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Determination of structure, dynamics and energetics of enzyme reactions

酶反应的结构、动力学和能量学测定

基本信息

批准号：
10672407
负责人：
OLAF G WIEST
金额：
$ 32.16万
依托单位：
UNIVERSITY OF NOTRE DAME
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-07-01 至 2025-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10672407
关键词：
3-hydroxy-3-methylglutaryl-coenzyme A Acceleration 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 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

项目摘要

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.

项目摘要了解酶的机制是至关重要的，从基础生物物理学的角度来看，了解生命过程和酶在疾病中的作用。为了详细了解酶催化，蛋白质结构和动力学对反应能量学的影响需要阐明。我们提出了一种计算和实验相结合的方法，结合了合成，计算和结构生物学专业知识的一个团队的研究人员，一直在一起工作了超过15年，创造这是一部“分子电影”，系统中每个原子的位置、运动和能量都跟随着整个系统。整个反应过程。该提案利用了分子生物学可访问的时间尺度的新兴收敛，使用GPU和时间分辨结构生物学进行模拟。具体目标1描述了模拟完整的反应途径的假单胞菌mevalonii（Pm）HMGCoA还原酶（HMGR），将使用通过量子引导分子力学方法产生的过渡态力场（TSFF），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。这允许对微秒动态耦合进行真实建模，在上一个资助期内，催化作用被证明是理解反应所必需的。一起用标准力加速分子动力学模拟反应中的构象变化场，这些计算研究涵盖了fsec到µsec的时间尺度。在具体目标2中，将与三层方法的结果合并，以获得结构快照，提高时间分辨率：（i）“冻结”中间体，在长时间尺度上绘制出整体路径，（ii）时间分辨劳厄晶体学，使用毫秒时间尺度上的pH跳跃起始，和（iii）使用光笼衬底，以允许在微秒时间尺度上进行时间分辨的劳厄实验。这种方法将适用于研究HMGR，一种具有复杂反应的高生物物理和生物医学意义的酶包括三个化学步骤，六个大规模构象变化和两个辅因子交换的机制步该项目是高度创新的，因为它（i）使用了使用TSFF和时间的MD模拟的组合解决晶体学跨越至少12个数量级的时间尺度，（ii）迭代耦合马尔可夫长时间尺度轨道状态分析的奇异值分解用于时间分辨分析晶体学数据，从而提供了新的工具，以产生和实验验证试验结构（iii）适用全局优化和机器学习技术，允许自动拟合蛋白质的TSFF，将增强这种强大的方法对其他蛋白质的应用，并（iv）提供新的光笼酶机制研究的底物，以化学生物界。所有的工具化合物，将向科学界提供在该项目中制定的方法和守则。