title: Accuracy of protein flexibility predictions.
abstract: Protein structural flexibility is important for catalysis, binding, and allostery. Flexibility has been predicted from amino acid sequence with a sliding window averaging technique and applied primarily to epitope search. New prediction parameters were derived from 92 refined protein structures in an unbiased selection of the Protein Data Bank by developing further the method of Karplus and Schulz (Naturwissenschaften 72:212-213, 1985). The accuracy of four flexibility prediction techniques was studied by comparing atomic temperature factors of known three-dimensional protein structures to predictions by using correlation coefficients. The size of the prediction window was optimized for each method. Predictions made with our new parameters, using an optimized window size of 9 residues in the prediction window, were giving the best results. The difference from another previously used technique was small, whereas two other methods were much poorer. Applicability of the predictions was also tested by searching for known epitopes from amino acid sequences. The best techniques predicted correctly 20 of 31 continuous epitopes in seven proteins. Flexibility parameters have previously been used for calculating protein average flexibility indices which are inversely correlated to protein stability. Indices with the new parameters showed better correlation to protein stability than those used previously; furthermore they had relationship even when the old parameters failed.
authors.affiliation: Department of Biochemistry, University of Turku, Finland.
authors.forename: M
authors.initials: M
authors.lastname: Vihinen
authors.forename: E
authors.initials: E
authors.lastname: Torkkila
authors.forename: P
authors.initials: P
authors.lastname: Riikonen
mesh_terms: D000941:Antigens / Q000276:immunology; D001665:Binding Sites; D001696:Biomechanical Phenomena; D011487:Protein Conformation; D015203:Reproducibility of Results; D012984:Software
chemical_list: D000941:Antigens