Sequence: Robust loop modeling using PyRosetta

The ability to predict the loop structure in a protein is useful in many studies, including homology modeling, protein design, and docking. There are significant challenges in obtaining high quality models as the loop length increases. The current research aims to overcome the challenges caused by the ruggedness of the energy landscape around a native protein structure, i.e. the presence of high-energy barriers immediately around the structure by locally manipulating the shape of the energy landscape during certain steps of the conformational search. It is noted that protein structure, especially the main chain conformation, often exhibits robustness against small sequence variations. For example, the structure of a mutant protein is often identical to that of wild type protein, except for the mutated residue. For the mutations that do not significantly change the main chain conformation, one may be free to perform the conformational search using either the original sequence or the mutant sequence. Once the main chain conformation has been modeled, the mutated amino acid can be reverted back to the original amino acid to successfully model the original structure. Although the native structure may be modeled using either approach, the latter method creates a possibility that a structure that is difficult to predict accurately using the wild type sequence because of the ruggedness of the energy landscape may be relatively easily modeled once the landscape has been temporarily smoothed through a transient mutation. We tested this strategy by modeling twenty 12 amino acid loops that have been the subject of prior studies. It was evidenced that the accuracy of loop modeling may be improved through judicious application of site directed mutation in the context of robotics based kinematic closure (KIC) method.