Iakoucheva Lilia M, Radivojac Predrag, Brown Celeste J, O'Connor Timothy R, Sikes Jason G, Obradovic Zoran, Dunker A Keith
School of Molecular Biosciences, Washington State University, Pullman, WA 99164, USA.
Nucleic Acids Res. 2004 Feb 11;32(3):1037-49. doi: 10.1093/nar/gkh253. Print 2004.
Reversible protein phosphorylation provides a major regulatory mechanism in eukaryotic cells. Due to the high variability of amino acid residues flanking a relatively limited number of experimentally identified phosphorylation sites, reliable prediction of such sites still remains an important issue. Here we report the development of a new web-based tool for the prediction of protein phosphorylation sites, DISPHOS (DISorder-enhanced PHOSphorylation predictor, http://www.ist.temple. edu/DISPHOS). We observed that amino acid compositions, sequence complexity, hydrophobicity, charge and other sequence attributes of regions adjacent to phosphorylation sites are very similar to those of intrinsically disordered protein regions. Thus, DISPHOS uses position-specific amino acid frequencies and disorder information to improve the discrimination between phosphorylation and non-phosphorylation sites. Based on the estimates of phosphorylation rates in various protein categories, the outputs of DISPHOS are adjusted in order to reduce the total number of misclassified residues. When tested on an equal number of phosphorylated and non-phosphorylated residues, the accuracy of DISPHOS reaches 76% for serine, 81% for threonine and 83% for tyrosine. The significant enrichment in disorder-promoting residues surrounding phosphorylation sites together with the results obtained by applying DISPHOS to various protein functional classes and proteomes, provide strong support for the hypothesis that protein phosphorylation predominantly occurs within intrinsically disordered protein regions.
可逆蛋白磷酸化是真核细胞中的一种主要调节机制。由于相对有限数量的经实验鉴定的磷酸化位点侧翼氨基酸残基的高度变异性,可靠预测这些位点仍然是一个重要问题。在此,我们报告了一种用于预测蛋白磷酸化位点的新型基于网络的工具——DISPHOS(无序增强型磷酸化预测器,http://www.ist.temple.edu/DISPHOS)。我们观察到,磷酸化位点附近区域的氨基酸组成、序列复杂性、疏水性、电荷及其他序列属性与内在无序蛋白区域的非常相似。因此,DISPHOS利用位置特异性氨基酸频率和无序信息来提高磷酸化位点与非磷酸化位点之间的区分度。基于各类蛋白中磷酸化率的估计,对DISPHOS的输出结果进行调整,以减少误分类残基的总数。当对数量相等的磷酸化和非磷酸化残基进行测试时,DISPHOS对丝氨酸的预测准确率达到76%,对苏氨酸为81%,对酪氨酸为83%。磷酸化位点周围促进无序的残基显著富集,以及将DISPHOS应用于各种蛋白功能类别和蛋白质组所获得的结果,为蛋白磷酸化主要发生在内在无序蛋白区域这一假说提供了有力支持。