title: Near-native structure refinement using in vacuo energy minimization.
abstract: One of the greatest shortcomings of macromolecular energy minimization and molecular dynamics techniques is that they generally do not preserve the native structure of proteins as observed by x-ray crystallography. This deformation of the native structure means that these methods are not generally used to refine structures produced by homology-modeling techniques. Here, we use a database of 75 proteins to test the ability of a variety of popular molecular mechanics force fields to maintain the native structure. Minimization from the native structure is a weak test of potential energy functions: It is complemented by a much stronger test in which the same methods are compared for their ability to attract a near-native decoy protein structure toward the native structure. We use a powerfully convergent energy-minimization method and show that, of the traditional molecular mechanics potentials tested, only one showed a modest net improvement over a large data set of structurally diverse proteins. A smooth, differentiable knowledge-based pairwise atomic potential performs better on this test than traditional potential functions. This work is expected to have important implications for protein structure refinement, homology modeling, and structure prediction.
authors.affiliation: Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305-5126, USA.
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Summa
authors.forename: Michael
authors.initials: M
authors.lastname: Levitt
mesh_terms: D001703:Biophysics / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D004735:Energy Transfer / Q000502:physiology; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins