SLiM on Diet: finding short linear motifs on domain interaction interfaces in Protein Data Bank
SLiM on Diet: finding short linear motifs on domain interaction interfaces in Protein Data Bank
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DOI：
10.1093/bioinformatics/btq065
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发表时间：
2010-04-15
期刊：
影响因子：
5.8
通讯作者：
Sung, Wing-Kin
中科院分区：
文献类型：
--
作者：
Hugo, Willy;Song, Fushan;Sung, Wing-Kin
动机：一类重要的蛋白质相互作用涉及蛋白质结构域与其相互作用伙伴上的短线性基序（SLiM）的结合。提取这样的基序，无论是实验还是计算，都是具有挑战性的，因为它们的弱结合和高度简并。最近可用的蛋白质结构的快速增加为直接从其3D结构研究slim提供了极好的机会。结果：利用结构域界面提取（Diet），我们从蛋白质数据库（PDB）中鉴定了452个不同的slim，其中155个在不同程度上得到了验证- 40个有文献验证，54个至少有一个结构域-肽结构实例支持，另外61个在高通量PPI数据中具有代表性。我们进一步观察到，现有计算微小粒子检测方法的覆盖范围不佳可能是由于大多数微小粒子发生在球状域区域之外的共同假设。我们报告的452个SLiM中有198个实际上是在domain domain interface上找到的；其中一些与自身免疫和神经退行性疾病有关。我们认为这些slms将有助于设计针对这些疾病的致病蛋白复合物的抑制剂。我们的。研究结果表明，基于三维结构的SLiM检测算法可以比当前基于序列的方法更全面地覆盖SLiM介导的蛋白质相互作用。
Motivation: An important class of protein interactions involves the binding of a protein's domain to a short linear motif (SLiM) on its interacting partner. Extracting such motifs, either experimentally or computationally, is challenging because of their weak binding and high degree of degeneracy. Recent rapid increase of available protein structures provides an excellent opportunity to study SLiMs directly from their 3D structures.Results: Using domain interface extraction (Diet), we characterized 452 distinct SLiMs from the Protein Data Bank (PDB), of which 155 are validated in varying degrees - 40 have literature validation, 54 are supported by at least one domain - peptide structural instance, and another 61 have overrepresentation in high- throughput PPI data. We further observed that the lacklustre coverage of existing computational SLiM detection methods could be due to the common assumption that most SLiMs occur outside globular domain regions. 198 of 452 SLiM that we reported are actually found on domain domain interface; some of them are implicated in autoimmune and neurodegenerative diseases. We suggest that these SLiMs would be useful for designing inhibitors against the pathogenic protein complexes underlying these diseases. Our. ndings show that 3D structure- based SLiM detection algorithms can provide a more complete coverage of SLiM- mediated protein interactions than current sequence- based approaches.