title: Practical lessons from protein structure prediction.
abstract: Despite recent efforts to develop automated protein structure determination protocols, structural genomics projects are slow in generating fold assignments for complete proteomes, and spatial structures remain unknown for many protein families. Alternative cheap and fast methods to assign folds using prediction algorithms continue to provide valuable structural information for many proteins. The development of high-quality prediction methods has been boosted in the last years by objective community-wide assessment experiments. This paper gives an overview of the currently available practical approaches to protein structure prediction capable of generating accurate fold assignment. Recent advances in assessment of the prediction quality are also discussed.
authors.affiliation: BioInfoBank Institute ul. Limanowskiego 24A, 60-744 Poznań, Poland.
authors.forename: Krzysztof
authors.initials: K
authors.lastname: Ginalski
authors.forename: Nick V
authors.initials: NV
authors.lastname: Grishin
authors.forename: Adam
authors.initials: A
authors.lastname: Godzik
authors.forename: Leszek
authors.initials: L
authors.lastname: Rychlewski
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D008958:Models, Molecular; D011487:Protein Conformation; D017510:Protein Folding; D020539:Sequence Analysis, Protein