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Where differences resemble: sequence-feature analysis in curated databases of intrinsically disordered proteins

机译:差异相似之处:精选的内在无序蛋白数据库中的序列特征分析

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摘要

Intrinsic disorder (ID) in proteins is involved in crucial interactions in the living cell. As the importance of ID is increasingly recognized, so are detailed analyses aimed at its identification and characterization. An open question remains the existence of ID `flavors’ representing different sub-phenomena. Several databases collect manually curated examples of experimentally validated ID, focusing on apparently different aspects of this phenomenon. The recent update of MobiDB presented the opportunity to carry out an in-depth comparison of the content of these validated ID collections, namely DIBS, DisProt, IDEAL, MFIB, FuzDB, ELM and UniProt. In order to assess what is specific to different ID flavors, we analyzed relevant sequence-based features, such as amino acid composition, length, taxa and gene ontology terms, highlighting differences and similarities among datasets. Despite that, the majority of the considered features are not statistically different across databases, with the exception of ELM. FuzDB also shares half of its entries with DisProt. In general, different ID databases describe similar phenomena. DisProt, which is the largest database, better represents the entire spectrum of different disorder flavors and the corresponding sequence diversity.
机译:蛋白质中的内源性疾病(ID)参与活细胞中的关键相互作用。随着人们越来越认识到ID的重要性,针对ID的识别和表征进行的详细分析也越来越多。一个悬而未决的问题仍然是代表不同子现象的ID风味的存在。几个数据库收集了经过人工整理的经过实验验证的ID的示例,重点是该现象的明显不同方面。 MobiDB的最新更新提供了机会,可以对这些经过验证的ID集合(即DIBS,DisProt,IDEAL,MFIB,FuzDB,ELM和UniProt)的内容进行深入比较。为了评估什么是针对不同ID风味的特异,我们分析了基于序列的相关特征,例如氨基酸组成,长度,分类和基因本体术语,突出了数据集之间的差异和相似性。尽管如此,除ELM之外,大多数数据库中考虑的大多数功能在统计上都没有差异。 FuzDB还与DisProt共享一半的条目。通常,不同的ID数据库描述相似的现象。 DisProt是最大的数据库,可以更好地表示不同疾病风味的整个光谱以及相应的序列多样性。

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