title: Recognition of a protein fold in the context of the Structural Classification of Proteins (SCOP) classification.
abstract: A computational method has been developed for the assignment of a protein sequence to a folding class in the Structural Classification of Proteins (SCOP). This method uses global descriptors of a primary protein sequence in terms of the physical, chemical, and structural properties of the constituent amino acids. Neural networks are utilized to combine these descriptors in a way to discriminate members of a given fold from members of all other folds. An extensive testing of the method has been performed to evaluate its prediction accuracy. The method is applicable for the fold assignment of any protein sequence with or without significant sequence homology to known proteins. A WWW page for predicting protein folds is available at URL http://cbcg.lbl.gov/.
authors.affiliation: E.O. Lawrence Berkeley National Laboratory, University of California, Berkeley 94720, USA. ildubchak@lbl.gov
authors.forename: I
authors.initials: I
authors.lastname: Dubchak
authors.forename: I
authors.initials: I
authors.lastname: Muchnik
authors.forename: C
authors.initials: C
authors.lastname: Mayor
authors.forename: I
authors.initials: I
authors.lastname: Dralyuk
authors.forename: S H
authors.initials: SH
authors.lastname: Kim
mesh_terms: D000596:Amino Acids / Q000737:chemistry; D016208:Databases, Factual; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*
chemical_list: D000596:Amino Acids; D011506:Proteins