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 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.

Mass Photometry of Membrane Proteins

“…To test the feasibility of dimer occurrence, we further explored the bo 3 dimer structure using protein-protein docking in conjunction with molecular dynamics. 20 We simulated the monomer (PDB: 1FFT) 21 in a 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) bilayer for 60 ns, and used this equilibrated structure to generate a pool of possible dimeric arrangements (best candidate is shown in Figure 2C). We then calculated the transmembrane solvent-accessible surface area (SASA) of monomeric bo 3 (21,800 Å 2 ).…”

Transmembrane Protein Docking with JabberDock

“… 21 GROMACS 22 is then used to generate the simulation data using the Amber14SB 23 and SLipid 24 force fields, which enables the generation of STID maps. The maps of both binding partners are then converted into isosurfaces using a predetermined cutoff and docked such that their surface complementarity is maximized 16 (see SI and Figure S2 ). This surface-based scoring function is effective because it bypasses the need to explicitly handle packing of interfacial atoms, yielding smoother and gentler gradients compared to typical atomistic representations (see SI and Figure S3 ).…”

“…Some proteins can form multiple complexes by interacting with different binding partners. In our previous work, 16 we observed that knowledge of a protein’s bound state with a specific partner may facilitate its docking with a different one; i.e., the bound state of the native complex from which the ligand or receptor is sourced can be used as a surrogate for the target complex. Here, we tested this approach with the 1M56 test case, comprised of two binding partners that have had their structures solved as part of an alternative complex.…”

“…We recently released our protein–protein docking software, JabberDock, 16 after testing it against a standard benchmark of 226 soluble complexes developed by the CAPRI community. 17 It obtained a greater than 54% success rate, with the notable achievement that the flexibility of the individual structures made little difference to its overall success.…”

Structure-based molecular modeling in SAR analysis and lead optimization

“…In the most basic approaches, the protein is simply seen as a surface, which is enhanced by electrostatic properties [7] . Such approaches are still in use for protein–protein docking, where a more complex representation is not feasible [8] . In protein-ligand docking, the selected binding site is represented in more detail.…”