title: Functional inferences from blind ab initio protein structure predictions.
abstract: Ab initio protein structure prediction methods have improved dramatically in the past several years. Because these methods require only the sequence of the protein of interest, they are potentially applicable to the open reading frames in the many organisms whose sequences have been and will be determined. Ab initio methods cannot currently produce models of high enough resolution for use in rational drug design, but there is an exciting potential for using the methods for functional annotation of protein sequences on a genomic scale. Here we illustrate how functional insights can be obtained from low-resolution predicted structures using examples from blind ab initio structure predictions from the third and fourth critical assessment of structure prediction (CASP3, CASP4) experiments.
authors.affiliation: Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA.
authors.forename: R
authors.initials: R
authors.lastname: Bonneau
authors.forename: J
authors.initials: J
authors.lastname: Tsai
authors.forename: I
authors.initials: I
authors.lastname: Ruczinski
authors.forename: D
authors.initials: D
authors.lastname: Baker
mesh_terms: D019295:Computational Biology / Q000379:methods* / Q000706:statistics & numerical data; D008956:Models, Chemical; D015394:Molecular Structure; D011487:Protein Conformation; D017510:Protein Folding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins