Automatic prediction of flexible regions improves the accuracy of protein-protein docking models

Computational models of protein-protein docking that incorporate backbone flexibility can predict perturbations of the backbone and side chains during docking and produce protein interaction models with atomic accuracy. Most previous models usually predefine flexible regions by visually comparing the bound and unbound structures. In this paper, we propose a general method to automatically identify the flexible hinges for domain assembly and the flexible loops for loop refinement, in addition to predicting the corresponding movements of the identified active residues. We conduct experiments to evaluate performance of our approach on two test sets. Comparison of results on test set I between algorithms with and without prediction of flexible regions demonstrate the superior recovery of energy funnels in many target interactions using the new loop refinement model. In addition, our decoys are superior for each target. Indeed, the total number of satisfactory models is almost double that of other programs. The results on test set II docking tests produced by our domain assembly method also show encouraging results. Of the three targets examined, one exhibits energy funnel and the best models of the other two targets all meet the conditions of acceptable accuracy. Results demonstrate that the automatic prediction of flexible backbone regions can greatly improve the performance of protein-protein docking models.