title: Secondary structure of proteins and three-dimensional pattern recognition.
abstract: We describe a new, parameter-free, method to predict the secondary structure of a protein. It is based on the recognition of well-defined pentapeptides, which allows the discrimination of alpha helices, beta sheets and random coils in proteins. Presently, a success rate of about 65% is achieved for a three-state model.
authors.affiliation: Université Claude Bernard, Villeurbanne, 69622, France.
authors.forename: A
authors.initials: A
authors.lastname: Figureau
authors.forename: M
authors.initials: M
authors.lastname: Angélica Soto
authors.forename: J
authors.initials: J
authors.lastname: Tohá
mesh_terms: D000465:Algorithms; D000818:Animals; D008956:Models, Chemical; D017433:Protein Structure, Secondary