title: Identification of protein-protein interaction sites from docking energy landscapes.
abstract: Protein recognition is one of the most challenging and intriguing problems in structural biology. Despite all the available structural, sequence and biophysical information about protein-protein complexes, the physico-chemical patterns, if any, that make a protein surface likely to be involved in protein-protein interactions, remain elusive. Here, we apply protein docking simulations and analysis of the interaction energy landscapes to identify protein-protein interaction sites. The new protocol for global docking based on multi-start global energy optimization of an all-atom model of the ligand, with detailed receptor potentials and atomic solvation parameters optimized in a training set of 24 complexes, explores the conformational space around the whole receptor without restrictions. The ensembles of the rigid-body docking solutions generated by the simulations were subsequently used to project the docking energy landscapes onto the protein surfaces. We found that highly populated low-energy regions consistently corresponded to actual binding sites. The procedure was validated on a test set of 21 known protein-protein complexes not used in the training set. As much as 81% of the predicted high-propensity patch residues were located correctly in the native interfaces. This approach can guide the design of mutations on the surfaces of proteins, provide geometrical details of a possible interaction, and help to annotate protein surfaces in structural proteomics.
authors.affiliation: Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA.
authors.forename: Juan
authors.initials: J
authors.lastname: Fernández-Recio
authors.forename: Maxim
authors.initials: M
authors.lastname: Totrov
authors.forename: Ruben
authors.initials: R
authors.lastname: Abagyan
mesh_terms: D001665:Binding Sites; D003198:Computer Simulation; D005103:Expert Systems; D008958:Models, Molecular; D009010:Monte Carlo Method; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins