Geometric Algorithms for Biological Research: Everything is a Puzzle After All

12:00noon, Oct 16, Thursday, 2008, ST2, 430


Amarda Shehu
Assistant Professor
Computer Science Department
George Mason University


As pieces in a puzzle, macromolecules assemble in cells to give rise to larger complex structures. Obtaining mechanistic insight into the cellular role of resulting complexes depends first on the ability to elucidate the structure and function of those pervasive building blocks in cells, proteins. The linear chain of amino acids in proteins often assumes various conformations to modulate function and inter-molecular associations. Protein function cannot be reliably extracted from a static picture of protein structure.

In this talk I will present a framework that makes progress in addressing an open problem in computational biology: how to obtain in silico a broad view of the ensemble of conformations populated by a protein under physiological (native) conditions. The framework employs probabilistic exploration to probe the geometry of a protein chain, integrates physical energetic constraints at multiple scales, reduces the dimensionality of the search space for both analysis and further exploration, and makes use of a statistical mechanics formulation of the protein native state. This approach allows quantifying relative populations of different conformational states of a protein. Recent work extends the framework to compute concerted motions that are the hallmark of proteins with multiple functional states.

Short Bio

Amarda Shehu is an Assistant Professor in the Department of Computer Science at George Mason University in Fairfax, VA. She holds a courtesy appointment in the Department of Bioinformatics and Computational Biology and is a faculty member of the Bioengineering Program at George Mason University. She received her Ph.D. in Computer Science from Rice University in Houston, TX in 2008, where she was an NIH fellow of the Nanobiology Training Program of the Gulf Coast Consortia. Her research interests encompass computational biophysics, bioinformatics, and nanobiology.