Improving the accuracy of protein secondary structure prediction using structural alignment

Background: The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3) of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence) database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences), the probability of a newly identified sequence having a structural homologue is actually quite high. Results: We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25%) onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based) secondary structure method...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Scott Montgomerie, Shan Sundararaj, Warren J. Gallin, David S. Wishart
• Keywords: BMCBI 2006, Protein Secondary Structure, Secondary Structure, Secondary Structure Prediction