Biophysical Model of Enzyme Catalysis: Conformational sub-states, solvent coupling and energy networks

酶催化的生物物理模型：构象亚态、溶剂耦合和能量网络

• 批准号: 10735359
• 负责人: Pratul K Agarwal
• 金额: $ 22.21万
• 依托单位: OKLAHOMA STATE UNIVERSITY STILLWATER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10735359
• 关键词: Active Sites; Biliverdin reductase; Biological Response Modifier Therapy; Biophysical Process; Biophysics; Catalysis; Chemicals; Collaborations; Communities; Computing Methodologies; Coupled; Coupling; Cyclophilin A; Data; Deposition; Development; Dihydrofolate Reductase; Disease; Distal; Drug Industry; Elements; Enabling Factors; Energy-Generating Resources; Environment; Enzyme Kinetics; Enzymes; Family; Health; Hereditary Disease; Human; Investigation; Joints; Kinetics; Knowledge; Link; Malignant Neoplasms; Medical; Medicine; Metabolic; Methods; Modeling; Molecular; Molecular Conformation; Molecular Machines; Motion; Mutate; Mutation; Nature; Output; Pancreas; Paper; Pathogenicity; Pathway interactions; Pharmaceutical Preparations; Play; Poison; Positioning Attribute; Process; Proteins; Publications; Reaction; Relaxation; Research; Ribonucleases; Roentgen Rays; Role; Sampling; Solvents; Structure; Surface; System; Techniques; Testing; Thermodynamics; United States National Institutes of Health; Validation; Work; biochemical model; biophysical model; conformational conversion; design; enzyme model; enzyme structure; experimental study; human disease; improved; insight; interest; laboratory experiment; molecular dynamics; mutant; neuron loss; novel strategies; novel therapeutics; protein data bank; protein structure; reaction rate; side effect; simulation; small molecule; software development; success

ABSTRACT Enzymes have important implications for understanding many human diseases as well as for developing new medicines and therapies. Design of small molecule drugs without side-effects targeting enzymes and designer enzymes as biotherapeutics are widely pursued in the pharmaceutical industry. However, these endeavors are hindered, among other aspects, by the lack of fundamental understanding of enzyme function including the factors that enable enzymes to achieve high catalytic efficiencies. For more than a century, an immense wealth of information has been accumulated based on experimental and computational investigations. Collectively, the biochemical model of enzyme catalysis has revealed the vital roles of active-site residues and other secondary structure elements. However, clear understanding of the roles of: (1) the functionally important conformational sub-states (or rare intermediates); (2) the distal regions including the conserved residues and surface loops; and (3) the surrounding solvent, in enzyme catalysis still remain elusive. For close to two decades, Agarwal lab has been working on using joint computational-experimental approaches for obtaining answers to several important questions about enzymes. Investigations of >20 different enzyme systems have enabled us to contribute to building a biophysical model of enzyme catalysis, which is improving our knowledge of these highly efficient molecular machines. We have discovered conserved network of residues linking surface loop regions to the active-site in several medically important enzyme systems, and successfully developed and validated quasi-anharmonic analysis (QAA) method for identification of conformational sub- states. In this proposal, we describe computational investigations of several enzymes including human ribonucleases, dihydrofolate reductase and biliverdin reductase. Using previously developed and new approaches, the following key questions will be answered: (1) What roles do conformational sub-states play in enzyme catalysis? Specifically, functionally important higher energy sub-states and their linkage to kinetics of the rate-limiting step in enzyme cycle will be quantitatively characterized; (2) Energy flow within preferential pathways (or network channels) formed by conserved residues will be characterized as the biophysical mechanism for long-distance coupling; (3) Thermodynamical coupling between the surrounding environment (solvent) and the enzyme structure and catalyzed reaction will be characterized. A combination of molecular dynamics (MD) and new theoretical analysis methods will be used. We have and continue to work with a number of experimental laboratories to validate our models and their outputs. Experimental data from NMR, enzyme kinetics, X-ray and other techniques on wild type and mutant versions of enzyme systems will be used to iteratively refine our models. These investigations will provide new insights into mechanism of long-distance effects and insights into factors that contribute to the catalytic efficiency of enzymes. The developed software will continue to be made available to the community and we will support a wide variety of labs in their investigations of enzymes. Over long-term these efforts will lead to designing of better allosteric modulators and designer enzymes for biotherapies.

摘要 酶对了解许多人类疾病以及开发新的 药物和疗法。无毒副作用靶向酶的小分子药物设计及设计者 酶作为生物治疗药物在制药工业中得到了广泛的追求。然而，这些努力是 除其他方面外，由于缺乏对酶功能的基本了解，包括 使酶能够实现高催化效率的因素。一个多世纪以来，一笔巨大的财富 在实验和计算调查的基础上积累了大量的信息。总而言之， 酶催化的生化模型揭示了活性中心残基和其他物质的重要作用 二次结构元素。然而，清楚地认识到：(1)功能上的重要性 构象亚态(或稀有中间体)；(2)包括保守残基和 表面环；以及(3)在酶催化中周围的溶剂仍然难以捉摸。将近两个人 几十年来，阿加瓦尔实验室一直致力于使用联合计算-实验方法来获得 回答了几个关于酶的重要问题。对&gt；20种不同的酶系统的研究 使我们能够为建立酶催化的生物物理模型做出贡献，这正在提高我们的知识 这些高效的分子机器。我们发现了连接残基的保守网络 在几个医学上重要的酶系统中将表面环区连接到活性部位，并成功地 开发并验证了用于识别构象亚组分的准非调和分析(QAA)方法 各州。在这项建议中，我们描述了几种酶的计算研究，包括人类 核糖核酸酶、二氢叶酸还原酶和胆绿素还原酶。使用以前开发的和新的 方法，将回答以下关键问题：(1)构象亚态在 酶催化？具体地说，功能上重要的更高能子态及其与动力学的联系 酶循环中的限速步骤将被定量描述；(2)优先内的能量流动 由保守残基形成的路径(或网络通道)将被描述为生物物理 长距离耦合机制；(3)周围环境之间的热力学耦合 (溶剂)，并对酶的结构和催化反应进行表征。一种分子的组合 将使用动力学(MD)和新的理论分析方法。我们已经并将继续与 实验实验室的数量，以验证我们的模型及其输出。来自核磁共振的实验数据， 将使用酶动力学、X射线和其他关于野生型和突变型酶系统的技术 反复改进我们的模型。这些研究将为研究远程运动的机制提供新的见解。 对影响酶催化效率的因素的影响和洞察。开发的软件 将继续向社区提供，我们将支持他们的各种实验室 酶的研究。从长远来看，这些努力将导致设计出更好的变构调节剂 以及用于生物治疗的特制酶。