TESS - A GEOMETRIC HASHING ALGORITHM FOR DERIVING 3D COORDINATE TEMPLATES FOR SEARCHING STRUCTURAL DATABASES - APPLICATION TO ENZYME ACTIVE-SITES

It is well established that sequence templates such as those in the PR OSITE and PRINTS databases are powerful tools for predicting the biolo gical function and tertiary structure for newly derived protein sequen ces. The number of X-ray and NMR protein structures is increasing rapi dly and it is apparent that a 3D equivalent of the sequence templates is needed. Here, we describe an algorithm called TESS that automatical ly derives 3D templates from structures deposited in the Brookhaven Pr otein Data Bank. While a new sequence can be searched for sequence pat terns, a new structure can be scanned against these 3D templates to id entify functional sites. As examples, 3D templates are derived for enz ymes 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 sug gests that the development of a 3D template database may help to ident ify the function of new protein structures, if unknown, as well as to design proteins with specific functions.