Computational and Structural Characterisation of Protein Associations

  • Susan Jones
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 747)


Protein-protein associations represent the building blocks of biological systems. The classification of different types of protein association is fundamental to an understanding of the interactions they exhibit. A protein association can be classified as homo- (identical components) or hetero- (non-identical components) and in addition permanent (components only exist and function in an associated state) or transient (components exist independently but interact for a limited time to carry out a specific function). A large number of studies have analysed the physical and chemical characteristics of protein-protein interactions using three-dimensional structures derived from X-ray crystallography. This chapter summarises the major conclusions of these studies, focusing on amino acid preferences and secondary structure packing at interfaces: hydration, hydrophobic and electrostatic effects, conformational changes and evolutionary conservation. The studies highlight differences between the interaction sites and the rest of the protein surface and between different classes of protein association. Common themes in the interfaces of protein associations are also revealed including shape complementarity, the presence of water molecules, a high percentage of arginine residues, intermolecular hydrogen bonds and an energy of association comprising hydrophobic and electrostatic effects. These studies also emphasise how the relative importance of such characteristics is dependant upon the class of protein association, with permanent associations generally displaying different characteristics to transient associations.


Accessible Surface Area Hydrophobic Effect Protein Dimerization Interface Residue Protein Interface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Landes Bioscience and Springer Science+Business Media 2012

Authors and Affiliations

  • Susan Jones
    • 1
  1. 1.Department of Biochemistry, School of Life SciencesUniversity of SussexBrightonUK

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