title: Prediction of beta-turns from amino acid sequences using the residue-coupled model.
abstract: We evaluated the prediction of beta-turns from amino acid sequences using the residue-coupled model with an enlarged representative protein data set selected from the Protein Data Bank. Our results show that the probability values derived from a data set comprising 425 protein chains yielded an overall beta-turn prediction accuracy 68.74%, compared with 94.7% reported earlier on a data set of 30 proteins using the same method. However, we noted that the overall beta-turn prediction accuracy using probability values derived from the 30-protein data set reduces to 40.74% when tested on the data set comprising 425 protein chains. In contrast, using probability values derived from the 425 data set used in this analysis, the overall beta-turn prediction accuracy yielded consistent results when tested on either the 30-protein data set (64.62%) used earlier or a more recent representative data set comprising 619 protein chains (64.66%) or on a jackknife data set comprising 476 representative protein chains (63.38%). We therefore recommend the use of probability values derived from the 425 representative protein chains data set reported here, which gives more realistic and consistent predictions of beta-turns from amino acid sequences.
authors.affiliation: Bioinformatics, Centre for Cellular and Molecular Biology, Hyderabad, India. guru@ccmb.res.in
authors.forename: K
authors.initials: K
authors.lastname: Guruprasad
authors.forename: S
authors.initials: S
authors.lastname: Shukla
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D030562:Databases, Protein; D011336:Probability; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D012680:Sensitivity and Specificity
chemical_list: D011506:Proteins