Protein Docking Using a Single Representation for Protein Surface, Electrostatics, and Local Dynamics

Predicting
the assembly of multiple proteins into specific complexes
is critical to understanding their biological function in an organism
and thus the design of drugs to address their malfunction. Proteins
are flexible molecules, which inherently pose 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 can accurately and robustly predict difficult target complexes
with an average success rate of >54%, which is comparable to or
greater
than the currently available methods.