Mapping the Evolution of a Novel Enzyme by Experiment and Computation

通过实验和计算绘制新型酶的进化图

• 批准号: 8298035
• 负责人: KENDALL N HOUK
• 金额: $ 33.83万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8298035
• 关键词: Active Sites; Affinity; Amino Acid Sequence; Amino Acids; Anabolism; Binding; Biochemical; Biological Sciences; Biotechnology; Catalysis; Chemicals; Cholesterol; Computing Methodologies; Custom; DNA Sequence Rearrangement; Data; Engineering; Entropy; Enzyme Stability; Enzymes; Evolution; Free Energy; Gene Mutation; Goals; Healthcare Industry; Investigation; Kinetics; Knowledge; Laboratories; Lead; Maps; Methods; Modeling; Mutagenesis; Mutation; Nature; Pathway interactions; Peptide Sequence Determination; Pharmaceutical Preparations; Property; Protein Conformation; Protein Engineering; Proteins; Reaction; Role; Series; Side; Simvastatin; Solvents; Source; Structure; Structure-Activity Relationship; Substrate Specificity; Testing; Triad Acrylic Resin; Water; base; catalyst; computerized tools; design; directed evolution; enzyme activity; fitness; improved; insight; mutant; novel; protein protein interaction; reaction rate; research study; simulation; structural biology; tool

DESCRIPTION (provided by applicant): Enzymes are the most versatile catalysts. Because of their exquisite selectivity, diverse array of catalyzed reactions, mild reaction conditions, and significant enhancement of reactions rates, enzymes isolated from natural sources have been widely used in the chemical, biotechnology and health care industries. However, unfavorable intrinsic properties of enzymes, including marginal stability, narrow substrate specificity and incompatibility with nonaqueous solvents, have made engineering of enzymes necessary. For some applications, enzymes can be designed de novo to catalyze reactions that are not found in nature. Therefore, our abilities to design and redesign efficient enzymes have extremely important and practical implications. The rational redesign of enzymes towards increased catalytic activity and stability is an ultimate test of our understanding of protein sequence-structure-function relationships. Although advances in computational tools have enabled construction of new enzymes catalyzing unnatural reactions, our ability to drastically improve enzyme activity towards a desired reaction in a rational manner has remained underdeveloped. In contrast, directed evolution experiments, in which fitness is elevated via random mutation and selection, is a highly successful method of improving enzyme function. However, our understanding of the structural and mechanistic basis of beneficial random mutations and fitness landscape remains rudimentary. Therefore, a comprehensive investigation of how large sequence changes can lead to dramatic changes in enzyme function will not only bridge this fundamental knowledge gap in protein sequence-structure-function relationships, it will also significantly improve our capabilities in designing custom enzymes with desired properties. This proposal attempts to reveal the structural and mechanistic bases of protein fitness landscape by combining the expertise of a protein engineering lab (Yi Tang), a structural biology lab (Todd Yeates) and a computational protein design lab (Ken Houk). Four interrelated and interdisciplinary aims will explore the catalytic landscape of a recently discovered enzyme, LovD, whose activity has been newly evolved in the laboratory towards the synthesis of the cholesterol lowering drug simvastatin: 1) Structural analysis of mutants in the directed- evolutionary pathway of a LovD enzyme carrying out a new reaction; 2) Biochemical and biophysical studies of LovD and mutants; 3) Computational characterization of LovD mutants; and 4) Computational prediction of alternate sequence mutations expected to confer enhanced catalytic activity on LovD. PUBLIC HEALTH RELEVANCE: Understanding the sequence-structure-function relationships of proteins is one of the most important goals in biological sciences. We proposed to perform comprehensive structural and mechanistic analysis of a set of evolved mutants of the simvastatin synthase LovD obtained from an exhaustive directed evolutionary effort. By using both experimental and computational tools, we aim to provide insights into enzyme catalysis and to enable more intelligent rational (re)design of new enzymes.

描述（由申请人提供）：酶是最通用的催化剂。从天然来源分离的酶由于其优良的选择性、多样的催化反应、温和的反应条件以及显着提高的反应速率，已广泛应用于化学、生物技术和医疗保健行业。然而，酶的不利内在特性，包括边际稳定性、狭窄的底物特异性以及与非水溶剂的不相容性，使得酶的工程化成为必要。对于某些应用，可以从头设计酶来催化自然界中未发现的反应。因此，我们设计和重新设计高效酶的能力具有极其重要和实际的意义。 为了提高催化活性和稳定性而对酶进行合理的重新设计是对我们对蛋白质序列-结构-功能关系理解的最终考验。尽管计算工具的进步已经能够构建催化非自然反应的新酶，但我们以合理的方式大幅提高酶活性以实现所需反应的能力仍然不发达。相比之下，定向进化实验通过随机突变和选择来提高适应度，是一种非常成功的改善酶功能的方法。然而，我们对有益随机突变和适应度景观的结构和机制基础的理解仍然很初级。因此，全面研究大的序列变化如何导致酶功能的巨大变化不仅将弥合蛋白质序列-结构-功能关系的基本知识差距，还将显着提高我们设计具有所需特性的定制酶的能力。 该提案试图通过结合蛋白质工程实验室（Yi Tang）、结构生物学实验室（Todd Yeates）和计算蛋白质设计实验室（Ken Houk）的专业知识来揭示蛋白质适应性景观的结构和机制基础。四个相互关联和跨学科的目标将探索最近发现的一种酶 LovD 的催化景观，该酶的活性已在实验室中针对降胆固醇药物辛伐他汀的合成进行了新的进化：1）定向进化途径中突变体的结构分析进行新反应的 LovD 酶； 2）LovD及其突变体的生化和生物物理研究； 3）LovD突变体的计算表征； 4) 替代序列突变的计算预测有望增强 LovD 的催化活性。 公共健康相关性：了解蛋白质的序列-结构-功能关系是生物科学最重要的目标之一。我们建议对辛伐他汀合酶 LovD 的一组进化突变体进行全面的结构和机制分析，这些突变体是通过详尽的定向进化努力获得的。通过使用实验和计算工具，我们的目标是提供对酶催化的见解，并实现新酶的更智能、合理（重新）设计。