title: TESS: a geometric hashing algorithm for deriving 3D coordinate templates for searching structural databases. Application to enzyme active sites.
abstract: It is well established that sequence templates such as those in the PROSITE and PRINTS databases are powerful tools for predicting the biological function and tertiary structure for newly derived protein sequences. The number of X-ray and NMR protein structures is increasing rapidly and it is apparent that a 3D equivalent of the sequence templates is needed. Here, we describe an algorithm called TESS that automatically derives 3D templates from structures deposited in the Brookhaven Protein Data Bank. While a new sequence can be searched for sequence patterns, a new structure can be scanned against these 3D templates to identify functional sites. As examples, 3D templates are derived for enzymes with an O-His-O "catalytic triad" and for the ribonucleases and lysozymes. When these 3D templates are applied to a large data set of nonidentical proteins, several interesting hits are located. This suggests that the development of a 3D template database may help to identify the function of new protein structures, if unknown, as well as to design proteins with specific functions.
authors.affiliation: Department of Biochemistry and Molecular Biology, University College, London, England.
authors.forename: A C
authors.initials: AC
authors.lastname: Wallace
authors.forename: N
authors.initials: N
authors.lastname: Borkakoti
authors.forename: J M
authors.initials: JM
authors.lastname: Thornton
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D016208:Databases, Factual; D010450:Endopeptidases / Q000737:chemistry; D004798:Enzymes / Q000737:chemistry*; D004950:Esterases / Q000737:chemistry; D011487:Protein Conformation
chemical_list: D004798:Enzymes; D004950:Esterases; D010450:Endopeptidases