title: Challenges for the prediction of macromolecular interactions.
abstract: Macromolecular interactions are central to most cellular processes. Experimental methods generate diverse data on these interactions ranging from high throughput protein-protein interactions (PPIs) to the crystallised structures of complexes. Despite this, only a fraction of interactions have been identified and therefore predictive methods are essential to fill in the numerous gaps. Many predictive methods use information from related proteins. Accordingly, we review the conservation of interface and ligand binding sites within protein families and their association with conserved residues and Specificity Determining Positions. We then review recent developments in predictive methods for the identification of PPIs, protein interface sites and small molecule ligand binding sites. The challenges that are still faced by the community in these areas are discussed.
authors.affiliation: Structural Bioinformatics Group, Division of Molecular Biosciences, Imperial College London, South Kensington, London, UK.
authors.forename: Mark N
authors.initials: MN
authors.lastname: Wass
authors.forename: Alessia
authors.initials: A
authors.lastname: David
authors.forename: Michael J E
authors.initials: MJ
authors.lastname: Sternberg
mesh_terms: D001665:Binding Sites; D019295:Computational Biology; D006801:Humans; D008024:Ligands; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D025941:Protein Interaction Mapping; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D008024:Ligands; D011506:Proteins