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首页> 外文期刊>Journal of Molecular Biology >Characterizing the existing and potential structural space of proteins by large-scale multiple loop permutations.
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Characterizing the existing and potential structural space of proteins by large-scale multiple loop permutations.

机译：通过大规模的多环置换来表征蛋白质的现有和潜在结构空间。

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Worldwide structural genomics projects are increasing structure coverage of sequence space but have not significantly expanded the protein structure space itself (i.e., number of unique structural folds) since 2007. Discovering new structural folds experimentally by directed evolution and random recombination of secondary-structure blocks is also proved rarely successful. Meanwhile, previous computational efforts for large-scale mapping of protein structure space are limited to simple model proteins and led to an inconclusive answer on the completeness of the existing observed protein structure space. Here, we build novel protein structures by extending naturally occurring circular (single-loop) permutation to multiple loop permutations (MLPs). These structures are clustered by structural similarity measure called TM-score. The computational technique allows us to produce different structural clusters on the same naturally occurring, packed, stable core but with alternatively connected secondary-structure segments. A large-scale MLP of 2936 domains from structural classification of protein domains reproduces those existing structural clusters (63%) mostly as hubs for many nonredundant sequences and illustrates newly discovered novel clusters as islands adopted by a few sequences only. Results further show that there exist a significant number of novel potentially stable clusters for medium-size or large-size single-domain proteins, in particular, >100 amino acid residues, that are either not yet adopted by nature or adopted only by a few sequences. This study suggests that MLP provides a simple yet highly effective tool for engineering and design of novel protein structures (including naturally knotted proteins). The implication of recovering new-fold targets from critical assessment of structure prediction techniques (CASP) by MLP on template-based structure prediction is also discussed. Our MLP structures are available for download at the publication page of the Web site http://sparks.informatics.iupui.edu.
机译：自2007年以来，全球结构基因组计划正在增加序列空间的结构覆盖范围，但并未显着扩展蛋白质结构空间本身（即独特结构折叠的数量）。通过定向进化和二级结构嵌段的随机重组，实验性地发现新的结构折叠是也被证明很少成功。同时，先前对蛋白质结构空间进行大规模作图的计算工作仅限于简单模型蛋白质，并导致对现有观察到的蛋白质结构空间的完整性无法得出结论。在这里，我们通过将自然发生的圆形（单环）置换扩展到多个环置换（MLP）来构建新颖的蛋白质结构。这些结构通过称为TM得分的结构相似性度量进行聚类。计算技术使我们能够在相同的自然发生，堆积，稳定的岩心上产生不同的结构簇，但具有交替连接的二级结构段。从蛋白质结构域的结构分类中对2936个结构域进行的大规模MLP再现了那些现有的结构簇（63％），主要是许多非冗余序列的集线器，并说明了新发现的新颖簇，仅被少数序列采用。结果进一步表明，对于中型或大型单域蛋白，尤其是> 100个氨基酸残基，存在大量新颖的潜在稳定簇，它们要么尚未被自然界采用，要么仅被少数人采用序列。这项研究表明，MLP为工程和设计新型蛋白质结构（包括天然打结的蛋白质）提供了一个简单而高效的工具。还讨论了通过MLP从结构预测技术（CASP）的关键评估中恢复新目标对基于模板的结构预测的意义。我们的MLP结构可从以下网站的发布页面下载：http://sparks.informatics.iupui.edu。

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