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蛋白质数据库中聚集的蛋白质和真核生物及细菌蛋白质组中的紊乱模式。

Disordered patterns in clustered Protein Data Bank and in eukaryotic and bacterial proteomes.

机构信息

Group of Bioinformatics, Institute of Protein Research Russian Academy of Sciences, Pushchino, Moscow Region, Russia.

出版信息

PLoS One. 2011;6(11):e27142. doi: 10.1371/journal.pone.0027142. Epub 2011 Nov 4.

Abstract

We have constructed the clustered Protein Data Bank and obtained clusters of chains of different identity inside each cluster, http://bioinfo.protres.ru/st_pdb/. We have compiled the largest database of disordered patterns (141) from the clustered PDB where identity between chains inside of a cluster is larger or equal to 75% (version of 28 June 2010) by using simple rules of selection. The results of these analyses would help to further our understanding of the physicochemical and structural determinants of intrinsically disordered regions that serve as molecular recognition elements. We have analyzed the occurrence of the selected patterns in 97 eukaryotic and in 26 bacterial proteomes. The disordered patterns appear more often in eukaryotic than in bacterial proteomes. The matrix of correlation coefficients between numbers of proteins where a disordered pattern from the library of 141 disordered patterns appears at least once in 9 kingdoms of eukaryota and 5 phyla of bacteria have been calculated. As a rule, the correlation coefficients are higher inside of the considered kingdom than between them. The patterns with the frequent occurrence in proteomes have low complexity (PPPPP, GGGGG, EEEED, HHHH, KKKKK, SSTSS, QQQQQP), and the type of patterns vary across different proteomes, http://bioinfo.protres.ru/fp/search_new_pattern.html.

摘要

我们构建了聚类蛋白数据库,并在每个聚类中获得了不同身份的链聚类,http://bioinfo.protres.ru/st_pdb/。我们使用简单的选择规则,从聚类 PDB 中编译了最大的无序模式数据库(141 个),其中聚类中链之间的身份大于或等于 75%(2010 年 6 月 28 日版本)。这些分析的结果将有助于我们进一步了解作为分子识别元件的固有无序区域的物理化学和结构决定因素。我们分析了 97 种真核生物和 26 种细菌蛋白质组中的这些模式的出现。无序模式在真核生物蛋白质组中比在细菌蛋白质组中更为常见。我们计算了 9 个真核生物王国和 5 个细菌门的蛋白质组中至少出现一次文库中 141 个无序模式之一的无序模式的数量之间的相关系数矩阵。通常,相关系数在考虑的王国内部比它们之间更高。在蛋白质组中频繁出现的模式具有低复杂度(PPPPP、GGG、EEEED、HHHH、KKKKK、SSTSS、QQQQQP),并且模式类型在不同的蛋白质组中有所不同,http://bioinfo.protres.ru/fp/search_new_pattern.html。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/045f/3208572/8ac3db83f692/pone.0027142.g001.jpg

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