title: Predicting protein conformation by statistical methods.
abstract: The unique folded structure makes a polypeptide a functional protein. The number of known sequences is about a hundred times larger than the number of known structures and the gap is increasing rapidly. The primary goal of all structure prediction methods is to obtain structure-related information on proteins, whose structures have not been determined experimentally. Besides this goal, the development of accurate prediction methods helps to reveal principles of protein folding. Here we present a brief survey of protein structure predictions based on statistical analyses of known sequence and structure data. We discuss the background of these methods and attempt to elucidate principles, which govern structure formation of soluble and membrane proteins.
authors.affiliation: Institute of Enzymology, BRC, Hungarian Academy of Sciences, Budapest, Hungary. simon@enzim.hu
authors.forename: I
authors.initials: I
authors.lastname: Simon
authors.forename: A
authors.initials: A
authors.lastname: Fiser
authors.forename: G E
authors.initials: GE
authors.lastname: Tusnády
mesh_terms: D008565:Membrane Proteins / Q000737:chemistry; D011487:Protein Conformation; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000145:classification; D013223:Statistics as Topic / Q000379:methods
chemical_list: D008565:Membrane Proteins; D011506:Proteins