Protein beta-turn prediction using nearest-neighbor method.
BACKGROUND
With the emerging success of protein secondary structure prediction through the applications of various statistical and machine learning techniques, similar techniques have been applied to protein beta-turn prediction. In this study, we perform protein beta-turn prediction using a k-nearest neighbor method, which is combined with a filter that uses predicted protein secondary structure information. Traditional beta-turn prediction from k-nearest neighbor method is modified to account for the unbalanced ratio of the natural occurrence of beta-turns and non-beta-turns.


RESULTS
Our prediction scheme is tested on a set of 426 non-homologous protein sequences. The prediction scheme consists of two stages: k-nearest neighbor method stage and filtering stage. Variations of the k-nearest neighbor method were used to take property of beta-turns into consideration. Our filtering method uses beta-turn/non-beta-turn estimates from the k-nearest neighbor method stage and predicted protein secondary structure information from PSI-PRED in order to get new beta-turn/non-beta-turn estimate. Our result is compared with the previously best known beta-turn prediction method on the dataset of 426 non-homologous protein sequences and is shown to give slightly superior performance at significantly lower computational complexity.


BACKGROUND
Contact the author for information on the source code of the programs used.
Kim
Saejoon
S
School of Computational Sciences, Korea Institute for Advanced Study, Seoul 130-722, Korea. saejoon@kias.re.kr
D000465:Algorithms; D000595:Amino Acid Sequence; D030562:Databases, Protein; D008958:Models, Molecular; D008969:Molecular Sequence Data; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017421:Sequence Analysis / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software
D011506:Proteins