Brinkworth Ross I, Munn Alan L, Kobe Bostjan
School of Molecular and Microbial Sciences, University of Queensland, Brisbane 4072, Australia.
BMC Bioinformatics. 2006 Jan 31;7:47. doi: 10.1186/1471-2105-7-47.
Protein phosphorylation is an extremely important mechanism of cellular regulation. A large-scale study of phosphoproteins in a whole-cell lysate of Saccharomyces cerevisiae has previously identified 383 phosphorylation sites in 216 peptide sequences. However, the protein kinases responsible for the phosphorylation of the identified proteins have not previously been assigned.
We used Predikin in combination with other bioinformatic tools, to predict which of 116 unique protein kinases in yeast phosphorylates each experimentally determined site in the phosphoproteome. The prediction was based on the match between the phosphorylated 7-residue sequence and the predicted substrate specificity of each kinase, with the highest weight applied to the residues or positions that contribute most to the substrate specificity. We estimated the reliability of the predictions by performing a parallel prediction on phosphopeptides for which the kinase has been experimentally determined.
The results reveal that the functions of the protein kinases and their predicted phosphoprotein substrates are often correlated, for example in endocytosis, cytokinesis, transcription, replication, carbohydrate metabolism and stress response. The predictions link phosphoproteins of unknown function with protein kinases with known functions and vice versa, suggesting functions for the uncharacterized proteins. The study indicates that the phosphoproteins and the associated protein kinases represented in our dataset have housekeeping cellular roles; certain kinases are not represented because they may only be activated during specific cellular responses. Our results demonstrate the utility of our previously reported protein kinase substrate prediction approach (Predikin) as a tool for establishing links between kinases and phosphoproteins that can subsequently be tested experimentally.
蛋白质磷酸化是细胞调控的一种极其重要的机制。此前，一项对酿酒酵母全细胞裂解液中磷酸化蛋白质的大规模研究已在216个肽序列中鉴定出383个磷酸化位点。然而，此前尚未确定负责这些已鉴定蛋白质磷酸化的蛋白激酶。
我们使用Predikin并结合其他生物信息学工具，来预测酵母中116种独特的蛋白激酶中哪些会使磷酸化蛋白质组中每个实验确定的位点发生磷酸化。该预测基于磷酸化的7个残基序列与每种激酶预测的底物特异性之间的匹配，对底物特异性贡献最大的残基或位置赋予最高权重。我们通过对已通过实验确定激酶的磷酸肽进行平行预测，来估计预测的可靠性。
结果表明，蛋白激酶及其预测的磷酸化蛋白质底物的功能通常是相关的，例如在内吞作用、胞质分裂、转录、复制、碳水化合物代谢和应激反应中。这些预测将功能未知的磷酸化蛋白质与功能已知的蛋白激酶联系起来，反之亦然，从而为未表征的蛋白质提示了功能。该研究表明，我们数据集中的磷酸化蛋白质和相关蛋白激酶具有细胞管家功能；某些激酶未被体现，可能是因为它们仅在特定细胞反应中被激活。我们的结果证明了我们之前报道的蛋白激酶底物预测方法（Predikin）作为一种工具的实用性，该工具可用于建立激酶与磷酸化蛋白质之间的联系，随后可通过实验进行验证。
