Mapping the Evolution of a Novel Enzyme by Experiment and Computation

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、多样化的催化反应、温和的反应条件和显著的提高反应速率等优点，在化学、生物技术和医疗保健等领域得到了广泛的应用。然而，酶的不利固有特性，包括边际稳定性、底物特异性窄和与非水溶剂不相容，使得酶的工程设计成为必要。在某些应用中，酶可以被重新设计来催化自然界中不存在的反应。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。对酶进行合理的重新设计以提高催化活性和稳定性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使构建催化非自然反应的新酶成为可能，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。相反，定向进化实验通过随机突变和选择来提高适应性，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性景观的结构和机制基础的理解仍然是初级的。因此，对大序列变化如何导致酶功能发生巨大变化的全面研究不仅将弥合蛋白质序列-结构-功能关系中的这一基本知识差距，还将显著提高我们设计具有所需特性的定制酶的能力。本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，揭示蛋白质适应性景观的结构和机制基础。四个相互关联的跨学科目标将探索一种新发现的酶，LovD，其活性在实验室中新进化到合成降胆固醇药物辛伐他汀的催化景观：1)进行新反应的LovD酶定向进化途径突变体的结构分析；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)交替序列突变的计算预测有望增强对LovD的催化活性。

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.