Sequence based residue depth prediction using evolutionary information and predicted secondary structure

Background: Residue depth allows determining how deeply a given residue is buried, in contrast to the solvent accessibility that differentiates between buried and solvent-exposed residues. When compared with the solvent accessibility, the depth allows studying deep-level structures and functional sites, and formation of the protein folding nucleus. Accurate prediction of residue depth would provide valuable information for fold recognition, prediction of functional sites, and protein design. Results: A new method, RDPred, for the real-value depth prediction from protein sequence is proposed. RDPred combines information extracted from the sequence, PSI-BLAST scoring matrices, and secondary structure predicted with PSIPRED. Threefold/ten-fold cross validation based tests performed on three independent, low-identity datasets show that the distance based depth (computed using MSMS) predicted by RDPred is characterized by 0.67/0.67, 0.66/0.67, and 0.64/0.65 correlation with the actual dept...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Hua Zhang, Tuo Zhang, Ke Chen 0003, Shiyi Shen, Jishou Ruan, Lukasz A. Kurgan
• Keywords: BMCBI 2008, Functional Sites, Mean Relative Errors, Solvent Accessibility