title: β-sheet topology prediction with high precision and recall for β and mixed α/β proteins.
abstract: The prediction of the correct β-sheet topology for pure β and mixed α/β proteins is a critical intermediate step toward the three dimensional protein structure prediction. The predicted beta sheet topology provides distance constraints between sequentially separated residues, which reduces the three dimensional search space for a protein structure prediction algorithm. Here, we present a novel mixed integer linear optimization based framework for the prediction of β-sheet topology in β and mixed α/β proteins. The objective is to maximize the total strand-to-strand contact potential of the protein. A large number of physical constraints are applied to provide biologically meaningful topology results. The formulation permits the creation of a rank-ordered list of preferred β-sheet arrangements. Finally, the generated topologies are re-ranked using a fully atomistic approach involving torsion angle dynamics and clustering. For a large, non-redundant data set of 2102 β and mixed α/β proteins with at least 3 strands taken from the PDB, the proposed approach provides the top 5 solutions with average precision and recall greater than 78%. Consistent results are obtained in the β-sheet topology prediction for blind targets provided during the CASP8 and CASP9 experiments, as well as for actual and predicted secondary structures. The β-sheet topology prediction algorithm, BeST, is available to the scientific community at http://selene.princeton.edu/BeST/.
authors.affiliation: Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, United States of America.
authors.forename: Ashwin
authors.initials: A
authors.lastname: Subramani
authors.forename: Christodoulos A
authors.initials: CA
authors.lastname: Floudas
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D008956:Models, Chemical; D008958:Models, Molecular; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins