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BetaSearch: a new method for querying β-residue motifs

机译:BetaSearch:一种查询β残基基序的新方法

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Background Searching for structural motifs across known protein structures can be useful for identifying unrelated proteins with similar function and characterising secondary structures such as β -sheets. This is infeasible using conventional sequence alignment because linear protein sequences do not contain spatial information. β -residue motifs are β -sheet substructures that can be represented as graphs and queried using existing graph indexing methods, however, these approaches are designed for general graphs that do not incorporate the inherent structural constraints of β -sheets and require computationally-expensive filtering and verification procedures. 3D substructure search methods, on the other hand, allow β -residue motifs to be queried in a three-dimensional context but at significant computational costs. Findings We developed a new method for querying β -residue motifs, called BetaSearch, which leverages the natural planar constraints of β -sheets by indexing them as 2D matrices, thus avoiding much of the computational complexities involved with structural and graph querying. BetaSearch exhibits faster filtering, verification, and overall query time than existing graph indexing approaches whilst producing comparable index sizes. Compared to 3D substructure search methods, BetaSearch achieves 33 and 240 times speedups over index-based and pairwise alignment-based approaches, respectively. Furthermore, we have presented case-studies to demonstrate its capability of motif matching in sequentially dissimilar proteins and described a method for using BetaSearch to predict β -strand pairing. Conclusions We have demonstrated that BetaSearch is a fast method for querying substructure motifs. The improvements in speed over existing approaches make it useful for efficiently performing high-volume exploratory querying of possible protein substructural motifs or conformations. BetaSearch was used to identify a nearly identical β -residue motif between an entirely synthetic (Top7) and a naturally-occurring protein (Charcot-Leyden crystal protein), as well as identifying structural similarities between biotin-binding domains of avidin, streptavidin and the lipocalin gamma subunit of human C8.
机译:背景技术跨已知蛋白质结构搜索结构基序可用于鉴定具有相似功能的无关蛋白质并表征二级结构,例如β-折叠。使用常规序列比对是不可能的,因为线性蛋白质序列不包含空间信息。 β-残基基序是β-sheet子结构,可以表示为图并使用现有的图索引方法查询,但是,这些方法是为不包含β-sheet固有结构约束且需要计算昂贵的过滤的一般图设计的和验证程序。另一方面,3D子结构搜索方法允许在3维上下文中查询β残基基元,但计算量较大。结果我们开发了一种查询β残基基序的新方法,称为BetaSearch,它通过将β折叠的自然平面约束索引为2D矩阵来利用它们,从而避免了结构和图形查询所涉及的许多计算复杂性。 BetaSearch具有比现有的图形索引方法更快的筛选,验证和整体查询时间,同时可产生可比较的索引大小。与3D子结构搜索方法相比,BetaSearch的速度分别比基于索引的方法和基于成对对齐的方法快33倍和240倍。此外,我们已经提供了案例研究,以证明其在相异蛋白质中的基序匹配能力,并描述了使用BetaSearch预测β链配对的方法。结论我们已经证明BetaSearch是查询子结构基序的快速方法。与现有方法相比,速度的提高使它对于有效执行可能的蛋白质亚结构基序或构象的大规模探索性查询很有用。 BetaSearch用于鉴定完全合成的(Top7)与天然存在的蛋白质(夏科特莱登晶体蛋白)之间几乎相同的β-残基基序,以及鉴定抗生物素蛋白,链霉亲和素和抗生物素蛋白的生物素结合结构域之间的结构相似性。人C8的lipocalinγ亚基。

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