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SLiMPrints:基于保守性的功能基序指纹在无规卷曲蛋白质区域中的发现。

SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions.

机构信息

Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Baden-Württemberg 69117, Germany.

出版信息

Nucleic Acids Res. 2012 Nov;40(21):10628-41. doi: 10.1093/nar/gks854. Epub 2012 Sep 12.

Abstract

Large portions of higher eukaryotic proteomes are intrinsically disordered, and abundant evidence suggests that these unstructured regions of proteins are rich in regulatory interaction interfaces. A major class of disordered interaction interfaces are the compact and degenerate modules known as short linear motifs (SLiMs). As a result of the difficulties associated with the experimental identification and validation of SLiMs, our understanding of these modules is limited, advocating the use of computational methods to focus experimental discovery. This article evaluates the use of evolutionary conservation as a discriminatory technique for motif discovery. A statistical framework is introduced to assess the significance of relatively conserved residues, quantifying the likelihood a residue will have a particular level of conservation given the conservation of the surrounding residues. The framework is expanded to assess the significance of groupings of conserved residues, a metric that forms the basis of SLiMPrints (short linear motif fingerprints), a de novo motif discovery tool. SLiMPrints identifies relatively overconstrained proximal groupings of residues within intrinsically disordered regions, indicative of putatively functional motifs. Finally, the human proteome is analysed to create a set of highly conserved putative motif instances, including a novel site on translation initiation factor eIF2A that may regulate translation through binding of eIF4E.

摘要

真核生物蛋白质组的大部分区域都是固有无序的,大量证据表明,这些蛋白质的无规则区域富含丰富的调控相互作用界面。无序相互作用界面的一个主要类别是称为短线性基序 (SLiM) 的紧凑和退化模块。由于实验鉴定和验证 SLiMs 存在困难,我们对这些模块的理解是有限的,因此提倡使用计算方法来集中进行实验发现。本文评估了进化保守性作为基序发现的判别技术。引入了一个统计框架来评估相对保守残基的显著性,量化给定周围残基的保守性,一个残基具有特定保守水平的可能性。该框架扩展到评估保守残基分组的显著性,这是 SLiMPrints(短线性基序指纹)的基础,这是一种从头开始的基序发现工具。SLiMPrints 确定了内在无序区域中相对过度约束的近端残基分组,表明可能具有功能的基序。最后,分析人类蛋白质组以创建一组高度保守的假定基序实例,包括翻译起始因子 eIF2A 上的一个新位点,该位点可能通过与 eIF4E 结合来调节翻译。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f57e/3510515/b76f8d1e15df/gks854f1p.jpg

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