title: A coarse-grained Langevin molecular dynamics approach to de novo protein structure prediction.
abstract: De novo prediction of protein structures, the prediction of structures from amino acid sequences which are not similar to those of hitherto resolved structures, has been one of the major challenges in molecular biophysics. In this paper, we develop a new method of de novo prediction, which combines the fragment assembly method and the simulation of physical folding process: structures which have consistently assembled fragments are dynamically searched by Langevin molecular dynamics of conformational change. The benchmarking test shows that the prediction is improved when the candidate structures are cross-checked by an empirically derived score function.
authors.affiliation: Department of Computational Science and Engineering, Nagoya University, Furocho, Chikusa, Nagoya 464-8603, Japan.
authors.forename: Takeshi N
authors.initials: TN
authors.lastname: Sasaki
authors.forename: Hikmet
authors.initials: H
authors.lastname: Cetin
authors.forename: Masaki
authors.initials: M
authors.lastname: Sasai
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins