Extending the catalytic activity of enzymes to unnatural reactions

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.