Mapping the Evolution of a Novel Enzyme by Experiment and Computation

说明(申请人提供)：酶是用途最广的催化剂。天然来源的酶具有选择性好、催化反应种类多样、反应条件温和、反应速度显著提高等优点，在化工、生物技术和医疗保健等领域得到了广泛的应用。然而，酶的不利的固有性质，包括边缘稳定性、窄的底物专一性和与非水溶剂的不相容，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没有的反应。因此，我们设计和重新设计高效酶的能力具有极其重要的现实意义。酶的合理重新设计以提高催化活性和稳定性是对我们理解蛋白质序列-结构-功能关系的最终考验。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。相比之下，定向进化实验是一种非常成功的改善酶功能的方法。在定向进化实验中，通过随机突变和选择来提高适应度。然而，我们对有益的随机突变和适应性格局的结构和机制基础的理解仍然处于初级阶段。因此，全面研究大的序列变化如何导致酶功能的急剧变化不仅将弥合蛋白质序列-结构-功能关系中的基本知识鸿沟，还将显著提高我们设计具有所需特性的定制酶的能力。这项建议试图通过结合蛋白质工程实验室(伊唐)、结构生物学实验室(托德·叶茨)和计算蛋白质设计实验室(Ken Houk)的专业知识来揭示蛋白质健康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酶LovD的催化前景，其活性已在实验室中新进化，用于合成降胆固醇药物辛伐他汀：1)对进行新反应的LovD酶的定向进化路径中的突变进行结构分析；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；以及4)对有望增强LovD催化活性的交替序列突变的计算预测。

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.