{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T23:36:08Z","timestamp":1773272168660,"version":"3.50.1"},"reference-count":30,"publisher":"World Scientific Pub Co Pte Lt","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2003,4]]},"abstract":"<jats:p>The increase in known three-dimensional protein structures enables us to build statistical profiles of important functional sites in protein molecules. These profiles can then be used to recognize sites in large-scale automated annotations of new protein structures. We report an improved FEATURE system which recognizes functional sites in protein structures. FEATURE defines multi-level physico-chemical properties and recognizes sites based on the spatial distribution of these properties in the sites' microenvironments. It uses a Bayesian scoring function to compare a query region with the statistical profile built from known examples of sites and control nonsites. We have previously shown that FEATURE can accurately recognize calcium-binding sites and have reported interesting results scanning for calcium-binding sites in the entire Protein Data Bank. Here we report the ability of the improved FEATURE to characterize and recognize geometrically complex and asymmetric sites such as ATP-binding sites and disulfide bond-forming sites. FEATURE does not rely on conserved residues or conserved residue geometry of the sites. We also demonstrate that, in the absence of a statistical profile of the sites, FEATURE can use an artificially constructed profile based on a priori knowledge to recognize the sites in new structures, using redoxin active sites as an example.<\/jats:p>","DOI":"10.1142\/s0219720003000150","type":"journal-article","created":{"date-parts":[[2003,4,28]],"date-time":"2003-04-28T10:49:23Z","timestamp":1051526963000},"page":"119-138","source":"Crossref","is-referenced-by-count":20,"title":["RECOGNIZING COMPLEX, ASYMMETRIC FUNCTIONAL SITES IN PROTEIN STRUCTURES USING A BAYESIAN SCORING FUNCTION"],"prefix":"10.1142","volume":"01","author":[{"given":"LIPING","family":"WEI","sequence":"first","affiliation":[{"name":"Nexus Genomics, Inc., 229 Polaris Ave., Suite 6, Mountain View, CA 94043, USA"}]},{"given":"RUSS B.","family":"ALTMAN","sequence":"additional","affiliation":[{"name":"Department of Genetics, Mail Stop-5120, Stanford University, Stanford, CA 94305-5120, USA"}]}],"member":"219","published-online":{"date-parts":[[2012,1,25]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1066011"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/19.suppl.2241"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/25.1.217"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/27.1.220"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/19.23.6565"},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/27.1.226"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/27.1.260"},{"key":"rf9","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.87.15.5648"},{"key":"rf10","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.91.2.817"},{"key":"rf11","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1996.0081"},{"key":"rf12","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.93.16.8344"},{"key":"rf13","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.93.16.8350"},{"key":"rf14","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1996.0077"},{"key":"rf15","doi-asserted-by":"publisher","DOI":"10.1002\/pro.5560061104"},{"key":"rf16","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1998.1993"},{"key":"rf17","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1998.2061"},{"key":"rf18","doi-asserted-by":"publisher","DOI":"10.1002\/pro.5560040404"},{"key":"rf19","first-page":"497","author":"Wei L.","journal-title":"Pac. 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