Integration of protein motions with molecular networks reveals different mechanisms for permanent and transient interactions

Authors

  • Nitin Bhardwaj,

    1. Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520
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  • Alexej Abyzov,

    1. Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520
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  • Declan Clarke,

    1. Department of Chemistry, Yale University, New Haven, Connecticut 06520
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  • Chong Shou,

    1. Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520
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  • Mark B. Gerstein

    Corresponding author
    1. Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520
    2. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520
    3. Department of Computer Science, Yale University, New Haven, Connecticut 06520
    • Program in Computational Biology and Bioinformatics, Yale University, Bass 426, 266 Whitney Avenue, New Haven, CT 06520
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Abstract

The integration of molecular networks with other types of data, such as changing levels of gene expression or protein-structural features, can provide richer information about interactions than the simple node-and-edge representations commonly used in the network community. For example, the mapping of 3D-structural data onto networks enables classification of proteins into singlish- or multi-interface hubs (depending on whether they have >2 interfaces). Similarly, interactions can be classified as permanent or transient, depending on whether their interface is used by only one or by multiple partners. Here, we incorporate an additional dimension into molecular networks: dynamic conformational changes. We parse the entire PDB structural databank for alternate conformations of proteins and map these onto the protein interaction network, to compile a first version of the Dynamic Structural Interaction Network (DynaSIN). We make this network available as a readily downloadable resource file, and we then use it to address a variety of downstream questions. In particular, we show that multi-interface hubs display a greater degree of conformational change than do singlish-interface ones; thus, they show more plasticity which perhaps enables them to utilize more interfaces for interactions. We also find that transient associations involve smaller conformational changes than permanent ones. Although this may appear counterintuitive, it is understandable in the following framework: as proteins involved in transient interactions shuttle between interchangeable associations, they interact with domains that are similar to each other and so do not require drastic structural changes for their activity. We provide evidence for this hypothesis through showing that interfaces involved in transient interactions bind fewer classes of domains than those in a control set.

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