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

Journal of Chemical Theory and Computation
Lucas S P Rudden, Matteo T Degiacomi

Abstract

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.

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Citations

Jan 30, 2021·Chem·Anna OlerinyovaPhilipp Kukura
Feb 27, 2021·Journal of Chemical Information and Modeling·Lucas S P Rudden, Matteo T Degiacomi
Mar 30, 2021·Computational and Structural Biotechnology Journal·Veronika Temml, Zsofia Kutil
Jun 20, 2020·Journal of Chemical Theory and Computation·Yue Cao, Yang Shen
Nov 18, 2021·The Protein Journal·Sharon Sunny, P B Jayaraj
Nov 19, 2021·Bioinformatics·Lucas S P RuddenMatteo T Degiacomi

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Methods Mentioned

BETA
NMR

Software Mentioned

HADDOCK
KaR
numpy
pyDock
PSO kick
PSO - KaR
GROMACS
er
JabberDock
POW

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