High-Resolution Comparative Modeling with RosettaCM

被引:792
|
作者
Song, Yifan [1 ]
DiMaio, Frank [1 ]
Wang, Ray Yu-Ruei [1 ]
Kim, David [1 ]
Miles, Chris [1 ]
Brunette, T. J. [1 ]
Thompson, James [1 ]
Baker, David [1 ,2 ]
机构
[1] Univ Washington, Dept Biochem, Seattle, WA 98195 USA
[2] Univ Washington, Howard Hughes Med Inst, Seattle, WA 98195 USA
基金
美国国家卫生研究院;
关键词
COMPUTATIONAL DESIGN; STRUCTURE PREDICTION; PROTEINS; ENERGY; INFORMATION; CASP8;
D O I
10.1016/j.str.2013.08.005
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
We describe an improved method for comparative modeling, RosettaCM, which optimizes a physically realistic all-atom energy function over the conformational space defined by homologous structures. Given a set of sequence alignments, RosettaCM assembles topologies by recombining aligned segments in Cartesian space and building unaligned regions de novo in torsion space. The junctions between segments are regularized using a loop closure method combining fragment superposition with gradient-based minimization. The energies of the resulting models are optimized by all-atom refinement, and the most representative low-energy model is selected. The CASP10 experiment suggests that RosettaCM yields models with more accurate side-chain and backbone conformations than other methods when the sequence identity to the templates is greater than similar to 15%.
引用
收藏
页码:1735 / 1742
页数:8
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