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Automatic domain decomposition of proteins by a Gaussian Network Model
Authors:Kundu Sibsankar  Sorensen Dan C  Phillips George N
Affiliation:Department of Biochemistry, University of Wisconsin, Madison, Wisconsin 53706, USA.
Abstract:Proteins are often comprised of domains of apparently independent folding units. These domains can be defined in various ways, but one useful definition divides the protein into substructures that seem to move more or less independently. The same methods that allow fairly accurate calculation of motion can be used to help classify these substructures. We show how the Gaussian Network Model (GNM), commonly used for determining motion, can also be adapted to automatically classify domains in proteins. Parallels between this physical network model and graph theory implementation are apparent. The method is applied to a nonredundant set of 55 proteins, and the results are compared to the visual assignments by crystallographers. Apart from decomposing proteins into structural domains, the algorithm can generally be applied to any large macromolecular system to decompose it into motionally decoupled sub-systems.
Keywords:protein structural domains  domain decomposition  Gaussian Network Model  Fiedler vector  vibrational dynamics  spectral graph partitioning  Laplacian matrix
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