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ECL: an exhaustive search tool for the identification of cross-linked peptides using whole database

机译:ECL:使用整个数据库来识别交联肽的详尽搜索工具

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Background Chemical cross-linking combined with mass spectrometry (CX-MS) is a high-throughput approach to studying protein-protein interactions. The number of peptide-peptide combinations grows quadratically with respect to the number of proteins, resulting in a high computational complexity. Widely used methods including xQuest (Rinner et al., Nat Methods 5(4):315–8, 2008; Walzthoeni et al., Nat Methods 9(9):901–3, 2012), pLink (Yang et al., Nat Methods 9(9):904–6, 2012), ProteinProspector (Chu et al., Mol Cell Proteomics 9:25–31, 2010; Trnka et al., 13(2):420–34, 2014) and Kojak (Hoopmann et al., J Proteome Res 14(5):2190–198, 2015) avoid searching all peptide-peptide combinations by pre-selecting peptides with heuristic approaches. However, pre-selection procedures may cause missing findings. The most intuitive approach is searching all possible candidates. A tool that can exhaustively search a whole database without any heuristic pre-selection procedure is therefore desirable. Results We have developed a cross-linked peptides identification tool named ECL. It can exhaustively search a whole database in a reasonable period of time without any heuristic pre-selection procedure. Tests showed that searching a database containing 5200 proteins took 7 h. ECL identified more non-redundant cross-linked peptides than xQuest, pLink, and ProteinProspector. Experiments showed that about 30 % of these additional identified peptides were not pre-selected by Kojak. We used protein crystal structures from the protein data bank to check the intra-protein cross-linked peptides. Most of the distances between cross-linking sites were smaller than 30 ?. Conclusions To the best of our knowledge, ECL is the first tool that can exhaustively search all candidates in cross-linked peptides identification. The experiments showed that ECL could identify more peptides than xQuest, pLink, and ProteinProspector. A further analysis indicated that some of the additional identified results were thanks to the exhaustive search.
机译:背景技术化学交联与质谱(CX-MS)结合是研究蛋白质-蛋白质相互作用的高通量方法。肽-肽组合的数量相对于蛋白质的数量呈二次方增长,导致计算复杂性高。广泛使用的方法包括xQuest(Rinner等人,Nat Methods 5(4):315-8,2008; Walzthoeni等人,Nat Methods 9(9):901-3,2012),pLink(Yang等人, Nat Methods 9(9):904–6,2012),ProteinProspector(Chu等人,Mol Cell Proteomics 9:25–31,2010; Trnka等人,13(2):420–34,2014)和Kojak (Hoopmann等人,J Proteome Res 14(5):2190-198,2015)通过使用启发式方法预先选择肽段来避免搜索所有肽段-肽段组合。但是,预选程序可能会导致缺少发现。最直观的方法是搜索所有可能的候选人。因此,需要一种能够在没有任何启发式预选择过程的情况下彻底搜索整个数据库的工具。结果我们开发了一种名为ECL的交联肽段鉴定工具。它可以在合理的时间内详尽搜索整个数据库,而无需任何启发式的预选过程。测试表明,搜索包含5200种蛋白质的数据库需要7个小时。与xQuest,pLink和ProteinProspector相比,ECL鉴定出更多的非冗余交联肽。实验表明,这些额外鉴定的肽中约有30%没有被Kojak预选。我们使用了来自蛋白质数据库的蛋白质晶体结构来检查蛋白质内交联肽。交联部位之间的大多数距离小于30?。结论据我们所知,ECL是第一个可以详尽搜索交联肽鉴定中所有候选物的工具。实验表明,ECL可以比xQuest,pLink和ProteinProspector识别更多的肽。进一步的分析表明,某些其他确定的结果要归功于详尽的搜索。

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