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多聚体 threading 和模板重组预测蛋白质-蛋白质复合物结构。

Protein-protein complex structure predictions by multimeric threading and template recombination.

机构信息

Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA.

出版信息

Structure. 2011 Jul 13;19(7):955-66. doi: 10.1016/j.str.2011.04.006.

Abstract

The total number of protein-protein complex structures currently available in the Protein Data Bank (PDB) is six times smaller than the total number of tertiary structures in the PDB, which limits the power of homology-based approaches to complex structure modeling. We present a threading-recombination approach, COTH, to boost the protein complex structure library by combining tertiary structure templates with complex alignments. The query sequences are first aligned to complex templates using a modified dynamic programming algorithm, guided by ab initio binding-site predictions. The monomer alignments are then shifted to the multimeric template framework by structural alignments. COTH was tested on 500 nonhomologous dimeric proteins, which can successfully detect correct templates for 50% of the cases after homologous templates are excluded, which significantly outperforms conventional homology modeling algorithms. It also shows a higher accuracy in interface modeling than rigid-body docking of unbound structures from ZDOCK although with lower coverage. These data demonstrate new avenues to model complex structures from nonhomologous templates.

摘要

目前蛋白质数据库(PDB)中可用的蛋白质-蛋白质复合物结构总数比 PDB 中的三级结构总数小六倍,这限制了基于同源性的方法对复合物结构建模的能力。我们提出了一种基于串联重组的方法 COTH,通过将三级结构模板与复合物比对相结合,来增强蛋白质复合物结构库。首先使用一种改进的动态规划算法,根据从头预测的结合位点对查询序列进行与复合物模板的比对。然后通过结构比对将单体比对转移到多聚体模板框架中。COTH 在 500 个非同源二聚体蛋白上进行了测试,在排除同源模板后,正确模板的检测成功率为 50%,明显优于传统的同源建模算法。它在界面建模方面的准确性也高于未结合结构的刚体对接,尽管覆盖率较低。这些数据表明了从非同源模板建模复合物结构的新途径。

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