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通过识别局部表面相似性进行功能注释:一种用于结构基因组学的新工具。

Functional annotation by identification of local surface similarities: a novel tool for structural genomics.

作者信息

Ferrè Fabrizio, Ausiello Gabriele, Zanzoni Andreas, Helmer-Citterich Manuela

机构信息

Boston College, Biology Department, Chestnut Hill MA, USA.

出版信息

BMC Bioinformatics. 2005 Aug 2;6:194. doi: 10.1186/1471-2105-6-194.

Abstract

BACKGROUND

Protein function is often dependent on subsets of solvent-exposed residues that may exist in a similar three-dimensional configuration in non homologous proteins thus having different order and/or spacing in the sequence. Hence, functional annotation by means of sequence or fold similarity is not adequate for such cases.

RESULTS

We describe a method for the function-related annotation of protein structures by means of the detection of local structural similarity with a library of annotated functional sites. An automatic procedure was used to annotate the function of local surface regions. Next, we employed a sequence-independent algorithm to compare exhaustively these functional patches with a larger collection of protein surface cavities. After tuning and validating the algorithm on a dataset of well annotated structures, we applied it to a list of protein structures that are classified as being of unknown function in the Protein Data Bank. By this strategy, we were able to provide functional clues to proteins that do not show any significant sequence or global structural similarity with proteins in the current databases.

CONCLUSION

This method is able to spot structural similarities associated to function-related similarities, independently on sequence or fold resemblance, therefore is a valuable tool for the functional analysis of uncharacterized proteins. Results are available at http://cbm.bio.uniroma2.it/surface/structuralGenomics.html.

摘要

背景

蛋白质功能通常依赖于溶剂暴露残基的子集,这些残基在非同源蛋白质中可能以相似的三维构型存在,因此在序列中具有不同的顺序和/或间距。因此,对于此类情况,通过序列或折叠相似性进行功能注释是不够的。

结果

我们描述了一种通过与带注释的功能位点库检测局部结构相似性来对蛋白质结构进行功能相关注释的方法。使用自动程序注释局部表面区域的功能。接下来,我们采用一种不依赖序列的算法,将这些功能片段与大量蛋白质表面空洞进行详尽比较。在一个注释良好的结构数据集上对该算法进行调整和验证后,我们将其应用于蛋白质数据库中分类为功能未知的蛋白质结构列表。通过这种策略,我们能够为那些与当前数据库中的蛋白质没有任何显著序列或全局结构相似性的蛋白质提供功能线索。

结论

该方法能够识别与功能相关相似性相关的结构相似性,而不依赖于序列或折叠相似性,因此是未表征蛋白质功能分析的有价值工具。结果可在http://cbm.bio.uniroma2.it/surface/structuralGenomics.html获取。

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