Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA.
Proteins. 2013 Feb;81(2):229-39. doi: 10.1002/prot.24179. Epub 2012 Oct 16.
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/.
利用从其他已解决蛋白质中切除的结构模体进行片段组装已被证明是从头预测蛋白质结构的有效方法。然而,如何构建准确的片段,如何从片段中推导出最佳约束,以及最佳的片段长度是尚未系统研究的基本问题。在这项工作中,我们开发了一种无间隙穿线方法来生成位置特异性结构片段。然后通过统计一致性分析从片段中推导出距离分布和扭转角对,尽管片段取自不相关的蛋白质,但它们的准确性可与基于机器学习的方法相媲美。通过对推导的距离分布和扭转角对的准确性进行测量,我们得出了一致的结论,即结构组装的最佳片段长度约为 10,并且每个位置至少需要 100 个片段才能实现最佳结构组装。由片段推导的距离分布和扭转角对已成功用于 QUARK 进行从头蛋白质结构组装,并可在 http://zhanglab.ccmb. med.umich.edu/QUARK/ 上的 QUARK 在线服务器获得。