Prediction of functional phosphorylation sites by incorporating evolutionary information

Protein phosphorylation is a ubiquitous protein post-translational modification, which plays an important role in cellular signaling systems underlying various physiological and pathological processes. Current in silico methods mainly focused on the prediction of phosphorylation sites, but rare methods considered whether a phosphorylation site is functional or not. Since functional phosphorylation sites are more valuable for further experimental research and a proportion of phosphorylation sites have no direct functional effects, the prediction of functional phosphorylation sites is quite necessary for this research area. Previous studies have shown that functional phosphorylation sites are more conserved than non-functional phosphorylation sites in evolution. Thus, in our method, we developed a web server by integrating existing phosphorylation site prediction methods, as well as both absolute and relative evolutionary conservation scores to predict the most likely functional phosphorylation sites. Using our method, we predicted the most likely functional sites of the human, rat and mouse proteomes and built a database for the predicted sites. By the analysis of overall prediction results, we demonstrated that protein phosphorylation plays an important role in all the enriched KEGG pathways. By the analysis of protein-specific prediction results, we demonstrated the usefulness of our method for individual protein studies. Our method would help to characterize the most likely functional phosphorylation sites for further studies in this research area.     

Phosphorylation of rap1GAP in vivo and by cAMP-dependent kinase and the cell cycle p34cdc2 kinase in vitro.

rap1GAP is a GTPase activating protein that specifically stimulates the GTP hydrolytic rate of the ras-related protein p21rap1.rap1GAP undergoes post-translational modification that causes a substantial change in its mobility on sodium dodecyl sulfate-polyacrylamide gels. At least part of this modification is due to the phosphorylation. Expression of a rap1GAP cDNA in insect cells labeled with 32Pi resulted in high level incorporation of radioactivity into serine residues of the expressed protein. Purified rap1GAP was phosphorylated in vitro by cAMP-dependent kinase and the cell cycle p34cdc2 kinase. The molar ratio of incorporated phosphate/rap1GAP was approximately 3 by cAMP-dependent kinase and 2 by p34cdc2. The sites of phosphorylation by both kinases were localized to a 100-residue segment contained in the carboxyl-terminal region of the predicted primary structure of rap1GAP. Highly favorable recognition sequences for the two kinases are contained within this fragment and are proposed as the sites of phosphorylation. Treatment of SK-MEL-3 cells with dibutyryl cAMP promoted phosphorylation of rap1GAP in vivo. Based on the results of comparative phosphopeptide mapping the sites of phosphorylation in vivo and in vitro are identical.     

Prediction of phosphorylation sites using SVMs

MOTIVATION: Phosphorylation is involved in diverse signal transduction pathways. By predicting phosphorylation sites and their kinases from primary protein sequences, we can obtain much valuable information that can form the basis for further research. Using support vector machines, we attempted to predict phosphorylation sites and the type of kinase that acts at each site. RESULTS: Our prediction system was limited to phosphorylation sites catalyzed by four protein kinase families and four protein kinase groups. The accuracy of the predictions ranged from 83 to 95% at the kinase family level, and 76-91% at the kinase group level. The prediction system used-PredPhospho-can be applied to the functional study of proteins, and can help predict the changes in phosphorylation sites caused by amino acid variations at intra- and interspecies levels.     

GPS: a novel group-based phosphorylation predicting and scoring method

Protein phosphorylation is an important reversible post-translational modification of proteins, and it orchestrates a variety of cellular processes. Experimental identification of phosphorylation site is labor-intensive and often limited by the availability and optimization of enzymatic reaction. In silico prediction may facilitate the identification of potential phosphorylation sites with ease. Here we present a novel computational method named GPS: group-based phosphorylation site predicting and scoring platform. If two polypeptides differ by only two consecutive amino acids, in particular when the two different amino acids are a conserved pair, e.g., isoleucine (I) and valine (V), or serine (S) and threonine (T), we view these two polypeptides bearing similar 3D structures and biochemical properties. Based on this rationale, we formulated GPS that carries greater computational power with superior performance compared to two existing phosphorylation sites prediction systems, ScanSite 2.0 and PredPhospho. With database in public domain, GPS can predict substrate phosphorylation sites from 52 different protein kinase (PK) families while ScanSite 2.0 and PredPhospho offer at most 30 PK families. Using PKA as a model enzyme, we first compared prediction profiles from the GPS method with those from ScanSite 2.0 and PredPhospho. In addition, we chose an essential mitotic kinase Aurora-B as a model enzyme since ScanSite 2.0 and PredPhospho offer no prediction. However, GPS offers satisfactory sensitivity (94.44%) and specificity (97.14%). Finally, the accuracy of phosphorylation on MCAK predicted by GPS was validated by experimentation, in which six out of seven predicted potential phosphorylation sites on MCAK (Q91636) were experimentally verified. Taken together, we have generated a novel method to predict phosphorylation sites, which offers greater precision and computing power over ScanSite 2.0 and PredPhospho.     

Prediction of kinase-specific phosphorylation sites with sequence features by a log-odds ratio approach

Protein phosphorylation plays important roles in a variety of cellular processes. Detecting possible phosphorylation sites and their corresponding protein kinases is crucial for studying the function of many proteins. This article presents a new prediction system, called PhoScan, to predict phosphorylation sites in a kinase-family-specific way. Common phosphorylation features and kinase-specific features are extracted from substrate sequences of different protein kinases based on the analysis of published experiments, and a scoring system is developed for evaluating the possibility that a peptide can be phosphorylated by the protein kinase at the specific site in its sequence context. PhoScan can achieve a specificity of above 90% with sensitivity around 90% at kinase-family level on the data experimented. The system is applied on a set of human proteins collected from Swiss-Prot and sets of putative phosphorylation sites are predicted for protein kinase A, cyclin-dependent kinase, and casein kinase 2 families. PhoScan is available at http://bioinfo.au.tsinghua.edu.cn/phoscan/.     

Analysis of the Arabidopsis cytosolic ribosome proteome provides detailed insights into its components and their post-translational modification

Finding gene-specific peptides by mass spectrometry analysis to pinpoint gene loci responsible for particular protein products is a major challenge in proteomics especially in highly conserved gene families in higher eukaryotes. We used a combination of in silico approaches coupled to mass spectrometry analysis to advance the proteomics insight into Arabidopsis cytosolic ribosomal composition and its post-translational modifications. In silico digestion of all 409 ribosomal protein sequences in Arabidopsis defined the proportion of theoretical gene-specific peptides for each gene family and highlighted the need for low m/z cutoffs of MS ion selection for MS/MS to characterize low molecular weight, highly basic ribosomal proteins. We undertook an extensive MS/MS survey of the cytosolic ribosome using trypsin and, when required, chymotrypsin and pepsin. We then used custom software to extract and filter peptide match information from Mascot result files and implement high confidence criteria for calling gene-specific identifications based on the highest quality unambiguous spectra matching exclusively to certain in silico predicted gene- or gene family-specific peptides. This provided an in-depth analysis of the protein composition based on 1446 high quality MS/MS spectra matching to 795 peptide sequences from ribosomal proteins. These identified peptides from five gene families of ribosomal proteins not identified previously, providing experimental data on 79 of the 80 different types of ribosomal subunits. We provide strong evidence for gene-specific identification of 87 different ribosomal proteins from these 79 families. We also provide new information on 30 specific sites of co- and post-translational modification of ribosomal proteins in Arabidopsis by initiator methionine removal, N-terminal acetylation, N-terminal methylation, lysine N-methylation, and phosphorylation. These site-specific modification data provide a wealth of resources for further assessment of the role of ribosome modification in influencing translation in Arabidopsis.     

Prediction of PK-specific phosphorylation site based on information entropy

Phosphorylation is a crucial way to control the activity of proteins in many eukaryotic organisms in vivo. Experimental methods to determine phosphorylation sites in substrates are usually restricted by the in vitro condition of enzymes and very intensive in time and labor. Although some in silico methods and web servers have been introduced for automatic detection of phosphorylation sites, sophisticated methods are still in urgent demand to further improve prediction performances. Protein primary sequences can help predict phosphorylation sites catalyzed by different protein kinase and most computational approaches use a short local peptide to make prediction. However, the useful information may be lost if only the conservative residues that are not close to the phosphorylation site are considered in prediction, which would hamper the prediction results. A novel prediction method named IEPP (Information-Entropy based Phosphorylation Prediction) is presented in this paper for automatic detection of potential phosphorylation sites. In prediction, the sites around the phosphorylation sites are selected or excluded by their entropy values. The algorithm was compared with other methods such as GSP and PPSP on the ABL, MAPK and PKA PK families. The superior prediction accuracies were obtained in various measurements such as sensitivity (Sn) and specificity (Sp). Furthermore, compared with some online prediction web servers on the new discovered phosphorylation sites, IEPP also yielded the best performance. IEPP is another useful computational resource for identification of PK-specific phosphorylation sites and it also has the advantages of simpleness, efficiency and convenience.     

AutoMotif Server for prediction of phosphorylation sites in proteins using support vector machine: 2007 update

We present here the recent update of AutoMotif Server (AMS 2.0) that predicts post-translational modification sites in protein sequences. The support vector machine (SVM) algorithm was trained on data gathered in 2007 from various sets of proteins containing experimentally verified chemical modifications of proteins. Short sequence segments around a modification site were dissected from a parent protein, and represented in the training set as binary or profile vectors. The updated efficiency of the SVM classification for each type of modification and the predictive power of both representations were estimated using leave-one-out tests for model of general phosphorylation and for modifications catalyzed by several specific protein kinases. The accuracy of the method was improved in comparison to the previous version of the service (Plewczynski et al., “AutoMotif server: prediction of single residue post-translational modifications in proteins”, Bioinformatics 21: 2525–7, 2005). The precision of the updated version reached over 90% for selected types of phosphorylation and was optimized in trade of lower recall value of the classification model. The AutoMotif Server version 2007 is freely available at . Additionally, the reference dataset for optimization of prediction of phosphorylation sites, collected from the UniProtKB was also provided and can be accessed at .     

Epidermal growth factor receptors: function modulation by phosphorylation and glycosylation interplay

Post-translational modifications (PTMs) of proteins induce structural and functional changes that are most often transitory and difficult to follow and investigate in vivo. In silico prediction procedures for PTMs are very valuable to foresee and define such transitory changes responsible for the multifunctionality of proteins. Epidermal growth factor receptor (EGFR) is such a multifunctional transmembrane protein with intrinsic tyrosine kinase activity that is regulated primarily by ligand-stimulated transphosphorylation of dimerized receptors. In human EGFR, potential phosphorylation sites on Ser, Thr and Tyr residues including five autophosphorylation sites on Tyr were investigated using in silico procedures. In addition to phosphorylation, O-GlcNAc modifications and interplay between these two modifications was also predicted. The interplay of phosphorylation and O-GlcNAc modification on same or neighboring Ser/Thr residues is termed as Yin Yang hypothesis and the interplay sites are named as Yin Yang sites. Amongst these modification sites, one residue is localized in the juxtamembrane (Thr 654) and two are found in the catalytic domain (Ser 1046/1047) of the EGFR. We propose that, when EGFR is O-GlcNAc modified on Thr 654, EGFR may be transferred from early to late endosomes, whereas when EGFR is O-GlcNAc modified on Ser 1046/1047 desensitization of the receptor may be prevented. These findings suggest a complex interplay between phosphorylation and O-GlcNAc modification resulting in modulation of EGFR's functionality.     

MAPRes: an efficient method to analyze protein sequence around post-translational modification sites

Functional switches are often regulated by dynamic protein modifications. Assessing protein functions, in vivo, and their functional switches remains still a great challenge in this age of development. An alternative methodology based on in silico procedures may facilitate assessing the multifunctionality of proteins and, in addition, allow predicting functions of those proteins that exhibit their functionality through transitory modifications. Extensive research is ongoing to predict the sequence of protein modification sites and analyze their dynamic nature. This study reports the analysis performed on phosphorylation, Phospho.ELM (version 3.0) and glycosylation, OGlycBase (version 6.0) data for mining association patterns utilizing a newly developed algorithm, MAPRes. This method, MAPRes (Mining Association Patterns among preferred amino acid residues in the vicinity of amino acids targeted for post-translational modifications), is based on mining association among significantly preferred amino acids of neighboring sequence environment and modification sites themselves. Association patterns arrived at by association pattern/rule mining were in significant conformity with the results of different approaches. However, attempts to analyze substrate sequence environment of phosphorylation sites catalyzed for Tyr kinases and the sequence data for O-GlcNAc modification were not successful, due to the limited data available. Using the MAPRes algorithm for developing an association among PTM site with its vicinal amino acids is a valid method with many potential uses: this is indeed the first method ever to apply the association pattern mining technique to protein post-translational modification data.     

Prediction of PK-specific phosphorylation site based on information entropy

Phosphorylation is a crucial way to control the activity of proteins in many eukaryotic organisms in vivo. Experimental methods to determine phosphorylation sites in substrates are usually restricted by the in vitro condition of enzymes and very intensive in time and labor. Although some in silico methods and web servers have been introduced for automatic detection of phosphorylation sites, sophisticated methods are still in urgent demand to further improve prediction performances. Protein primary se-quences can help predict phosphorylation sites catalyzed by different protein kinase and most com-putational approaches use a short local peptide to make prediction. However, the useful information may be lost if only the conservative residues that are not close to the phosphorylation site are consid-ered in prediction, which would hamper the prediction results. A novel prediction method named IEPP (Information-Entropy based Phosphorylation Prediction) is presented in this paper for automatic de-tection of potential phosphorylation sites. In prediction, the sites around the phosphorylation sites are selected or excluded by their entropy values. The algorithm was compared with other methods such as GSP and PPSP on the ABL, MAPK and PKA PK families. The superior prediction accuracies were ob-tained in various measurements such as sensitivity (Sn) and specificity (Sp). Furthermore, compared with some online prediction web servers on the new discovered phosphorylation sites, IEPP also yielded the best performance. IEPP is another useful computational resource for identification of PK-specific phosphorylation sites and it also has the advantages of simpleness, efficiency and con-venience.     

Phosphorylation of varicella-zoster virus glycoprotein gpI by mammalian casein kinase II and casein kinase I.

Varicella-zoster virus (VZV) glycoprotein gpI is the predominant viral glycoprotein within the plasma membranes of infected cells. This viral glycoprotein is phosphorylated on its polypeptide backbone during biosynthesis. In this report, we investigated the protein kinases which participate in the phosphorylation events. Under in vivo conditions, VZV gpI was phosphorylated on its serine and threonine residues by protein kinases present within lysates of either VZV-infected or uninfected cells. Because this activity was diminished by heparin, a known inhibitor of casein kinase II, isolated gpI was incubated with purified casein kinase II and shown to be phosphorylated in an in vitro assay containing [gamma-32P]ATP. The same glycoprotein was phosphorylated when [32P]GTP was substituted for [32P]ATP in the protein kinase assay. We also tested whether VZV gpI was phosphorylated by two other ubiquitous mammalian protein kinases--casein kinase I and cyclic AMP-dependent kinase--and found that only casein kinase I modified gpI. When the predicted 623-amino-acid sequence of gpI was examined, two phosphorylation sites known to be optimal for casein kinase II were observed. Immediately upstream from each of the casein kinase II sites was a potential casein kinase I phosphorylation site. In summary, this study showed that VZV gpI was phosphorylated by each of two mammalian protein kinases (casein kinase I and casein kinase II) and that potential serine-threonine phosphorylation sites for each of these two kinases were present in the viral glycoprotein.     

Prediction of protein kinase-specific phosphorylation sites in hierarchical structure using functional information and random forest

Reversible protein phosphorylation is one of the most important post-translational modifications, which regulates various biological cellular processes. Identification of the kinase-specific phosphorylation sites is helpful for understanding the phosphorylation mechanism and regulation processes. Although a number of computational approaches have been developed, currently few studies are concerned about hierarchical structures of kinases, and most of the existing tools use only local sequence information to construct predictive models. In this work, we conduct a systematic and hierarchy-specific investigation of protein phosphorylation site prediction in which protein kinases are clustered into hierarchical structures with four levels including kinase, subfamily, family and group. To enhance phosphorylation site prediction at all hierarchical levels, functional information of proteins, including gene ontology (GO) and protein–protein interaction (PPI), is adopted in addition to primary sequence to construct prediction models based on random forest. Analysis of selected GO and PPI features shows that functional information is critical in determining protein phosphorylation sites for every hierarchical level. Furthermore, the prediction results of Phospho.ELM and additional testing dataset demonstrate that the proposed method remarkably outperforms existing phosphorylation prediction methods at all hierarchical levels. The proposed method is freely available at http://bioinformatics.ustc.edu.cn/phos_pred/.     

Strategies for the identification of kinase substrates using analog-sensitive kinases

Phosphorylation of proteins is a prevalent post-translational modification, which affects intracellular signaling in many ways. About 2% of all eukaryotic genes code for protein kinases catalyzing phosphorylation events. Despite technological advances that have made it possible to identify thousands of phosphorylation sites simultaneously, identification of the substrates of a given kinase remains an exceptionally challenging task. Here, we summarize approaches for substrate identification that make use of genetically engineered ‘analog-sensitive’ kinases.     

Phosphoproteome sequence analysis and significance: Mining association patterns around phosphorylation sites utilizing MAPRes

Phosphorylation, one of the most common protein post‐translational modifications (PTMs) on hydroxyl groups of S/T/Y is catalyzed by kinases and involves the presence or absence of certain amino acid residues in the vicinity of the phosphorylation sites. Using MAPRes, we have analyzed the substrate proteins of Phospho.ELM 7.0 and found that there are both general and specific requirements for the presence or absence of particular amino acids in the vicinity of phosphorylated S/T/Y for both of the phosphorylation data, whether or not kinase information was taken into account. Patterns extracted by MAPRes for kinase‐specific data have been utilized to find the consensus sequence motifs for various kinases required to catalyze the process of phosphorylation on S/T/Y. These consensus sequences for different kinase groups, families, and individual members are consistent with those described earlier with some novel consensus reported for the first time. A comparison study for the patterns mined by MAPRes with the results of existing prediction methods was performed by searching for these patterns in the vicinity of phosphorylation sites predicted by different available method. This comparison resulted in 87–98% conformity with the results of the predictions by available methods. Additionally, the patterns mined by MAPRes for substrate sites included 61 kinases, the highest number analyzed so far. J. Cell. Biochem. 108: 64–74, 2009. © 2009 Wiley‐Liss, Inc.     

Evolutionary Constraint and Disease Associations of Post-Translational Modification Sites in Human Genomes

Interpreting the impact of human genome variation on phenotype is challenging. The functional effect of protein-coding variants is often predicted using sequence conservation and population frequency data, however other factors are likely relevant. We hypothesized that variants in protein post-translational modification (PTM) sites contribute to phenotype variation and disease. We analyzed fraction of rare variants and non-synonymous to synonymous variant ratio (Ka/Ks) in 7,500 human genomes and found a significant negative selection signal in PTM regions independent of six factors, including conservation, codon usage, and GC-content, that is widely distributed across tissue-specific genes and function classes. PTM regions are also enriched in known disease mutations, suggesting that PTM variation is more likely deleterious. PTM constraint also affects flanking sequence around modified residues and increases around clustered sites, indicating presence of functionally important short linear motifs. Using target site motifs of 124 kinases, we predict that at least ∼180,000 motif-breaker amino acid residues that disrupt PTM sites when substituted, and highlight kinase motifs that show specific negative selection and enrichment of disease mutations. We provide this dataset with corresponding hypothesized mechanisms as a community resource. As an example of our integrative approach, we propose that PTPN11 variants in Noonan syndrome aberrantly activate the protein by disrupting an uncharacterized cluster of phosphorylation sites. Further, as PTMs are molecular switches that are modulated by drugs, we study mutated binding sites of PTM enzymes in disease genes and define a drug-disease network containing 413 novel predicted disease-gene links.     

A genome-wide analysis of sumoylation-related biological processes and functions in human nucleus

Protein sumoylation is an important reversible post-translational modification of proteins in the nucleus, and it orchestrates a variety of the cellular processes. Genome-wide analysis of functional abundance and distribution of Small Ubiquitin-related MOdifier (SUMO) substrates may shed a light on how sumoylation is involved in nuclear biological processes and functions. Two interesting questions about sumoylation have emerged: (1) how many SUMO substrates exist in mammalian proteomes, such as human and mouse, (2) and what are their functions and how are they involved in a variety of biological processes? To address these two questions,we present an in silico genome-scale analysis for SUMO substrates in human. Based on the pattern recognition and phylogenetic conservation, we retrieved a list of 2683 potential SUMO substrates conserved in both human and mouse. Then, by functional enrichment analysis, we surveyed the over-represented GO terms and functional domains of them against the whole human proteome. Besides the consistence between our analyses and in vivo or in vitro work, the in silico predicted candidates also point to several potential roles of sumoylation, e.g., perception of sound. These potential SUMO substrates in human are of great value for further in vivo or in vitro experimental analysis.     

Multiple phosphorylation sites in the 165-kilodalton peptide associated with dihydropyridine-sensitive calcium channels

Evidence from electrophysiological and ion flux studies has established that dihydropyridine-sensitive calcium channels are subject to regulation by neurotransmitter-mediated phosphorylation and dephosphorylation reactions. In the present study, we have further characterized the phosphorylation by cAMP-dependent protein kinase and a multifunctional Ca/calmodulin-dependent protein kinase of the membrane-associated form of the 165-kDa polypeptide identified as the skeletal muscle dihydropyridine receptor. The initial rates of phosphorylation of the 165-kDa peptide by both protein kinases were found to be relatively good compared to the rates of phosphorylation of established substrates of the enzymes. Phosphorylation of the 165-kDa peptide by both protein kinases was additive. Prior phosphorylation by either one of the kinases alone did not preclude phosphorylation by the second kinase. The cAMP-dependent protein kinase phosphorylated the 165-kDa peptide preferentially at serine residues, although a small amount of phosphothreonine was also formed. In contrast, after phosphorylation of the 165-kDa peptide by the Ca/calmodulin-dependent protein kinase, slightly more phosphothreonine than phosphoserine was recovered. Phosphopeptide mapping indicated that the two kinases phosphorylated the peptide at distinct as well as similar sites. Notably, one major site phosphorylated by the cAMP-dependent protein kinase was not phosphorylated by the Ca/calmodulin-dependent protein kinase, while other sites were phosphorylated to a high degree by the Ca/calmodulin-dependent protein kinase, but to a much lesser degree by the cAMP-dependent protein kinase. The results show that the 165-kDa dihydropyridine receptor from skeletal muscle can be multiply phosphorylated at distinct sites by the cAMP- and Ca/calmodulin-dependent protein kinases. As the 165-kDa peptide may be the major functional unit of the dihydropyridine-sensitive Ca channel, the results suggest that the phosphorylation-dependent modulation of Ca channel activity by neurotransmitters may involve phosphorylation of the 165-kDa peptide at multiple sites.