Xue Yu, Li Ao, Wang Lirong, Feng Huanqing, Yao Xuebiao
School of Life Science, University of Science and Technology of China, Hefei, Anhui, 230027, China.
BMC Bioinformatics. 2006 Mar 20;7:163. doi: 10.1186/1471-2105-7-163.
As a reversible and dynamic post-translational modification (PTM) of proteins, phosphorylation plays essential regulatory roles in a broad spectrum of the biological processes. Although many studies have been contributed on the molecular mechanism of phosphorylation dynamics, the intrinsic feature of substrates specificity is still elusive and remains to be delineated.
In this work, we present a novel, versatile and comprehensive program, PPSP (Prediction of PK-specific Phosphorylation site), deployed with approach of Bayesian decision theory (BDT). PPSP could predict the potential phosphorylation sites accurately for approximately 70 PK (Protein Kinase) groups. Compared with four existing tools Scansite, NetPhosK, KinasePhos and GPS, PPSP is more accurate and powerful than these tools. Moreover, PPSP also provides the prediction for many novel PKs, say, TRK, mTOR, SyK and MET/RON, etc. The accuracy of these novel PKs are also satisfying.
Taken together, we propose that PPSP could be a potentially powerful tool for the experimentalists who are focusing on phosphorylation substrates with their PK-specific sites identification. Moreover, the BDT strategy could also be a ubiquitous approach for PTMs, such as sumoylation and ubiquitination, etc.
作为一种可逆的、动态的蛋白质翻译后修饰（PTM），磷酸化在广泛的生物过程中发挥着重要的调节作用。尽管已经有许多关于磷酸化动力学分子机制的研究，但底物特异性的内在特征仍然难以捉摸，有待进一步阐明。
在这项工作中，我们提出了一个新颖、通用且全面的程序PPSP（蛋白激酶特异性磷酸化位点预测），采用贝叶斯决策理论（BDT）方法。PPSP可以为大约70个蛋白激酶（PK）组准确预测潜在的磷酸化位点。与现有的四个工具Scansite、NetPhosK、KinasePhos和GPS相比，PPSP比这些工具更准确、更强大。此外，PPSP还为许多新型蛋白激酶提供预测，例如TRK、mTOR、SyK和MET/RON等。这些新型蛋白激酶的预测准确性也令人满意。
综上所述，我们认为PPSP对于专注于通过蛋白激酶特异性位点鉴定磷酸化底物的实验人员来说可能是一个潜在的强大工具。此外，BDT策略也可能是一种普遍适用于翻译后修饰的方法，如SUMO化和泛素化等。
