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Detection and refinement of encounter complexes for protein–protein docking: Taking account of macromolecular crowding

Authors

  • Xiaofan Li,

    1. Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, Lincoln's Inn Fields Laboratories, London WC2A 3PX, United Kindom
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    • The authors state no conflict of interest.

    • Xiaofan Li and Iain H. Moal contributed equally to this work

  • Iain H. Moal,

    1. Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, Lincoln's Inn Fields Laboratories, London WC2A 3PX, United Kindom
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    • The authors state no conflict of interest.

    • Xiaofan Li and Iain H. Moal contributed equally to this work

  • Paul A. Bates

    Corresponding author
    1. Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, Lincoln's Inn Fields Laboratories, London WC2A 3PX, United Kindom
    • Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, Lincoln's Inn Fields Laboratories, 44 Lincoln's Inn Fields, London WC2A 3PX, United Kingdom
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    • The authors state no conflict of interest.


Abstract

Analysis of trajectories from our rigid-body dynamics simulation package, BioSimz, is used to find regions on the surface of unbound proteins that form frequent and tenacious encounter complexes with their binding partner. Binding partners are significantly more likely to sojourn around true binding regions than around the remainder of the protein surface. This information is used to restrict the search space for flexible protein–protein docking using our SwarmDock algorithm, reducing the computational expense of docking, and improving or matching the ranking of successfully docked poses for all but four of 26 test cases. Running the simulations with external crowder proteins, at near physiological concentration, further enhances the binding region, compared to simulations without external crowders. Information gleaned from these simulations can give mechanistic insights into binding events. The application of these techniques to CAPRI targets 32 and 38–40 is discussed. Proteins 2010. © 2010 Wiley-Liss, Inc.

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