Toward optimal fragment generations for ab initio protein structure assembly
被引:170
作者:
Xu, Dong
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Univ Michigan, Dept Computat Med & Bioinformat, Ann Arbor, MI 48109 USAUniv Michigan, Dept Computat Med & Bioinformat, Ann Arbor, MI 48109 USA
Xu, Dong
[1
]
Zhang, Yang
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Univ Michigan, Dept Computat Med & Bioinformat, Ann Arbor, MI 48109 USA
Univ Michigan, Dept Biol Chem, Ann Arbor, MI 48109 USAUniv Michigan, Dept Computat Med & Bioinformat, Ann Arbor, MI 48109 USA
Zhang, Yang
[1
,2
]
机构:
[1] Univ Michigan, Dept Computat Med & Bioinformat, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Biol Chem, Ann Arbor, MI 48109 USA
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/. Proteins 2013. (C) 2012 Wiley Periodicals, Inc.
机构:
Univ Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
Handl, Julia
;
Knowles, Joshua
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Univ Manchester, Sch Comp Sci, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
Knowles, Joshua
;
Vernon, Robert
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Univ Washington, Dept Biochem, Seattle, WA 98195 USAUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
Vernon, Robert
;
Baker, David
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Univ Washington, Dept Biochem, Seattle, WA 98195 USAUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
Baker, David
;
Lovell, Simon C.
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机构:
Univ Manchester, Fac Life Sci, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
机构:
Univ Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
Handl, Julia
;
Knowles, Joshua
论文数: 0引用数: 0
h-index: 0
机构:
Univ Manchester, Sch Comp Sci, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
Knowles, Joshua
;
Vernon, Robert
论文数: 0引用数: 0
h-index: 0
机构:
Univ Washington, Dept Biochem, Seattle, WA 98195 USAUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
Vernon, Robert
;
Baker, David
论文数: 0引用数: 0
h-index: 0
机构:
Univ Washington, Dept Biochem, Seattle, WA 98195 USAUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
Baker, David
;
Lovell, Simon C.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Manchester, Fac Life Sci, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England