Corey J Wilson
Scientific Tracks Abstracts: Metabolomics
Enzymes are essential protein catalysts that regulate most important biological processes. Our ability to control the function of enzymes via rational design will significantly improve our understanding of protein structure-function relationships and transform our ability to control biological processes (e.g., creating temperature adaptive proteins for biomedical and bio- industrial applications). Our current inability to predict the role of the protein scaffold structure and corresponding feedback mechanisms upon mutation reflects a significant gap in our understanding of enzyme function beyond the catalytic-site structure and to design enzymes that function outside of standard physiological conditions. Our current effort has focused on developing a novel computational protein design strategy to rationally design temperature-adapted enzymes. This project is innovative, because it represents a new and substantive departure from fixed-backbone enzyme design. Namely, we developed a discrete multistate enzyme design cycle (i.e., iterative hypothesis-driven multi-state enzyme modeling and experimental validation) that accurately captures structural and thermodynamic scaffold feedback properties to explicitly design conditional (temperature-adapted) enzymatic catalysis. Furthermore, we gained significant new insights into thermodynamic properties of enzyme structure function relationships.
Corey J Wilson is the director of the Biomolecular Engineering program at Yale University. He holds a doctorate in Molecular Biophysics (2005) and continued his education as a Gordon E. Moore Postdoctoral Scholar at Caltech (2006-2008) before taking his position at Yale University where he is the Principal Investigator of a thriving research group. His group at Yale seeks to engineer novel, non-natural proteins of tailored function for high impact applications. Protein engineering applies the fundamental principles of biophysics and biochemistry toward design, and is best achieved through an integrated experimental/computational framework.
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