Synergizing Enzyme and Encapsulation Engineering to Develop Superoptimal Biocatalysts

酶是促进化学反应的蛋白质。它们可以生产生物燃料、化学品和药物。 它们可以被设计成在非自然条件下表现良好。设计工作通常会导致性能之间的权衡。例如，增加酶稳定性通常导致活性降低。该项目的主要目标是评估新的设计策略。这种策略可能会改善某些属性，而不会降低其他属性。该策略结合了一种新的起始材料的计算方法。 这项工作还将通过实践研究、研讨会和讲座支持本科生研究人员和代表性不足的群体的招聘和参与。这项工作的总体目标是开发一个“超优”生物催化系统，使酶可以在其特征最佳温度、周转频率（TOF，kcat）和转化率之外运行。实现这一点需要酶工程直接改变其催化性质和封装，以改变稳定性和底物和产物的运输速率和分配。该项目将使用含4-亚甲基咪唑-5-酮（MIO）的氨基酸氨裂解酶（XAL）作为模型酶。三个不同的假设将被测试。第一个是新的酶活性可以通过在工程化过程中放宽稳定性标准来实现。第二是含MIO的XAL酶可以接受非芳香底物。第三，工程化的封装系统可以提高酶的稳定性，反应速率和转化率。定向进化工作流程将鉴定具有高活性的XAL变体。在定向进化过程中，稳定性要求将被放宽。鉴定对非同源氨基酸底物具有活性的变体将是另一个目标。XAL酶以前从未被工程化以作用于非芳香底物。酶工程工作将使用深度突变扫描（DMS）指导的实验工作流程以及计算建模。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Enzymes are proteins that promote chemical reactions. They can produce biofuels, chemicals, and medicines. They can be designed to perform well under unnatural conditions. Design efforts usually result in trade-offs between properties. For example, increasing enzyme stability often results in reduced activity. A primary objective of the project is to evaluate a new design strategy. This strategy might improve certain properties without degrading others. The strategy combines a computational approach with a novel starting material. This work will also support recruitment and engagement of undergraduate researchers and underrepresented groups through hands-on research, workshops, and lectures.The overall goal of this work is to develop a “super-optimal” biocatalytic system where enzymes can operate beyond their characterized optimal temperatures, turnover frequency (TOF, kcat), and conversion. Achieving this requires enzyme engineering to directly modify their catalytic properties and encapsulation to alter stability and substrate and product transport rates and partitioning. The project will use a 4-methylideneimidazole-5-one (MIO)-containing amino acid ammonia-lyases (XAL) as a model enzyme. Three different hypotheses will be tested. The first is that novel enzyme activity can be achieved by relaxing stability criteria during engineering. The second is that MIO-containing XAL enzymes can accept non-aromatic substrates. The third is that an engineered encapsulation system can enhance enzyme stability, reaction rates, and conversion. A directed evolution workflow will identify XAL variants with high activity. Stability requirements will be relaxed during directed evolution. Identifying variants with activity on non-cognate amino acid substrates will be another objective. XAL enzymes have never previously been engineered to act on non-aromatic substrates. The enzyme engineering work will use a deep mutational scanning (DMS)-guided experimental workflow as well as computational modeling. Encapsulations for enzymes to enhance their stability, reaction rate, and product yield will be designed and evaluated.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.