title: Protein-protein binding affinity prediction on a diverse set of structures.
abstract: BACKGROUND
  Accurate binding free energy functions for protein-protein interactions are imperative for a wide range of purposes. Their construction is predicated upon ascertaining the factors that influence binding and their relative importance. A recent benchmark of binding affinities has allowed, for the first time, the evaluation and construction of binding free energy models using a diverse set of complexes, and a systematic assessment of our ability to model the energetics of conformational changes.
  
  
  RESULTS
  We construct a large set of molecular descriptors using commonly available tools, introducing the use of energetic factors associated with conformational changes and disorder to order transitions, as well as features calculated on structural ensembles. The descriptors are used to train and test a binding free energy model using a consensus of four machine learning algorithms, whose performance constitutes a significant improvement over the other state of the art empirical free energy functions tested. The internal workings of the learners show how the descriptors are used, illuminating the determinants of protein-protein binding.
  
  
  BACKGROUND
  The molecular descriptor set and descriptor values for all complexes are available in the Supplementary Material. A web server for the learners and coordinates for the bound and unbound structures can be accessed from the website: http://bmm.cancerresearchuk.org/~Affinity.
  
  
  BACKGROUND
  paul.bates@cancer.org.uk.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.
authors: Iain H
authors: IH
authors: Moal
authors: Rudi
authors: R
authors: Agius
authors: Paul A
authors: PA
authors: Bates
mesh_terms: D001185:Artificial Intelligence; D046912:Multiprotein Complexes / Q000737:chemistry / Q000378:metabolism*; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*
chemical_list: D046912:Multiprotein Complexes