Computational Analysis of Enzyme Catalysis and Regulation

酶催化与调控的计算分析

• 批准号: 10376792
• 负责人: Qiang Cui
• 金额: $ 41.25万
• 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/10376792
• 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.

项目概述：了解其物理原理具有重要的基础和生物医学意义