Prediction of Protein Complexes in Trypanosoma brucei by Protein Correlation Profiling Mass Spectrometry and Machine Learning
Prediction of Protein Complexes in Trypanosoma brucei by Protein Correlation Profiling Mass Spectrometry and Machine Learning
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DOI：
10.1074/mcp.o117.068122
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发表时间：
2017-12-01
影响因子：
7
通讯作者：
Ferguson, Michael A. J.
中科院分区：
文献类型：
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作者：
Crozier, Thomas W. M.;Tinti, Michele;Ferguson, Michael A. J.
从原生动物寄生虫布氏锥虫（Trypanosoma brucei）（一种重要的人类和动物病原体）的基因组序列中，不成比例的预测蛋白质数量是功能未知的假设蛋白质。本文介绍了一种蛋白质相关性分析质谱方法，使用两个尺寸排阻和一个离子交换色谱系统，通过层次聚类和机器学习方法来获得预测的蛋白质复合物。这些产生假设的蛋白质组学数据在开放获取的在线数据可视化环境（http：//www.example.com：8083/complex_explorer）中提供。134.36.66.166通过用户友好的自定义图形界面可以方便地搜索数据。我们提供了潜在的新亚基的已知蛋白质复合物和新的锥虫复合物的建议功能的例子，有助于提高锥虫蛋白质组的功能注释。数据可通过ProteomeXchange获得，标识符为PXD 005968。
A disproportionate number of predicted proteins from the genome sequence of the protozoan parasite Trypanosoma brucei, an important human and animal pathogen, are hypothetical proteins of unknown function. This paper describes a protein correlation profiling mass spectrometry approach, using two size exclusion and one ion exchange chromatography systems, to derive sets of predicted protein complexes in this organism by hierarchical clustering and machine learning methods. These hypothesis- generating proteomic data are provided in an open access online data visualization environment (http:// 134.36.66.166: 8083/complex_explorer). The data can be searched conveniently via a user friendly, custom graphical interface. We provide examples of both potential new subunits of known protein complexes and of novel trypanosome complexes of suggested function, contributing to improving the functional annotation of the trypanosome proteome. Data are available via ProteomeXchange with identifier PXD005968.