Prediction of Protein Secondary Structure from PDB Structure Information Based on Sequence Segments Homology Searching

In this paper, a novel method to predict protein secondary structure (e.g., helix, beta-sheet and coil) is described. Our method predicts the secondary structure for a query sequence using a segment-wise similarity search, which finds the most probable secondary structure based on similarities between a set of sequence segments of a query sequence and our segment databases: the segment sequence DB and the segment structure DB. The important points concerning our system are: (i) capability of visualizing evidence for the prediction of a query sequence, (ii) higher prediction accuracy in regard to beta-sheet than those of existing methods. Since the existing test set (e.g., the RD126 set) is not applicable to our system for performance evaluation, we used an original blind test set (similar to CASP) which included 355 non-homologous protein chains. The performance of our system yields a 76.9% accuracy of secondary structure prediction which is up to 20% greater than other prediction methods.