title: Toward optimal fragment generations for ab initio protein structure assembly.
abstract: Fragment assembly using structural motifs excised from other solved proteins has shown to be an efficient method for ab initio protein-structure prediction. However, how to construct accurate fragments, how to derive optimal restraints from fragments, and what the best fragment length is are the basic issues yet to be systematically examined. In this work, we developed a gapless-threading method to generate position-specific structure fragments. Distance profiles and torsion angle pairs are then derived from the fragments by statistical consistency analysis, which achieved comparable accuracy with the machine-learning-based methods although the fragments were taken from unrelated proteins. When measured by both accuracies of the derived distance profiles and torsion angle pairs, we come to a consistent conclusion that the optimal fragment length for structural assembly is around 10, and at least 100 fragments at each location are needed to achieve optimal structure assembly. The distant profiles and torsion angle pairs as derived by the fragments have been successfully used in QUARK for ab initio protein structure assembly and are provided by the QUARK online server at http://zhanglab.ccmb. med.umich.edu/QUARK/.
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA.
authors.forename: Dong
authors.initials: D
authors.lastname: Xu
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D001185:Artificial Intelligence; D053453:Caspase 9 / Q000737:chemistry / Q000378:metabolism; D030562:Databases, Protein; D008958:Models, Molecular; D010446:Peptide Fragments / Q000737:chemistry / Q000378:metabolism; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D010446:Peptide Fragments; D011506:Proteins; C506433:CASP9 protein, human; D053453:Caspase 9