Title: "Engineering thermostability: Toward the design of highly stable protein mutants that maintain function at lower temperatures"

Speaker: Dr. Dennis R. Livesay
Place: SMITH 108; Tuesday, February 3, 2004, 4:30pm


Recent advances in protein engineering have resulted in several design breakthroughs, including the groundbreaking de novo design, synthesis, and characterization of a completely new protein fold (Kuhlman et al., Science. 2003, 302 1364-8). An especially important protein engineering problem relates to the relatively poor stability of many protein therapeutics and industrial enzyme catalysts. Therefore, our lab is focused on the development of strategies to confer increased stability to promising protein targets. There has been some success along these lines in the literature. However, increased stability often occurs at the expense of lower temperature function, generally due to over-rigidifying the protein structure. This challenge is a key obstacle and is preventing protein-based technologies from becoming more ubiquitous. In this talk, I will discuss three computational developments from our lab to circumvent this problem. The first is a robust bioinformatic methodology to identify which portions of the protein are most likely related to maintaining function. We show that our method, based on phylogenetic motifs, is able to reliably predict key functionality across a diverse protein dataset. These results provide critical knowledge which can be used to increase the likelihood of success in subsequent design endeavors. The second and third are biophysical models used to screen protein mutants for increased stability. In the second, we use continuum electrostatic theory to optimize protein surfaces, thus leading to increased stability. This approach meets our design mandate (increased stability and conserved function at lower temperatures) due to the plasticity of the protein surface. In the third, we present a powerful Distance Constraint Model, which is an accurate free energy calculation that explicitly accounts for protein flexibility. The DCM is built upon a mechanical description (called network rigidity) of the protein structure. Network rigidity efficiently identifies all rigid and flexible protein substructures and is used to correctly sum up component entropies. An additional advantage of this method is that network rigidity identifies all allosteric motions within the protein structure, meaning it can be used to gauge the likelihood of effecting proper protein function. For more information, visit: http://www.csupomona.edu/~drlivesay/.

(This is a candidate for the Bioinformatics COALESCE hires in the School of Science. To meet with the candidate, please contact RW Doerge at doerge@purdue.edu)

See http://www.stat.purdue.edu/~doerge/BIOINFORM.D/SPRING04/sem.html for a full scheule of BIOINFORMATICS SEMINARS.