Protein docking using a single representation for protein surface, electrostatics and local dynamics.

Abstract

Predicting the assembly of multiple proteins into specific complexes is critical to the understanding of their biological function in an organism, and thus the design of drugs to address their malfunction. Proteins are flexible molecules, and this inherently poses a problem to any protein docking computational method, where even a simple rearrangement of the side chain and backbone atoms at the interface of binding partners complicates the successful determination of the correct docked pose. Herein, we present a means of representing protein surface, electrostatics and local dynamics within a single volumetric descriptor. We show that our representations can be physically related to the surface accessible solvent area and mass of the protein. We then demonstrate that the application of this representation into a protein-protein docking scenario bypasses the need to compensate for, and predict, specific side chain packing at the interface of binding partners. This representation is leveraged in our de novo protein docking software, JabberDock, which we show can accurately and robustly predict difficult target complexes with an average success rate of >54%, which is comparable to or greater than currently available methods.