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Center for Nonlinear Studies |
Nature is restricted to a limited number of protein interactions; hence, the number of binding architectures is also limited. In addition to similar binding preferences of homologous protein pairs, different protein pairs can also use the same binding architectures. Thus, extrapolation of known template architectures to whole target proteins should permit the modeling of the interactions of the proteome; and piecing these together can provide a detailed view of protein pathways. Here, we introduce a knowledge-based combinatorial strategy to predict global functional associations of proteins, and putting these together to construct pathways on the proteome scale. Within this framework, the allosteric effect, i.e. the redistribution of the conformational ensembles following some perturbation event, is a major factor controlling pathway regulation; determining which protein binds at a shared binding site; regulates the coordinated action of molecular machines; and is responsible for long-range transmission of the information across the cell. Collectively, together with pre-organization of the network, these principles suggest how a hub protein can bind many different partners, and spell clear evolutionary advantages: the cell can function efficiently with fewer genes. 1. How do dynamic cellular signals travel long distances? Nussinov R. Mol Biosyst. 2012; 8(1):22-6. 2. Dynamic allostery: linkers are not merely flexible. Ma B, Tsai CJ, Haliloğlu T, Nussinov R. Structure. 2011; 19(7):907-17. 3. Constructing structural networks of signaling pathways on the proteome scale. Kuzu G, Keskin O, Gursoy A, Nussinov R. Curr Opin Struct Biol. 2012 May 8. [Epub ahead of print] 4. Protein-protein interaction networks: how can a hub protein bind so many different partners? Tsai CJ, Ma B, Nussinov R. Trends Biochem Sci. 2009; 34(12):594-600. This project has been funded in whole or in part with Federal funds from the NCI, NIH, under contract number HHSN261200800001E.
Host: S. Gnanakaran, 5-1923, gnana@lanl.gov