Abstract
BackgroundProtein phosphorylation catalyzed by kinases plays crucial regulatory roles in cellular processes. Given the high-throughput mass spectrometry-based experiments, the desire to annotate the catalytic kinases for in vivo phosphorylation sites has motivated. Thus, a variety of computational methods have been developed for performing a large-scale prediction of kinase-specific phosphorylation sites. However, most of the proposed methods solely rely on the local amino acid sequences surrounding the phosphorylation sites. An increasing number of three-dimensional structures make it possible to physically investigate the structural environment of phosphorylation sites.ResultsIn this work, all of the experimental phosphorylation sites are mapped to the protein entries of Protein Data Bank by sequence identity. It resulted in a total of 4508 phosphorylation sites containing the protein three-dimensional (3D) structures. To identify phosphorylation sites on protein 3D structures, this work incorporates support vector machines (SVMs) with the information of linear motifs and spatial amino acid composition, which is determined for each kinase group by calculating the relative frequencies of 20 amino acid types within a specific radial distance from central phosphorylated amino acid residue. After the cross-validation evaluation, most of the kinase-specific models trained with the consideration of structural information outperform the models considering only the sequence information. Furthermore, the independent testing set which is not included in training set has demonstrated that the proposed method could provide a comparable performance to other popular tools.ConclusionThe proposed method is shown to be capable of predicting kinase-specific phosphorylation sites on 3D structures and has been implemented as a web server which is freely accessible at http://csb.cse.yzu.edu.tw/PhosK3D/. Due to the difficulty of identifying the kinase-specific phosphorylation sites with similar sequenced motifs, this work also integrates the 3D structural information to improve the cross classifying specificity.
Highlights
Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in many essential cellular processes including cellular regulation, cellular signal pathways, metabolism, growth, differentiation, and membrane effort to experimentally verify the catalytic kinases remains time-consuming, labor-intensive, and expensive
Many researches are undertaken to develop a computational method for the identification of kinase-specific phosphorylation sites, including NetPhosK [5], Scansite 2.0 [6], PredPhospho [7], GPS [8], PlantPhos [9], PPSP [4], MetaPredPS [10], NetPhorest [11] and KinasePhos [12,13,14]
Sequential and structural characteristics of kinase-specific phosphorylation sites As the sequence logos given in Table S2 (Additional File 1), most of the kinase groups have conserved amino acids surrounding the phosphorylation sites
Summary
Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in many essential cellular processes including cellular regulation, cellular signal pathways, metabolism, growth, differentiation, and membrane effort to experimentally verify the catalytic kinases remains time-consuming, labor-intensive, and expensive. With most of the existing phosphorylation site prediction tools requiring prior knowledge of experimentally verified substrates and its kinase, a method is developed to be able to predict kinase-specific phosphorylation sites based solely on protein sequence [16]. Over 20 methods have been developed for the accurate prediction of kinase-specific phosphorylation sites, most of them rely solely on the local amino acid sequence surrounding the phosphorylated sites. A variety of computational methods have been developed for performing a large-scale prediction of kinase-specific phosphorylation sites. Most of the proposed methods solely rely on the local amino acid sequences surrounding the phosphorylation sites. An increasing number of three-dimensional structures make it possible to physically investigate the structural environment of phosphorylation sites
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