β-sheet topology prediction with high precision and recall for β and mixed αβ proteinsβ-sheet拓扑预测精度高和召回β和混合αβ蛋白质.pdf

b -sheet Topology Prediction with High Precision and Recall for b and Mixed a/b Proteins Ashwin Subramani, Christodoulos A. Floudas* Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, United States of America Abstract The prediction of the correct b-sheet topology for pure b and mixed a=b 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 b-sheet topology in b and mixed a=b 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 b-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 b and mixed a=b 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 b-sheet topology prediction for blind targets provided during the CASP8 and CASP9 experiments, as well as for actual and predicted secondary structures. The b-sheet topology prediction algorithm, BeST, is available to the scientific community at http:// /BeST/. Citation: Subramani A, Floudas CA (2012) b-