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                                           BIOINFORMATICS COLLOQUIUM
					       College of Science
                                            George Mason University
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		From Atoms to Molecules to Machines:  Computing Protein Motion to Elucidate Function 
					
 						   Amarda Shehu
    
	      			 		     Professor
					      George Mason University

Abstract:
Like small lego pieces, protein monomers assemble into structures of greater
complexity in cells. Protein complexes play central roles in ion transport
and regulation in membranes, transduction of signal down chemical pathways,
degradation of proteins, and even transcriptional regulation. The
pervasiveness of protein complexes as important molecular machines in
cells warrants more urgency into structural studies to offer mechanistic
insight into their biological function. Elucidating structure, however,
does not tell the entire picture. The protein subunits in a complex often
change their own structures to modify in a concerted way the morphology
and biological function of the complex.

In this talk I will present a framework that computes
functionally-relevant motions by generating ensembles of conformations
assumed by a protein under physiological (native) conditions. The
framework elucidates how diverse functional structures arise from
concerted motions in a protein. The framework combines probabilistic
exploration conducted at multiple scales, with dimensionality reduction
techniques, and a statistical mechanics formulation. Such combination
allows to quantify relative populations of different native substates of a
protein.

The proposed framework provides a bridge between computer science,
biophysical theory, and wet-lab applications. By obtaining an in-silico
view of motions and resulting structures, the framework has the potential
to complement wet-lab protocols in the study of function and mechanism
in naturally-occurring and engineered protein monomers and complexes. The
design aspect, in particular, has far-reaching implications for proposing
physically-sound models of molecular machines with specific structural
morphologies and function.