Literature DB >> 14708119

The complexity of complexes in signal transduction.

William S Hlavacek1, James R Faeder, Michael L Blinov, Alan S Perelson, Byron Goldstein.   

Abstract

Many activities of cells are controlled by cell-surface receptors, which in response to ligands, trigger intracellular signaling reactions that elicit cellular responses. A hallmark of these signaling reactions is the reversible nucleation of multicomponent complexes, which typically begin to assemble when ligand-receptor binding allows an enzyme, often a kinase, to create docking sites for signaling molecules through chemical modifications, such as tyrosine phosphorylation. One function of such docking sites is the co-localization of enzymes with their substrates, which can enhance both enzyme activity and specificity. The directed assembly of complexes can also influence the sensitivity of cellular responses to ligand-receptor binding kinetics and determine whether a cellular response is up- or downregulated in response to a ligand stimulus. The full functional implications of ligand-stimulated complex formation are difficult to discern intuitively. Complex formation is governed by conditional interactions among multivalent signaling molecules and influenced by quantitative properties of both the components in a system and the system itself. Even a simple list of the complexes that can potentially form in response to a ligand stimulus is problematic because of the number of ways signaling molecules can be modified and combined. Here, we review the role of multicomponent complexes in signal transduction and advocate the use of mathematical models that incorporate detail at the level of molecular domains to study this important aspect of cellular signaling. Copyright 2003 Wiley Periodicals, Inc.

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Year:  2003        PMID: 14708119     DOI: 10.1002/bit.10842

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  76 in total

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6.  Studying multiprotein complexes by multisignal sedimentation velocity analytical ultracentrifugation.

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7.  Trading the micro-world of combinatorial complexity for the macro-world of protein interaction domains.

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8.  Signaling through receptors and scaffolds: independent interactions reduce combinatorial complexity.

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10.  Kinetic Monte Carlo method for rule-based modeling of biochemical networks.

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Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2008-09-10
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