title: Prediction of beta-turns.
abstract: Kohonen's self-organization model, a neural network model, is applied to predict the beta-turns in proteins. There are 455 beta-turn tetrapeptides and 3807 non-beta-turn tetrapeptides in the training database. The rates of correct prediction for the 110 beta-turn tetrapeptides and 30,229 non-beta-turn tetrapeptides in the testing database are 81.8% and 90.7%, respectively. The high quality of prediction of neural network model implies that the residue-coupled effect along a polypeptide chain is important for the formation of reversal turns, such as beta-turns, during the process of protein folding.
authors.affiliation: Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences.
authors.forename: Y D
authors.initials: YD
authors.lastname: Cai
authors.forename: H
authors.initials: H
authors.lastname: Yu
authors.forename: K C
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000595:Amino Acid Sequence; D008956:Models, Chemical; D016571:Neural Networks, Computer; D009842:Oligopeptides / Q000737:chemistry*; D011487:Protein Conformation
chemical_list: D009842:Oligopeptides