Protein-protein docking is the prediction of the structure of the complex, given the structures of the individual proteins. In the heart of the docking methodology is the notion of steric and physicochemical complementarity at the protein-protein interface. Protein–protein interactions are involved in every cellular process, and their characterization is therefore critical to understanding the underlying molecular mechanisms.
The prediction of protein–protein complexes from the structures of unbound components is a challenging and powerful strategy to decipher the mechanism of many essential biological processes.
In protein-protein docking, the similarity between proteins in complexes can be assessed through comparison/alignment of sequences, sequences and structures (threading) or just the structures because the structures of the protein to be docked are assumed to be known by the very definition of docking. However, the protein docking field, as opposed to the prediction of individual proteins, largely has not been taking advantage of the template-based modeling.
Protein-docking is a molecular modeling problem which aims to predict, with computer science algorithms and techniques, the mutual orientation and position of two molecules forming a complex. One of the molecules is a protein, the other could be another protein, a nucleic acid chain or a smaller molecule. Points to be noted in docking are;
Geometrical shape of molecules
binding affinity calculated through scoring functions
flexibility/rigidity of the backbone
Protein-protein docking methods, which are based on a variety of selection criteria and exhaustive searches of the spatial interaction between two proteins by matching local complementary features on their surfaces, have also been applied to GPCRs in an effort to predict dimerization/oligomerization interfaces.
The HDOCK server
The ClusPro server
A protein–protein docking approach has been developed based on a reduced protein representation with up to three pseudo atoms per amino acid residue. Docking is performed by energy minimization in rotational and translational degrees of freedom. The reduced protein representation allows an efficient search for docking minima on the protein surfaces within. During docking, an effective energy function between pseudo atoms has been used based on amino acid size and physico-chemical character. Energy minimization of protein test complexes in the reduced representation results in geometries close to experiment with backbone root mean square deviations (RMSDs) of ~1 to 3 Å for the mobile protein partner from the experimental geometry. For most test cases, the energy-minimized experimental structure scores among the top five energy minima in systematic docking studies when using both partners in their bound conformations. To account for side-chain conformational changes in case of using unbound protein conformations, a multicopy approach has been used to select the most favorable side-chain conformation during the docking process. The multicopy approach significantly improves the docking performance, using unbound binding partners without a significant increase in computer time. For most docking test systems using unbound partners, and without accounting for any information about the known binding geometry, a solution within ~2 to 3.5 Å RMSD of the full mobile partner from the experimental geometry was found among the 40 top-scoring complexes. The approach could be extended to include protein loop flexibility, and might also be useful for docking of modeled protein structures.