title: APoc: large-scale identification of similar protein pockets.
abstract: BACKGROUND
  Most proteins interact with small-molecule ligands such as metabolites or drug compounds. Over the past several decades, many of these interactions have been captured in high-resolution atomic structures. From a geometric point of view, most interaction sites for grasping these small-molecule ligands, as revealed in these structures, form concave shapes, or 'pockets', on the protein's surface. An efficient method for comparing these pockets could greatly assist the classification of ligand-binding sites, prediction of protein molecular function and design of novel drug compounds.
  
  
  RESULTS
  We introduce a computational method, APoc (Alignment of Pockets), for the large-scale, sequence order-independent, structural comparison of protein pockets. A scoring function, the Pocket Similarity Score (PS-score), is derived to measure the level of similarity between pockets. Statistical models are used to estimate the significance of the PS-score based on millions of comparisons of randomly related pockets. APoc is a general robust method that may be applied to pockets identified by various approaches, such as ligand-binding sites as observed in experimental complex structures, or predicted pockets identified by a pocket-detection method. Finally, we curate large benchmark datasets to evaluate the performance of APoc and present interesting examples to demonstrate the usefulness of the method. We also demonstrate that APoc has better performance than the geometric hashing-based method SiteEngine.
  
  
  METHODS
  The APoc software package including the source code is freely available at http://cssb.biology.gatech.edu/APoc.
authors: Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA 30076, USA.
authors: Mu
authors: M
authors: Gao
authors: Jeffrey
authors: J
authors: Skolnick
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000201:enzymology; D001426:Bacterial Proteins / Q000737:chemistry; D001665:Binding Sites; D020558:GTP Phosphohydrolases / Q000737:chemistry; D008024:Ligands; D008958:Models, Molecular; D015233:Models, Statistical; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D012984:Software
chemical_list: D001426:Bacterial Proteins; D008024:Ligands; D011506:Proteins; D020558:GTP Phosphohydrolases