March 11, Thu 2010
11:00 am, MRB 100 Conference Room
Dr. Yan Yuan Tseng
University of Chicago
A geometric approach to protein structure, function and evolution
The function of a protein is often fulfilled via molecular interactions on its surfaces, so identifying functionally important protein surfaces and locating key residues are critical for understanding protein functions. I use a geometric approach to extract site-specific spatial information from coordinates of structures. To reduce the search space and expedite the process of surface partitioning, probe radii are designed according to the physicochemical textures of molecules. For each putative surface, I obtain its geometric measurements such as residue composition (spatial pattern), solvent-accessible area, and molecular volume. In a large-scale shape analysis, I develop an exact algorithm,SplitPocket, and conduct accurate computations to identify ~38,900 protein functional surfaces from ~19,000 crystal structures for the prediction of unbound binding sites and the inference of molecular functions. However, inferring protein functions from structures is a challenging task, as an increasing number of orphan protein structures from structural genomics project are now solved without their biochemical functions characterized. For proteins binding to similar ligands and carrying out similar functions, their binding surfaces are under similar physicochemical constraints, and hence the sets of allowed and forbidden residue substitutions are similar. In this presentation, I present my methods for predicting protein functions by incorporating evolutionary information specific to an individual binding region and by rapidly matching local surfaces. I also discuss these predictions, biological implications and medically important applications such as human disease-associated SNPs (Single-Nucleotide Polymorphisms). Finally, I show that the methods demonstrate the power of geometric and evolutionary matching for studying structural evolution on the basis of protein functional surfaces.