The automatic detection of known beta-propeller structural motifs from protein tertiary structure

Following our previous work on the analysis of 'structural plasticity' associated with the beta-propeller structural motifs, we have now developed a simple method that can automatically detect all the known beta-propellers in protein tertiary structure, given a list of Protein Data Bank (PDB) codes as input to the computer program. Our beta-propeller detection (BPD) method identifies the location of beta-propellers in the protein structure, specifies the beta-propeller type, the beta-sheet associated beta-strand pattern and the structurally similar beta-propellers observed in other proteins. When tested on 21,566 proteins in the PDB, the BPD method was capable of correctly identifying all the known 245 beta-propellers described in the structural classification of proteins (SCOP) with the number of false positives detected being less than 0.2%. Forty-one false positives were detected that correspond to eight known protein families. When compared with some of the popular web-based programs that can automatically detect 'structural similarities' between the query and target proteins, our method has the advantage of also being capable of detecting beta-propellers associated with 'structural plasticity' and in situations where the target and query proteins differ in amino acid sequence length.