Poster abstracts
Poster number 19 submitted by Sidharth Mohan
Engineering Protein Stability Through Statistical Analyses
Sidharth Mohan (Biophysics Graduate Program), Nicholas W. Callahan (Biophysics Graduate Program)
Abstract:
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 analyses of ubiquitous protein families for protein redesign. Residues that are important for specific functions of a protein may be conserved at specific positions or could co-vary with other residues within the target sequence. It has been shown that mutating residues to the consensus can be used as a starting point to stabilize proteins belonging to a common fold. In the statistical redesign approach, we have used a consensus-screening algorithm to engineer variants of Triosephosphate Isomerase (TIM) and present their biophysical characteristics, since we are interested in the roles of correlated occurrences of amino acids in natural protein families. In addition to fine tuning this approach for TIM as a model system through the use of specific sections of phylogeny, we have applied this technique to other proteins, such as Adenylate Kinase (ADK), FruR and p53, with promising results. We discovered that highly conserved positions with statistical independence from other sites provided the greatest benefit upon mutation. We are able to predict stabilizing consensus mutations with ~90% accuracy. We are currently using error-prone PCR techniques on cTIM and creating binomial libraries with cTIM and ccTIM through DNA shuffling experiments to probe the differences between cTIM and ccTIM from a biochemical viewpoint.
Keywords: Consensus Design, Protein Engineering, Combinatorial Biochemistry