Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure in

Background: Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio. Results: Here we develop high-throughput machine learning systems for the prediction of protein secondary structure and solvent accessibility that exploit homology to proteins of known structure, where available, in the form of simple structural frequency profiles extracted from sets of PDB templates. We compare these systems to their state-of-the-art ab initio counterparts, and with a number of baselines in which secondary structures and ...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Gianluca Pollastri, Alberto J. M. Martin, Catherine Mooney, Alessandro Vullo
• Keywords: BMCBI 2007, Prediction, Secondary Structure, Solvent Accessibility