title: FTSite: high accuracy detection of ligand binding sites on unbound protein structures.
abstract: BACKGROUND
  Binding site identification is a classical problem that is important for a range of applications, including the structure-based prediction of function, the elucidation of functional relationships among proteins, protein engineering and drug design. We describe an accurate method of binding site identification, namely FTSite. This method is based on experimental evidence that ligand binding sites also bind small organic molecules of various shapes and polarity. The FTSite algorithm does not rely on any evolutionary or statistical information, but achieves near experimental accuracy: it is capable of identifying the binding sites in over 94% of apo proteins from established test sets that have been used to evaluate many other binding site prediction methods.
  
  
  BACKGROUND
  FTSite is freely available as a web-based server at http://ftsite.bu.edu.
authors: Department of Biomedical Engineering, Boston University, Boston, MA 02115, USA.
authors: Chi-Ho
authors: CH
authors: Ngan
authors: David R
authors: DR
authors: Hall
authors: Brandon
authors: B
authors: Zerbe
authors: Laurie E
authors: LE
authors: Grove
authors: Dima
authors: D
authors: Kozakov
authors: Sandor
authors: S
authors: Vajda
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D018360:Crystallography, X-Ray; D015195:Drug Design; D006678:HIV / Q000201:enzymology; D016333:HIV Protease / Q000737:chemistry; D008024:Ligands; D019906:Nuclear Magnetic Resonance, Biomolecular; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D013025:Glycine max / Q000201:enzymology; D001614:beta-Amylase / Q000737:chemistry
chemical_list: D008024:Ligands; D011506:Proteins; D001614:beta-Amylase; D016333:HIV Protease