title: Functional site prediction selects correct protein models.
abstract: BACKGROUND
  The prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites. Without this information it is still possible to predict which residues are likely to be part of a functional site and this information can be used to select model structures from a variety of alternatives that would correspond to a functional protein.
  
  
  RESULTS
  Using a large collection of protein-like decoy models, a score was devised that selected those with predicted functional site residues that formed a cluster. When tested on a variety of small alpha/beta/alpha type proteins, including enzymes and non-enzymes, those that corresponded to the native fold were ranked highly. This performance held also for a selection of larger alpha/beta/alpha proteins that played no part in the development of the method.
  
  
  CONCLUSIONS
  The use of predicted site positions provides a useful filter to discriminate native-like protein models from non-native models. The method can be applied to any collection of models and should provide a useful aid to all modelling methods from ab initio to homology based approaches.
authors.affiliation: Division of Mathematical Biology, The National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK. vchelli@nimr.mrc.ac.uk
authors.forename: Vijayalakshmi
authors.initials: V
authors.lastname: Chelliah
authors.forename: William R
authors.initials: WR
authors.lastname: Taylor
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001665:Binding Sites; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure*; D020539:Sequence Analysis, Protein / Q000379:methods*; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins