title: Detecting the native ligand orientation by interfacial rigidity: SiteInterlock.
abstract: Understanding the physical attributes of protein-ligand interfaces, the source of most biological activity, is a fundamental problem in biophysics. Knowing the characteristic features of interfaces also enables the design of molecules with potent and selective interactions. Prediction of native protein-ligand interactions has traditionally focused on the development of physics-based potential energy functions, empirical scoring functions that are fit to binding data, and knowledge-based potentials that assess the likelihood of pairwise interactions. Here we explore a new approach, testing the hypothesis that protein-ligand binding results in computationally detectable rigidification of the protein-ligand interface. Our SiteInterlock approach uses rigidity theory to efficiently measure the relative interfacial rigidity of a series of small-molecule ligand orientations and conformations for a number of protein complexes. In the majority of cases, SiteInterlock detects a near-native binding mode as being the most rigid, with particularly robust performance relative to other methods when the ligand-free conformation of the protein is provided. The interfacial rigidification of both the protein and ligand prove to be important characteristics of the native binding mode. This measure of rigidity is also sensitive to the spatial coupling of interactions and bond-rotational degrees of freedom in the interface. While the predictive performance of SiteInterlock is competitive with the best of the five other scoring functions tested, its measure of rigidity encompasses cooperative rather than just additive binding interactions, providing novel information for detecting native-like complexes. SiteInterlock shows special strength in enhancing the prediction of native complexes by ruling out inaccurate poses. Proteins 2016; 84:1888-1901. © 2016 Wiley Periodicals, Inc.
authors.affiliation: Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, 48824, USA.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Raschka
authors.affiliation: Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, 48824, USA.
authors.forename: Joseph
authors.initials: J
authors.lastname: Bemister-Buffington
authors.affiliation: Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, 48824, USA.|Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, 48824, USA.
authors.forename: Leslie A
authors.initials: LA
authors.lastname: Kuhn
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D030562:Databases, Protein; D008024:Ligands; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012107:Research Design; D054852:Small Molecule Libraries / Q000737:chemistry*; D013499:Surface Properties
chemical_list: D008024:Ligands; D011506:Proteins; D054852:Small Molecule Libraries
keywords: ProFlex; binding determinants; binding mode prediction; coupled interactions; docking; flexibility; interface features; ligand stabilization of proteins; protein stability; scoring functions