Fine tuned exploration of evolutionary relationships within the protein universe.

IF 0.8 4区 数学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Danilo Gullotto
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引用次数: 0

Abstract

In the regime of domain classifications, the protein universe unveils a discrete set of folds connected by hierarchical relationships. Instead, at sub-domain-size resolution and because of physical constraints not necessarily requiring evolution to shape polypeptide chains, networks of protein motifs depict a continuous view that lies beyond the extent of hierarchical classification schemes. A number of studies, however, suggest that universal sub-sequences could be the descendants of peptides emerged in an ancient pre-biotic world. Should this be the case, evolutionary signals retained by structurally conserved motifs, along with hierarchical features of ancient domains, could sew relationships among folds that diverged beyond the point where homology is discernable. In view of the aforementioned, this paper provides a rationale where a network with hierarchical and continuous levels of the protein space, together with sequence profiles that probe the extent of sequence similarity and contacting residues that capture the transition from pre-biotic to domain world, has been used to explore relationships between ancient folds. Statistics of detected signals have been reported. As a result, an example of an emergent sub-network that makes sense from an evolutionary perspective, where conserved signals retrieved from the assessed protein space have been co-opted, has been discussed.

对蛋白质宇宙中进化关系的精细探索。
在结构域分类制度中,蛋白质宇宙揭示了一组由层次关系连接的离散折叠。相反,在亚结构域大小的分辨率下,由于物理约束不一定需要进化来形成多肽链,蛋白质基序网络描绘了一个连续的视图,超出了等级分类方案的范围。然而,许多研究表明,普遍的亚序列可能是在一个古老的前生命世界中出现的肽的后代。如果是这样的话,那么由结构保守的基序所保留的进化信号,以及古代域的等级特征,可能会将褶皱之间的关系缝合起来,而这些褶皱之间的关系已经超出了同源性可识别的程度。鉴于上述情况,本文提供了一个理论基础,其中一个具有分层和连续水平的蛋白质空间网络,以及用于探测序列相似性程度的序列概况和捕获从生命前到域世界过渡的接触残基,已被用于探索古代褶皱之间的关系。已上报检测信号的统计信息。因此,本文讨论了一个从进化角度来看有意义的紧急子网络的例子,其中从评估的蛋白质空间检索到的保守信号已被增选。
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来源期刊
Statistical Applications in Genetics and Molecular Biology
Statistical Applications in Genetics and Molecular Biology BIOCHEMISTRY & MOLECULAR BIOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
自引率
11.10%
发文量
8
期刊介绍: Statistical Applications in Genetics and Molecular Biology seeks to publish significant research on the application of statistical ideas to problems arising from computational biology. The focus of the papers should be on the relevant statistical issues but should contain a succinct description of the relevant biological problem being considered. The range of topics is wide and will include topics such as linkage mapping, association studies, gene finding and sequence alignment, protein structure prediction, design and analysis of microarray data, molecular evolution and phylogenetic trees, DNA topology, and data base search strategies. Both original research and review articles will be warmly received.
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