title: An algorithm for constraint-based structural template matching: application to 3D templates with statistical analysis.
abstract: BACKGROUND
  Structural templates consisting of a few atoms in a specific geometric conformation provide a powerful tool for studying the relationship between protein structure and function. Current methods for template searching constrain template syntax and semantics by their design. Hence there is a need for a more flexible core algorithm upon which to build more sophisticated tools. Statistical analysis of structural similarity is still in its infancy when compared with its analogue in sequence alignment. In the context of template matching, there is an urgent need for normalization of scores so that results from templates with differing sensitivity may be compared directly.
  
  
  RESULTS
  We introduce Jess, a fast and flexible algorithm for searching protein structures for small groups of atoms under arbitrary constraints on geometry and chemistry. We apply the algorithm to a set of manually derived enzyme active site templates, and derive an empirical measure for estimating the relative significance of hits encountered using differing templates.
authors.affiliation: European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. jbarker@ebi.ac.uk
authors.forename: Jonathan A
authors.initials: JA
authors.lastname: Barker
authors.forename: Janet M
authors.initials: JM
authors.lastname: Thornton
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D003198:Computer Simulation; D004798:Enzymes / Q000737:chemistry*; D008958:Models, Molecular; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods; D013329:Structure-Activity Relationship
chemical_list: D004798:Enzymes; D011506:Proteins