Prof. Thomas Magliery, The Ohio State University

Information in Protein Sequences: Combinatorial and statistical Protein Design

Biochemistry Seminar

Both the prediction and design of protein structure, using computational and rational approaches, remain significant challenges in protein chemistry. A major limitation to developing a comprehensive physicochemical model of the protein structure-sequence relationship is the vastness of sequence space and the low-throughput nature of biophysical studies. We are pursuing two avenues to understand better the sequence structure-relationship: sorting large libraries of protein variants for structured proteins, and statistical analysis of ubiquitous protein families for protein redesign. In the combinatorial approach, we have developed a high-throughput cell-based screen for activity of the well-studied four-helix bundle protein Rop. To collect quantitative stability data for large numbers of variants, we have developed a method of high-throughput hydrophobic dye binding called High-Throughput Thermal Scanning (HTTS) which can be applied using automation and a real-time PCR machine 96-wells at a time. This system is being used to directly test the “rules” of protein design, taking those rules as hypotheses and sorting the resulting libraries for structure and stability. We are also interested in the role of correlated occurrences of amino acids in natural protein families. To that end, we have generated a consensus version of triosephosphate isomerase as a host to interrogate the roles of correlated positions by mutagenesis and library methods. Two closely-related consensus variants differ dramatically in their physical properties and activity. Methods for the analysis of pair-wise correlations in protein families, and a proof-of-principle application, will be discussed. Lessons from these approaches have been applied to improving the drug-like properties of the enzyme paraoxonase-1, a possible catalytic bioscavenger of organophosphorus nerve agents.

For more information contact Prof. Raquel Lieberman (404-385-3663).