title: Evidence of conformational selection driving the formation of ligand binding sites in protein-protein interfaces.
abstract: Many protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study. The measures used for structure comparison are based on detecting binding hot spots, i.e., protein regions that are major contributors to the binding free energy. The main tool of the analysis is computational solvent mapping, which explores the surface of proteins by docking a large number of small "probe" molecules. Although we consider conformational ensembles obtained by NMR techniques, the analysis is independent of the method used for generating the structures. Finding the energetically most important regions, mapping can identify binding site residues using ligand-free models based on NMR data. In addition, the method selects conformations that are similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. This agrees with the conformational selection model of molecular recognition, which assumes such pre-existing conformations. The analysis also shows the maximum level of similarity between unbound and bound states that is achieved without any influence from a ligand. Further shift toward the bound structure assumes protein-peptide or protein-ligand interactions, either selecting higher energy conformations that are not part of the NMR ensemble, or leading to induced fit. Thus, forming the sites in protein-protein interfaces that bind peptides and can be targeted by small ligands always includes conformational selection, although other recognition mechanisms may also be involved.
authors.affiliation: Program in Bioinformatics, Boston University, Boston, Massachusetts, United States of America.
authors.forename: Tanggis
authors.initials: T
authors.lastname: Bohnuud
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.
authors.forename: Dima
authors.initials: D
authors.lastname: Kozakov
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America; Department of Chemistry, Boston University, Boston, Massachusetts, United States of America.
authors.forename: Sandor
authors.initials: S
authors.lastname: Vajda
mesh_terms: D001665:Binding Sites; D019295:Computational Biology; D030562:Databases, Protein; D008958:Models, Molecular; D019906:Nuclear Magnetic Resonance, Biomolecular; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D011506:Proteins