Cheng Han, Wang Yongbo, Liu Zexian, Xue Yu
Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Methods Mol Biol. 2015;1306:195-205. doi: 10.1007/978-1-4939-2648-0_15.
The protein phosphorylation catalyzed by protein kinases (PKs) plays an essential role in almost all biological progresses in plants. Thus, the identification of PKs and kinase-specific substrates is fundamental for understanding the regulatory mechanisms of protein phosphorylation especially in controlling plant growth and development. In this chapter, we describe the computational methods and protocols for the identification of PKs and kinase-specific substrates in plants, by using Vitis vinifera as an example. First, the proteome sequences and experimentally identified phosphorylation sites (p-sites) in Vitis vinifera were downloaded. The potential PKs were computationally identified based on preconstructed Hidden Markov Model (HMM) profiles and ortholog searches, whereas the kinase-specific p-sites, or site-specific kinase-substrate relations (ssKSRs) were initially predicted by the software package of Group-based Prediction System (GPS) and further processed by the iGPS algorithm (in vivo GPS) to filter potentially false positive hits. All primary data sets and prediction results of Vitis vinifera are available at: http://ekpd.biocuckoo.org/protocol.php.
蛋白激酶（PKs）催化的蛋白质磷酸化在植物几乎所有的生物学进程中都起着至关重要的作用。因此，鉴定蛋白激酶和激酶特异性底物是理解蛋白质磷酸化调控机制的基础，尤其是在控制植物生长发育方面。在本章中，我们以葡萄为例，描述了鉴定植物中蛋白激酶和激酶特异性底物的计算方法和流程。首先，下载了葡萄的蛋白质组序列和通过实验鉴定的磷酸化位点（p位点）。基于预先构建的隐马尔可夫模型（HMM）图谱和直系同源物搜索，通过计算鉴定潜在的蛋白激酶，而激酶特异性p位点或位点特异性激酶-底物关系（ssKSRs）最初由基于组的预测系统（GPS）软件包进行预测，并通过iGPS算法（体内GPS）进一步处理，以过滤潜在的假阳性结果。葡萄的所有原始数据集和预测结果可在以下网址获取：http://ekpd.biocuckoo.org/protocol.php。
