The DEF data base of sequence based protein fold class predictions.
A new method for predicting protein fold-classes and protein domains from sequence data is constructed and used for generating a data base of protein fold-class assignments. Any given sequence of amino acids is assigned a specific prediction of one out of 45 typical protein fold-classes, a prediction of one out of 4 super fold-classes for the content of secondary structures and a profile of fold-class predictions along the sequence. The prediction accuracy for the super fold-classes is around 91% correct and 82% correct for the specific fold-classes. This accuracy is maintained down to a few percent of sequence identity.
Reczko
M
M
DKFZ-German Cancer Research Center, Heidelberg, Germany.
Bohr
H
H
D000595:Amino Acid Sequence; D016208:Databases, Factual; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D017421:Sequence Analysis; D012984:Software
D011506:Proteins