of determining thermal ensembles of protein configurations at room temperature using static crystallography data. These will enable me to reduce the measurements of atomic-scale motions of thousands of individual atoms to a description of coordinated motions on different scales with the expectation of revealing a small number of mechanical mechanisms dictating protein function and allostery. This mathematical analysis not only opens up new experimental, computational and conceptual methods for understanding protein function from microscopic structural information; its improved, evidence-based simulation methods can be used for predicting collective motions when crystallography experiments are nonexistent or inaccessible. Overall, this research will develop new quantitative tools for studying the connection between protein mechanics and function, and implement these tools to extract a low-dimensional, ordered description of this seemingly high-dimensional, disordered phenomenon.

项目摘要 蛋白质是进行生命所必需的化学反应的“机器”。不像人造的 机器，蛋白质表现出独特的组合功能：高性能方面的具体 生物学功能和对环境变化的适应性。这两种性质的巧合 这表明存在着未知的设计原则，这些原则支配着进化的机器。但尽管 这一观察结果对我们理解进化、蛋白质和工程学有着明确的意义， 由于蛋白质内部原子运动的高维性， 与问题相关的长度和时间范围。目前，分子动力学模拟 是揭示蛋白质内部动力学的最有用的工具，但鉴于挑战 在测量蛋白质在经历某些生物过程时依赖于时间的内部运动时， 模拟通常不能由实验数据证实。本实验室的新实验和分析方法 能够以埃分辨率测量蛋白质内部的运动。这提供了一个机会：我将 进行大量的实验验证的分子动力学模拟， 实验通过使用几种不同的力场进行这些模拟，并比较各种 量的实验值，我将构建新的实验动机的分子动力学“最好的” 实践”，使得模拟和实验暗示给定蛋白质的一致性质。使用这些 “优化的”分子动力学方法沿着数据分析方法，如降维， 将在多种背景下研究蛋白质动力学，包括电场刺激X射线晶体学（EFX）， 一种新的技术，通过该技术将电场施加到蛋白质晶体上， 测量使用X射线晶体学，和室温X射线晶体学（RTX），一种新的方法， 使用静态晶体学数据确定室温下蛋白质构型的热系综。 这些将使我能够减少对数千个单个原子的原子尺度运动的测量， 对不同尺度上的协调运动的描述，期望揭示少量的 决定蛋白质功能和变构的机械机制。这种数学分析不仅揭示了 从微观角度理解蛋白质功能的新实验、计算和概念方法 结构信息;其改进的，基于证据的模拟方法可用于预测集体 当晶体学实验不存在或无法访问时，总的来说，这项研究将发展 研究蛋白质力学和功能之间联系的新定量工具，并实现 这些工具来提取一个低维的，有序的描述，这个看似高维的，无序的， 现象