Template-based methods for predicting protein structure provide models for a significant portion of the protein but often contain insertions or chain ends (InsEnds) of indeterminate conformation. The local structure prediction problem entails modeling the InsEnds onto the rest of the protein. A well-known limit involves predicting loops of =12 residues in crystal structures. However, InsEnds may contain as many as ~50 amino acids, and the template-based model of the protein itself may be imperfect. To address these challenges, we present a free modeling method for predicting the local structure of loops and large InsEnds in both crystal structures and template-based models. The approach uses single amino acid torsional angle pivot moves of the protein backbone with a Cßlevel representation. Nevertheless, our accuracy for loops is comparable to existing methods. We also apply a more stringent test, the blind structure prediction and refinement categories of the CASP9 tournament, where we improve the quality of several homology based models by modeling InsEnds as long as 45 amino acids, sizes generally inaccessible to existing loop prediction methods. Our approach ranks as one of the best in the CASP9 refinement category that involves improving template-based models so that they can function as molecular replacement models to solve the phase problem for crystallographic structure determination.
We present a fully automated webserver for the prediction of lanthanide-binding peptide tag (LBT) insertions onto existing protein structures. The underlying method uses a coarse-grained backbone+Cb representation of the protein and samples on the backbone dihedral angles. We are able to successfully predict the proper conformation of the LBT tag with respect to the parent protein in existing fusion crystal structures. We further apply the method to predict the feasibility of LBT insertion on different sites on the parent protein and show qualitative agreement with the experimental observables. We report several metrics to assess the quality of LBT insertion in a specific site in a parent protein. We believe our method will serve as a useful computational tool for selecting reasonable sites in a given parent protein where the LBT insertion will likely be successful.