title: Residue-level global and local ensemble-ensemble comparisons of protein domains.
abstract: Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a "consistency check" of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons.
authors.affiliation: Department of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon, 97331.
authors.forename: Sarah A
authors.initials: SA
authors.lastname: Clark
authors.affiliation: Department of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon, 97331.
authors.forename: Dale E
authors.initials: DE
authors.lastname: Tronrud
authors.affiliation: Department of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon, 97331.
authors.forename: P Andrew
authors.initials: PA
authors.lastname: Karplus
mesh_terms: D019295:Computational Biology / Q000379:methods*; D018360:Crystallography, X-Ray; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D008958:Models, Molecular; D011487:Protein Conformation; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins
keywords: NMR ensemble; Rosetta; force field optimization; homology modeling; protein comparisons; structure prediction; structure validation; superposition; template-based modeling