title: Improving the physical realism and structural accuracy of protein models by a two-step atomic-level energy minimization.
abstract: Most protein structural prediction algorithms assemble structures as reduced models that represent amino acids by a reduced number of atoms to speed up the conformational search. Building accurate full-atom models from these reduced models is a necessary step toward a detailed function analysis. However, it is difficult to ensure that the atomic models retain the desired global topology while maintaining a sound local atomic geometry because the reduced models often have unphysical local distortions. To address this issue, we developed a new program, called ModRefiner, to construct and refine protein structures from Cα traces based on a two-step, atomic-level energy minimization. The main-chain structures are first constructed from initial Cα traces and the side-chain rotamers are then refined together with the backbone atoms with the use of a composite physics- and knowledge-based force field. We tested the method by performing an atomic structure refinement of 261 proteins with the initial models constructed from both ab initio and template-based structure assemblies. Compared with other state-of-art programs, ModRefiner shows improvements in both global and local structures, which have more accurate side-chain positions, better hydrogen-bonding networks, and fewer atomic overlaps. ModRefiner is freely available at http://zhanglab.ccmb.med.umich.edu/ModRefiner.
authors.affiliation: Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Dong
authors.initials: D
authors.lastname: Xu
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D013816:Thermodynamics
chemical_list: D011506:Proteins
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