Protein fragment reconstruction using various modeling techniques

被引:68
作者
Boniecki, M
Rotkiewicz, P
Skolnick, J
Kolinski, A
机构
[1] Warsaw Univ, Fac Chem, Lab Theory Biopolymers, PL-02093 Warsaw, Poland
[2] SUNY Buffalo, Ctr Excellence Bioinformat, Buffalo, NY 14203 USA
基金
美国国家卫生研究院;
关键词
comparative modeling; loop modeling; Monte Carlo sampling; protein structure prediction; reduced protein models;
D O I
10.1023/B:JCAM.0000017486.83645.a0
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
Recently developed reduced models of proteins with knowledge-based force fields have been applied to a specific case of comparative modeling. From twenty high resolution protein structures of various structural classes, significant fragments of their chains have been removed and treated as unknown. The remaining portions of the structures were treated as fixed - i.e., as templates with an exact alignment. Then, the missed fragments were reconstructed using several modeling tools. These included three reduced types of protein models: the lattice SICHO ( Side Chain Only) model, the lattice CABS (Calpha + Cbeta + Side group) model and an off-lattice model similar to the CABS model and called REFINER. The obtained reduced models were compared with more standard comparative modeling tools such as MODELLER and the SWISS-MODEL server. The reduced model results are qualitatively better for the higher resolution lattice models, clearly suggesting that these are now mature, competitive and complementary ( in the range of sparse alignments) to the classical tools of comparative modeling. Comparison between the various reduced models strongly suggests that the essential ingredient for the sucessful and accurate modeling of protein structures is not the representation of conformational space ( lattice, off-lattice, all-atom) but, rather, the specificity of the force fields used and, perhaps, the sampling techniques employed. These conclusions are encouraging for the future application of the fast reduced models in comparative modeling on a genomic scale.
引用
收藏
页码:725 / 738
页数:14
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