Computational Analysis of Enzyme Catalysis and Regulation

酶催化与调控的计算分析

• 批准号: 10206585
• 负责人: Qiang Cui
• 金额: $ 29.56万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10206585
• 关键词: Active Sites; Allosteric Regulation; Catalysis; Chemicals; Computer Analysis; Computing Methodologies; Coupled; Coupling; Crystallography; Diabetes Mellitus; Directed Molecular Evolution; Distal; Drug Design; Enzymes; Equilibrium; Event; Free Energy; Insulin Resistance; Ions; Knowledge; Machine Learning; Malignant Neoplasms; Membrane; Metals; Modernization; Modification; Molecular Conformation; Mutation; Nature; Nucleic Acids; Penetration; Peripheral; Positioning Attribute; Process; Proteins; Reaction; Regulation; Research; Sampling; Specificity; Speed; Techniques; Time; Tweens; Water; computerized tools; design; enzyme mechanism; human disease; insight; lipid metabolism; method development; mutation screening; novel; recruit; transcription factor

Project Summary: It is of great fundamental and biomedical importance to understand the physical princi- ples that govern the coupling between the chemical step in a biomolecule and other events, such as penetration of water molecules into the active site, recruitment of transient metal ions, or conformational rearrangements near and afar. This is a challenging task, however, due to the intrinsic multi-scale nature of the problem. As a result, our understanding in factors that dictate the efficiency and specificity of enzyme catalysis remains in- complete, especially regarding contributions beyond the active site; this knowledge gap has greatly limited our ability to design highly efficient enzymes de novo. Motivated by these considerations, the overarching theme of our research is to develop and apply multi-scale computational methods to reveal the underlying mechanism of enzyme catalysis at an atomic level, with a particular emphasis on establishing to what degree the chem- ical step is coupled with other processes proximal or distal to the active site. Specifically, we aim to develop an efficient QM/MM framework to compute free energy profiles of enzyme reactions with a good balance of computational speed and accuracy; further integration with enhanced sampling approaches, machine learning techniques and modern computational hardwares enables us to gain insights into the nature of coupling be- tween the chemical step and other events during the functional cycle. Accordingly, we are in a unique position to pursue several lines of exciting applications, which include the mechanism and impact of transient metal ion recruiting in nucleic acid processing enzymes, the catalytic and regulatory mechanism of peripheral membrane enzymes, and systemic analysis of allosteric coupling in a transcription factor; an emerging research direction is to explore the interplay of stability, catalytic activity, and allostery during continuous directed evolution. Our project integrates computational method developments with applications inspired by recent experimental ad- vances, such as time-resolved crystallography, deep mutational scanning and continuous directed evolution. The research efforts will lead to novel computational tools and mechanistic insights into the regulatory mech- anisms of enzymes by processes either near or remote from the active site. Thus the project will have both fundamental impacts and implications for better design strategies for catalysis and allostery in biomolecules.

项目摘要：了解物理原理具有重要的基础和生物医学意义。 控制生物分子化学步骤与其他事件（例如渗透）之间耦合的过程 水分子进入活性位点、招募瞬时金属离子或构象重排 然而，由于问题的内在多尺度性质，这是一项具有挑战性的任务。 因此，我们对决定酶催化效率和特异性的因素的理解仍然存在—— 完整，特别是关于活动站点之外的贡献；这种知识差距极大地限制了我们 出于这些考虑，我们的首要主题是从头设计高效酶。 我们的研究是开发和应用多尺度计算方法来揭示潜在机制 酶催化在原子水平上的研究，特别强调确定化学作用的程度 具体来说，我们的目标是开发与活性位点近端或远端的其他过程相结合的步骤。 一个有效的 QM/MM 框架，用于计算酶反应的自由能曲线，并具有良好的平衡 计算速度和准确性；与增强采样方法、机器学习的进一步集成 技术和现代计算硬件使我们能够深入了解耦合的本质 因此，我们处于独特的地位。 追求多种令人兴奋的应用，其中包括瞬态金属离子的机制和影响 核酸加工酶的招募、外周膜的催化和调节机制 酶，以及转录因子变构偶联的系统分析； 我们的目标是探索连续定向进化过程中稳定性、催化活性和变构的相互作用。 该项目将计算方法开发与受最近实验广告启发的应用程序相结合 进步，例如时间分辨晶体学、深度突变扫描和连续定向进化。 研究工作将带来新颖的计算工具和对监管机制的深入见解。 因此，该项目将同时具有靠近或远离活性位点的酶的作用。 对更好的生物分子催化和变构设计策略的基本影响和影响。