Extending the catalytic activity of enzymes to unnatural reactions

酶的工程化为可持续的化学合成创造了有用的催化剂，它也展示了对酶如何工作的理解。在这个项目中，蛋白质运动将被建模，以识别赋予新能力的酶突变。这些突变将通过实验进行评估，以验证模型。将招募代表性不足的少数民族学生参与该项目。将开发蛋白质工程的免费教科书以及蛋白质工程的网络工具。如果成功，该项目将使酶在工业应用中得到更广泛的应用。蛋白质工程师目前还不能设计出高效的酶。该项目的重点是将天然酶的催化能力扩展到非天然反应的简单问题。这使得更准确的计算方法来测试的假设，遥远的残基有助于催化精确定位的基板和催化基团。酶如何工作的更现实的模型将通过大量的实验数据验证计算来创建。模型系统将是酯酶进化成羟基腈裂解酶。将确定交换其催化活性所需的这些酶之间的最小数量的氨基酸变化。计算预测将通过构建酶变体并测量它们对催化的贡献来进行实验测试。这些精细的计算模型将被用来预测哪些取代将延长催化活性的羟基腈裂解酶的硝基醛加成，一个非自然的反应。对科学和工程的潜在贡献是第一个预测活性位点外的残基如何促进催化的计算方法，以及第一个合理设计用于非自然反应的有效酶。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。

Engineering of enzymes creates useful catalysts for sustainable chemical synthesis, and it also demonstrates an understanding of how enzymes work. In this project, protein motion will be modeled to identify enzyme mutations that impart new abilities. These mutations will be evaluated experimentally to validate the model. Underrepresented minority students will be recruited to work on the project. A free textbook for protein engineering will be developed as well as web tools for protein engineering. If successful, the project will enable the broader application of enzymes for industrial applications. Protein engineers cannot currently design efficient enzymes. This project focuses on the simpler problem of extending a natural enzyme's catalytic abilities to unnatural reactions. This allows more accurate computational approaches to test the hypothesis that distant residues contribute to catalysis by precisely positioning the substrates and catalytic groups. More realistic models of how enzymes work will be created by validating computation with extensive experimental data. The model system will be the evolution of esterases into hydroxynitrile lyases. The minimum number of amino acid changes between these enzymes that are needed to exchange their catalytic activities will be identified. Computational predictions will be tested experimentally by constructing enzyme variants and measuring their contributions to catalysis. These refined computational models will next be used to predict which substitutions will extend the catalytic activity of hydroxynitrile lyases to nitroaldol addition, an unnatural reaction. The potential contributions to science and engineering are the first computational approach to predict how residues outside the active site contribute to catalysis, and the first rational design of efficient enzymes for unnatural reactions. These abilities will enable biocatalytic synthesis of pharmaceuticals and fine chemicals.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.