Determination of structure, dynamics and energetics of enzyme reactions

酶反应的结构、动力学和能量学测定

• 批准号: 10456219
• 负责人: OLAF G WIEST
• 金额: $ 32.15万
• 依托单位: UNIVERSITY OF NOTRE DAME
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10456219
• 关键词: Active Sites; Anti-Bacterial Agents; Biochemistry; Biological; Biology; Biophysics; Catalysis; Chemicals; Cholesterol; Code; Collaborations; Combined Modality Therapy; Communities; Complex; Computational Biology; Computing Methodologies; Couples; Coupling; Crystallization; Crystallography; Data; Developed Countries; Development; Disease; Drug Targeting; Enzymatic Biochemistry; Enzymes; Equilibrium; Free Energy; Freezing; Goals; Grant; Health; Human; Hydroxymethylglutaryl-CoA reductase; Knowledge; Life; Link; Machine Learning; Maps; Methodology; Methods; Modeling; Molecular; Molecular Conformation; Movement; Mutagenesis; Nature; Oxidoreductase; Pathway interactions; Pharmaceutical Preparations; Positioning Attribute; Process; Protein Dynamics; Proteins; Pseudomonas; Public Health; Reaction; Research Personnel; Resolution; Roentgen Rays; Role; Running; Science; Structure; System; Techniques; Time; Validation; Work; base; biophysical chemistry; cofactor; computer studies; design; electron density; enzyme mechanism; experience; experimental study; improved; innovation; machine learning method; millisecond; molecular dynamics; molecular mechanics; molecular scale; movie; new therapeutic target; particle; protein structure; quantum; simulation; structural biology; synthetic biology; theories; tool

Project Summary Understanding enzyme mechanisms is of paramount importance from both the basic biophysics perspective of understanding life processes and the role of enzymes in diseases. To achieve a detailed understanding of enzyme catalysis, the effects of protein structure and dynamics on the reaction energetics need to be elucidated. We propose a combined computational and experimental approach that combines the synthetic, computational and structural biology expertise of a team of investigators that has been working together for >15 years to create a “molecular movie” where the position, movement and energy of every atom in the system followed over the entire reaction pathway. The proposal exploits the emerging convergence of timescales accessible by molecular simulation using GPUs and time resolved structural biology. Specific Aim 1 describes the simulation of the complete reaction pathway of Pseudomonas mevalonii (Pm) HMGCoA Reductase (HMGR) and will use transition state force fields (TSFFs) generated by the quantum guided molecular mechanics method to allow the µsec MD simulations of the chemical steps. TSFFs not only circumvent the well-known boundary problem of QM/MM, but are also 102-104 times faster. This allows a realistic modeling of the coupling of µsec dynamics and catalysis that was demonstrated in the last grant period to be essential for understanding the reaction. Together with accelerated MD simulations of the conformational changes involved in the reaction using standard force fields, these computational studies cover the fsec to µsec timescale. In Specific Aim 2, the computational results will be merged with the results of a three-tiered approach to obtain structural snapshots with progressively increasing time resolution: (i) “Frozen” intermediates that map out the overall pathway on long timescales, (ii) time resolved Laue crystallography using pH jump initiation on the msec timescale and (iii) use of photocaged substrates to allow time resolved Laue experiments on the µsec timescale. This approach will be applied to the study of HMGR, an enzyme of high biophysical and biomedical significance that has a complex reaction mechanism involving three chemical steps, six large-scale conformational changes and two cofactor exchange steps. The project is highly innovative because it (i) uses a combination of MD simulations using TSFFs and time resolved crystallography to span timescales of at least 12 orders of magnitude, (ii) iteratively couples the Markov State analysis of long timescale trajectories to the Singular Value Decomposition used to analyze time resolved crystallography data, thus providing new tools to generate and experimentally validate trial structures (iii) applies global optimization and machine learning techniques to allow the automated fitting of TSFFs for proteins, which will enhance the application of this powerful method to other proteins and (iv) provides new photocaged substrates for the study of enzyme mechanisms to the chemical biology community. All tool compounds, methods and codes developed in this project will be made available to the scientific community.

项目摘要 从两个基本的生物物理学角度来看，了解酶机制至关重要 了解生命过程和酶在疾病中的作用。为了详细了解 需要阐明酶催化，蛋白质结构和动力学对反应能量的影响。 我们提出了一种结合合成，计算的组合计算方法和实验方法 以及一个研究人员团队的结构生物学专业知识，他们已经合作了15年以创建 一部“分子电影”，系统中每个原子的位置，运动和能量都跟随 该提案利用了分子可访问的时标的新兴收敛性 使用GPU和时间解决结构生物学的模拟。特定目的1描述了模拟的模拟 假单胞菌Mevalonii（PM）HMGCOA还原酶（HMGR）的完整反应途径，并将使用 量子引导分子力学方法产生的过渡状态力场（TSFF）允许 化学步骤的µSEC MD模拟。 TSFF不仅规避了众所周知的边界问题 QM/mm，但也快102-104倍。这允许对µSec动力学的耦合进行现实建模和 在最后一个赠款期间证明的催化对于理解反应至关重要。一起 使用标准力加速了反应中涉及的构象变化的MD模拟 这些计算研究涵盖了FSEC到µSEC时间尺度。在特定目标2中，计算结果 将与三层方法的结果合并，以获得结构快照 增加时间分辨率：（i）“冷冻”中间体可以绘制长时间尺度上的整体途径，（ii） 使用PH跳跃计划在MSEC时间尺度和（iii）使用光塑料的时间上解决了LAUE晶体学 底物允许在µSec时间尺度上进行时间解决的时间解决。这种方法将应用于 HMGR的研究是一种具有复杂反应的高生物物理和生物医学意义的酶 涉及三个化学步骤的机制，六个大规模构象变化和两个辅因子交换 步骤。该项目具有很高的创新性，因为它（i）使用TSFF和时间结合了MD模拟的组合 解决的晶体学以跨越至少12个数量级的时间尺度，（ii）迭代偶联马尔可夫 长时间轨迹对分析时间分析时间分析的单数值分解的状态分析 晶体学数据，因此提供了新工具来生成和实验验证试验结构（III） 全球优化和机器学习技术允许TSFF自动拟合蛋白质，该蛋白质的拟合 将增强这种强大方法在其他蛋白质中的应用，（iv）提供新的摄影。 研究化学生物学界的酶机制的底物。所有工具化合物， 该项目中开发的方法和代码将提供给科学界。