Effect of Secondary Structure Prediction on Protein Fold Recognition and Database Search

Abstract

Hydrophobic long-range interactions and local polypeptide chain propensities are the major factors directing protein folding. Incorporating both these terms in addition to the Dayhoff matrix helps us to increase quality of protein fold recognition via sequencestructure alignment. We have shown that the results of secondary structure prediction substantially increase a sensitivity of the fold recognition. To measure a performance of the protein fold recognition, we have developed a comprehensive test along with a set of the quality control scores based on the most populated structural families. With this test we have demonstrated improvement of the sequence alignment with consideration of the predicted secondary structure, even without knowledge of the real three-dimensional structure.