Network representation of protein interactions: Theory of graph description and analysis.
A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin.
Departement de Chimie, Ecole Normale Superieure, PSL Research University, UPMC Univ Paris 06, CNRS, Laboratoire des Biomolecules (LBM), 24 rue Lhomond, 75005 Paris, France.
Dennis
D
Kurzbach
D064267:Intrinsically Disordered Proteins / Q000737:chemistry* / Q000378:metabolism; D008958:Models, Molecular; D046912:Multiprotein Complexes / Q000737:chemistry* / Q000378:metabolism; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*
D064267:Intrinsically Disordered Proteins; D046912:Multiprotein Complexes
chemical shift; graph theory; network description; nuclear magnetic resonance; protein interactions; relaxation