Tandem tyrosine phosphosites in the Enteropathogenic Escherichia coli chaperone CesT are required for differential type III effector translocation and virulence

Enteropathogenic Escherichia coli (EPEC) use a type 3 secretion system (T3SS) for injection of effectors into host cells and intestinal colonization. Here, we demonstrate that the multicargo chaperone CesT has two strictly conserved tyrosine phosphosites, Y152 and Y153 that regulate differential effector secretion in EPEC. Conservative substitution of both tyrosine residues to phenylalanine strongly attenuated EPEC type 3 effector injection into host cells, and limited Tir effector mediated intimate adherence during infection. EPEC expressing a CesT Y152F variant were deficient for NleA effector expression and exhibited significantly reduced translocation of NleA into host cells during infection. Other effectors were observed to be dependent on CesT Y152 for maximal translocation efficiency. Unexpectedly, EPEC expressing a CesT Y153F variant exhibited significantly enhanced effector translocation of many CesT‐interacting effectors, further implicating phosphosites Y152 and Y153 in CesT functionality. A mouse infection model of intestinal disease using Citrobacter rodentium revealed that CesT tyrosine substitution variants displayed delayed colonization and were more rapidly cleared from the intestine. These data demonstrate genetically separable functions for tandem tyrosine phosphosites within CesT. Therefore, CesT via its C‐terminal tyrosine phosphosites, has relevant roles beyond typical type III secretion chaperones that interact and stabilize effector proteins.     

Phosphorylation states greatly regulate the activity and gating properties of Cav3.1 T-type Ca2+ channels

Ca_v3.1 T-type Ca²⁺ channels play pivotal roles in neuronal low-threshold spikes, visceral pain, and pacemaker activity. Phosphorylation has been reported to potently regulate the activity and gating properties of Ca_v3.1 channels. However, systematic identification of phosphorylation sites (phosphosites) in Ca_v3.1 channel has been poorly investigated. In this work, we analyzed rat Ca_v3.1 protein expressed in HEK-293 cells by mass spectrometry, identified 30 phosphosites located at the cytoplasmic regions, and illustrated them as a Ca_v3.1 phosphorylation map which includes the reported mouse Ca_v3.1 phosphosites. Site-directed mutagenesis of the phosphosites to Ala residues and functional analysis of the phospho-silent Ca_v3.1 mutants expressed in Xenopus oocytes showed that the phospho-silent mutation of the N-terminal Ser18 reduced its current amplitude with accelerated current kinetics and negatively shifted channel availability. Remarkably, the phospho-silent mutations of the C-terminal Ser residues (Ser1924, Ser2001, Ser2163, Ser2166, or Ser2189) greatly reduced their current amplitude without altering the voltage-dependent gating properties. In contrast, the phosphomimetic Asp mutations of Ca_v3.1 on the N- and C-terminal Ser residues reversed the effects of the phospho-silent mutations. Collectively, these findings demonstrate that the multiple phosphosites of Ca_v3.1 at the N- and C-terminal regions play crucial roles in the regulation of the channel activity and voltage-dependent gating properties.     

Structure–sequence features based prediction of phosphosites of serine/threonine protein kinases of Mycobacterium tuberculosis

Elucidation of signaling events in a pathogen is potentially important to tackle the infection caused by it. Such events mediated by protein phosphorylation play important roles in infection, and therefore, to predict the phosphosites and substrates of the serine/threonine protein kinases, we have developed a Machine learning-based approach for Mycobacterium tuberculosis serine/threonine protein kinases using kinase-peptide structure–sequence data. This approach utilizes features derived from kinase three-dimensional-structure environment and known phosphosite sequences to generate support vector machine (SVM)-based kinase-specific predictions of phosphosites of serine/threonine protein kinases (STPKs) with no or scarce data of their substrates. SVM outperformed the four machine learning algorithms we tried (random forest, logistic regression, SVM, and k-nearest neighbors) with an area under the curve receiver-operating characteristic value of 0.88 on the independent testing dataset and a 10-fold cross-validation accuracy of ~81.6% for the final model. Our predicted phosphosites of M. tuberculosis STPKs form a useful resource for experimental biologists enabling elucidation of STPK mediated posttranslational regulation of important cellular processes.     

Phosphorylation network rewiring by gene duplication

Elucidating how complex regulatory networks have assembled during evolution requires a detailed understanding of the evolutionary dynamics that follow gene duplication events, including changes in post‐translational modifications. We compared the phosphorylation profiles of paralogous proteins in the budding yeast Saccharomyces cerevisiae to that of a species that diverged from the budding yeast before the duplication of those genes. We found that 100 million years of post‐duplication divergence are sufficient for the majority of phosphorylation sites to be lost or gained in one paralog or the other, with a strong bias toward losses. However, some losses may be partly compensated for by the evolution of other phosphosites, as paralogous proteins tend to preserve similar numbers of phosphosites over time. We also found that up to 50% of kinase–substrate relationships may have been rewired during this period. Our results suggest that after gene duplication, proteins tend to subfunctionalize at the level of post‐translational regulation and that even when phosphosites are preserved, there is a turnover of the kinases that phosphorylate them.     

In Silico Analysis of Phosphoproteome Data Suggests a Rich-get-richer Process of Phosphosite Accumulation over Evolution

Recent phosphoproteome analyses using mass spectrometry-based technologies have provided new insights into the extensive presence of protein phosphorylation in various species and have raised the interesting question of how this protein modification was gained evolutionarily on such a large scale. We investigated this issue by using human and mouse phosphoproteome data. We initially found that phosphoproteins followed a power-law distribution with regard to their number of phosphosites: most of the proteins included only a few phosphosites, but some included dozens of phosphosites. The power-law distribution, unlike more commonly observed distributions such as normal and log-normal distributions, is considered by the field of complex systems science to be produced by a specific rich-get-richer process called preferential attachment growth. Therefore, we explored the factors that may have promoted the rich-get-richer process during phosphosite evolution. We conducted a bioinformatics analysis to evaluate the relationship of amino acid sequences of phosphoproteins with the positions of phosphosites and found an overconcentration of phosphosites in specific regions of protein surfaces and implications that in many phosphoproteins these clusters of phosphosites are activated simultaneously. Multiple phosphosites concentrated in limited spaces on phosphoprotein surfaces may therefore function biologically as cooperative modules that are resistant to selective pressures during phosphoprotein evolution. We therefore proposed a hypothetical model by which the modularization of multiple phosphosites has been resistant to natural selection and has driven the rich-get-richer process of the evolutionary growth of phosphosite numbers.Protein phosphorylation is an important and ubiquitous post-translational modification that regulates a variety of biological processes in various organisms (1–4). Reversible phosphorylations of serine, threonine, and tyrosine residues are critical steps in the control of signal transduction pathways (1–4). Recent advances in MS-based technologies and phosphopeptide enrichment methods have allowed high throughput and large scale in vivo phosphosite mapping for a wide variety of organisms such as human (5–8), mouse (9), yeast (10–12), fly (13,14), bacteria (15,16), and plants (17–19). Moreover information on several hundred to several thousand phosphosites from each study has been gathered in public databases such as Phospho.ELM (20), PhosphoSitePlus, PHOSIDA (21), and UniProt (22). However, the total number of phosphosites and most of their biological functions are still unknown. Similarly only about 10% of the estimated 500–600 human kinases target known phosphosite consensus sequences within their substrate proteins (23). Although the tyrosine phosphoproteome in Arabidopsis was recently published (24), the corresponding tyrosine kinases have not been identified because of the lack of known consensus sequences activated by tyrosine kinases.Computational data-mining approaches have been required to extract information from the large amount of accumulated phosphosite data obtained from experimental approaches. These approaches have also been used to add more meaningful information about each of the phosphosites to understand the proteome-wide protein phosphorylation in various organisms. One of the most useful strategies of computational data mining is to identify phosphorylated sequence motifs by extracting consensus sequences from the sets of amino acid sequences clustered around phosphorylated residues (25). A number of kinases and their corresponding recognition substrate motifs have been successfully identified by the experimental approach of incubating each target kinase with a combinatorial substrate peptide library and ATP, and these data are registered in various databases, including the Human Protein Reference Database (HPRD)¹ (26). With this knowledge of documented kinases and their related sequence motifs, we can use computational biology techniques to discover additional phosphorylated motifs in the numerous substrates shown in phosphoproteomics studies to be biologically phosphorylated. This has allowed us to reconstruct the kinome on a large scale (27–29).A comparative study of phosphoproteome data in multiple species has revealed that a wide range of phosphoproteins are relatively well conserved relative to non-phosphoproteins, and similarly many phosphoserine (Ser(P)), phosphothreonine (Thr(P)), and phosphotyrosine (Tyr(P)) phosphosites are well conserved compared with non-phosphorylated sites (21). Under natural selection, the emergence of phosphoproteins and the gain and loss of phosphosites should have changed the regulation of many intracellular systems, such as kinetic pathways, subcellular protein localization, and protein interactions and stabilization. This triggered our interest in the evolution of phosphoproteins and their phosphosites.In this study, we combined statistical physics and computational biology to investigate the role of selective pressure in the evolution of phosphoproteins and to create a model of the evolutionary gain of phosphosites. First using the human and mouse phosphoproteome data registered in public databases, we discovered that the number of phosphosites in each phosphoprotein follows a power-law distribution, which has been shown in complex systems science and statistical physics to emerge through a specific rich-get-richer process called preferential attachment growth (30–32). We therefore hypothesized that phosphoproteins may have evolved through a rich-get-richer process, gaining new phosphosites according to a probability density proportional to their current number of phosphosites. Starting from this hypothesis, we then explored how this particular evolutionary pattern may have arisen during natural selection and suggested that sets of phosphosites localized in limited spaces on protein surfaces may function as cooperative modules that are resistant to selective pressures. Therefore, to explain phosphosite evolution, we proposed a model in which the evolutionary gain of phosphosites follows a rich-get-richer process and evolution is promoted by the development of cooperative functional modules on protein surfaces.     

Dynamic Phosphoproteome Profiling of Zebrafish Embryonic Fibroblasts during Cold Acclimation

Temperature affects almost all aspects of the fish life. To cope with low temperature, fish have evolved the ability of cold acclimation for survival. However, intracellular signaling events underlying cold acclimation in fish remain largely unknown. Here, the formation of cold acclimation in zebrafish embryonic fibroblasts (ZF4) is monitored and the phosphorylation events during the process are investigated through a large‐scale quantitative phosphoproteomic approach. In total, 11 474 phosphorylation sites are identified on 4066 proteins and quantified 5772 phosphosites on 2519 proteins. Serine, threonine, and tyrosine (Ser/Thr/Tyr) phosphorylation accounted for 85.5%, 13.3%, and 1.2% of total phosphosites, respectively. Among all phosphosites, 702 phosphosites on 510 proteins show differential regulation during cold acclimation of ZF4 cells. These phosphosites are divided into six clusters according to their dynamic changes during cold exposure. Kinase–substrate prediction reveals that mitogen‐activated protein kinase (MAPK) among the kinase groups is predominantly responsible for phosphorylation of these phosphosites. The differentially regulated phosphoproteins are functionally associated with various cellular processes such as regulation of actin cytoskeleton and MAPK signaling pathway. These data enrich the database of protein phosphorylation sites in zebrafish and provide key clues for the elucidation of intracellular signaling networks during cold acclimation of fish.     

PhoPepMass: A database and search tool assisting human phosphorylation peptide identification from mass spectrometry data

Protein phosphorylation, one of the most important protein post-translational modifications, is involved in various biological processes, and the identification of phosphorylation peptides (phosphopeptides) and their corresponding phosphorylation sites (phosphosites) will facilitate the understanding of the molecular mechanism and function of phosphorylation. Mass spectrometry (MS) provides a high-throughput technology that enables the identification of large numbers of phosphosites. PhoPepMass is designed to assist human phosphopeptide identification from MS data based on a specific database of phophopeptide masses and a multivariate hypergeometric matching algorithm. It contains 244,915 phosphosites from several public sources. Moreover, the accurate masses of peptides and fragments with phosphosites were calculated. It is the first database that provides a systematic resource for the query of phosphosites on peptides and their corresponding masses. This allows researchers to search certain proteins of which phosphosites have been reported, to browse detailed phosphopeptide and fragment information, to match masses from MS analyses with defined threshold to the corresponding phosphopeptide, and to compare proprietary phosphopeptide discovery results with results from previous studies. Additionally, a database search software is created and a “two-stage search strategy” is suggested to identify phosphopeptides from tandem mass spectra of proteomics data. We expect PhoPepMass to be a useful tool and a source of reference for proteomics researchers. PhoPepMass is available at https://www.scbit.org/phopepmass/index.html.     

Evolution of protein phosphorylation for distinct functional modules in vertebrate genomes

Recent publications have revealed that the evolution of phosphosites is influenced by the local protein structures and whether the phosphosites have characterized functions or not. With knowledge of the wide functional range of phosphorylation, we attempted to clarify whether the evolutionary conservation of phosphosites is different among distinct functional modules. We grouped the phosphosites in the human genome into the modules according to the functional categories of KEGG (Kyoto Encyclopedia of Genes and Genomes) and investigated their evolutionary conservation in vertebrate genomes from mouse to zebrafish. We have found that the phosphosites in the vertebrate-specific functional modules (VFMs), such as cellular signaling processes and responses to stimuli, are evolutionarily more conserved than those in the basic functional modules (BFMs), such as metabolic and genetic processes. The phosphosites in the VFMs are also significantly more conserved than their flanking regions, whereas those in the BFMs are not. These results hold for both serine/threonine and tyrosine residues, although the fraction of phosphorylated tyrosine residues is increased in the VFMs. Moreover, the difference in the evolutionary conservation of the phosphosites between the VFMs and BFMs could not be explained by the difference in the local protein structures. There is also a higher fraction of phosphosites with known functions in the VFMs than BFMs. Based on these findings, we have concluded that protein phosphorylation may play more dominant roles for the VFMs than BFMs during the vertebrate evolution. As phosphorylation is a quite rapid biological reaction, the VFMs that quickly respond to outer stimuli and inner signals might heavily depend on this regulatory mechanism. Our results imply that phosphorylation may have an essential role in the evolution of vertebrates.     

CPhos: A program to calculate and visualize evolutionarily conserved functional phosphorylation sites

Profiling using high‐throughput MS has discovered an overwhelming number of novel protein phosphorylation sites (“phosphosites”). However, the functional relevance of these sites is not always clear. In light of recent studies on the evolutionary mechanism of phosphorylation, we have developed CPhos, a Java program that can assess the conservation of phosphosites among species using an information theory‐based approach. The degree of conservation established using CPhos can be used to assess the functional significance of phosphosites. CPhos has a user friendly graphical user interface and is available both as a web service and as a standalone Java application to assist phosphoproteomic researchers in analyzing and prioritizing lists of phosphosites for further experimental validation. CPhos can be accessed or downloaded at http://helixweb.nih.gov/CPhos/ .     

Prediction of Functionally Important Phospho-Regulatory Events in Xenopus laevis Oocytes

The African clawed frog Xenopus laevis is an important model organism for studies in developmental and cell biology, including cell-signaling. However, our knowledge of X. laevis protein post-translational modifications remains scarce. Here, we used a mass spectrometry-based approach to survey the phosphoproteome of this species, compiling a list of 2636 phosphosites. We used structural information and phosphoproteomic data for 13 other species in order to predict functionally important phospho-regulatory events. We found that the degree of conservation of phosphosites across species is predictive of sites with known molecular function. In addition, we predicted kinase-protein interactions for a set of cell-cycle kinases across all species. The degree of conservation of kinase-protein interactions was found to be predictive of functionally relevant regulatory interactions. Finally, using comparative protein structure models, we find that phosphosites within structured domains tend to be located at positions with high conformational flexibility. Our analysis suggests that a small class of phosphosites occurs in positions that have the potential to regulate protein conformation.     

Quantitative proteomics indicate a strong correlation of mitotic phospho-/dephosphorylation with non-structured regions of substrates

Protein phosphorylation plays a critical role in the regulation and progression of mitosis. >40,000 phosphorylated residues and the associated kinases have been identified to date via proteomic analyses. Although some of these phosphosites are associated with regulation of either protein-protein interactions or the catalytic activity of the substrate protein, the roles of most mitotic phosphosites remain unclear. In this study, we examined structural properties of mitotic phosphosites and neighboring residues to understand the role of heavy phosphorylation in non-structured domains. Quantitative mass spectrometry analysis of mitosis-arrested and non-arrested HeLa cells revealed >4100 and > 2200 residues either significantly phosphorylated or dephosphorylated, respectively, at mitotic entry. The calculated disorder scores of amino acid sequences of neighboring individual phosphosites revealed that >70% of dephosphorylated phosphosites exist in disordered regions, whereas 50% of phosphorylated sites exist in non-structured domains. A clear inverse correlation was observed between probability of phosphorylation in non-structured domain and increment of phosphorylation in mitosis. These results indicate that at entry to mitosis, a significant number of phosphate groups are removed from non-structured domains and transferred to more-structured domains. Gene ontology term analysis revealed that mitosis-related proteins are heavily phosphorylated, whereas RNA-related proteins are both dephosphorylated and phosphorylated, suggesting that heavy phosphorylation/dephosphorylation in non-structured domains of RNA-binding proteins plays a role in dynamic rearrangement of RNA-containing organelles, as well as other intracellular environments.     

Cooperativity within proximal phosphorylation sites is revealed from large-scale proteomics data

Background  

Phosphorylation is the most prevalent post-translational modification on eukaryotic proteins. Multisite phosphorylation enables a specific combination of phosphosites to determine the speed, specificity and duration of biological response. Until recent years, the lack of high quality data limited the possibility for analyzing the properties of phosphorylation at the proteome scale and in the context of a wide range of conditions. Thanks to advances of mass spectrometry technologies, thousands of phosphosites from in-vivo experiments were identified and archived in the public domain. Such resource is appropriate to derive an unbiased view on the phosphosites properties in eukaryotes and on their functional relevance.     

Untargeted metabolomics unravels functionalities of phosphorylation sites in <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis>

Background

Coordinated through a complex network of kinases and phosphatases, protein phosphorylation regulates essentially all cellular processes in eukaryotes. Recent advances in proteomics enable detection of thousands of phosphorylation sites (phosphosites) in single experiments. However, functionality of the vast majority of these sites remains unclear and we lack suitable approaches to evaluate functional relevance at a pace that matches their detection.

Results

Here, we assess functionality of 26 phosphosites by introducing phosphodeletion and phosphomimic mutations in 25 metabolic enzymes and regulators from the TOR and HOG signaling pathway in Saccharomyces cerevisiae by phenotypic analysis and untargeted metabolomics. We show that metabolomics largely outperforms growth analysis and recovers 10 out of the 13 previously characterized phosphosites and suggests functionality for several novel sites, including S79 on the TOR regulatory protein Tip41. We analyze metabolic profiles to identify consequences underlying regulatory phosphorylation events and detecting glycerol metabolism to have a so far unknown influence on arginine metabolism via phosphoregulation of the glycerol dehydrogenases. Further, we also find S508 in the MAPKK Pbs2 as a potential link for cross-talking between HOG signaling and the cell wall integrity pathway.

Conclusions

We demonstrate that metabolic profiles can be exploited for gaining insight into regulatory consequences and biological roles of phosphosites. Altogether, untargeted metabolomics is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of phosphosites.

     

Comparison of ERLIC-TiO2, HILIC-TiO2, and SCX-TiO2 for global phosphoproteomics approaches

Reversible phosphorylations play a critical role in most biological pathways. Hence, in signaling studies great effort has been put into identification of a maximum number of phosphosites per experiment. Mass spectrometry (MS)-based phosphoproteomics approaches have been proven to be an ideal analytical method for mapping of phosphosites. However, because of sample complexity, fractionation of phosphopeptides prior to MS analysis is a crucial step. In the current study, we compare the chromatographic strategies electrostatic repulsion-hydrophilic interaction chromatography (ERLIC), hydrophilic interaction liquid chromatography (HILIC), and strong cation exchange chromatography (SCX) for their fractionation behavior of phosphopeptides. In addition, we investigate the use of repetitive TiO(2)-based enrichment steps for a maximum identification of phosphopeptides. On the basis of our results, SCX yields the highest number of identified phosphopeptides, whereas ERLIC is optimal for the identification of multiphosphorylated peptides. Consecutive incubations of fractions and flow-through by TiO(2) beads enrich qualitatively different sets of phosphopeptides, increasing the number of identified phosphopeptides per analysis.     

A dataset resource for clinically associated phosphosites in hepatocellular carcinoma

Phosphorylation is one of the most common post-translational modifications (PTMs) and is closely related to protein activity and function, playing a critical role during cancer development. Quantitative phosphoproteomic strategies have been widely used to study the underlying mechanisms of cancer progression or drug resistance. In this report, we analyzed the association of phosphosite levels originated from our previously reported proteogenomic study in hepatocellular carcinoma (HCC) with clinical parameters, including prognosis, recurrence, and Tumor–Node–Metastasis (TNM) stages. By using both the log-rank test and univariate Cox proportional hazards regression analysis, we found that the abundance levels of 1712 phosphosites were associated with prognosis and those of 393 phosphosites associated with recurrence. Besides, 692 phosphosites had different abundance levels among TNM stages (I, II, III+IV) by Analysis of Variance (ANOVA) test. Gene ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using proteins with these statistically significant phosphosites. In conclusion, we provided a dataset resource for clinically associated phosphosites in HCC, which may be beneficial to liver cancer related basic research.     

Phosphorylation at the interface

Proteomic studies have identified thousands of eukaryotic phosphorylation sites (phosphosites), but few are functionally characterized. Nishi et?al., in this issue of Structure, characterize phosphosites at protein-protein interfaces and estimate the effect of their phosphorylation on interaction affinity, by combining proteomics data with protein structures.     

Protein abundance is key to distinguish promiscuous from functional phosphorylation based on evolutionary information

In eukaryotic cells, protein phosphorylation is an important and widespread mechanism used to regulate protein function. Yet, of the thousands of phosphosites identified to date, only a few hundred at best have a characterized function. It was recently shown that these functional sites are significantly more conserved than phosphosites of unknown function, stressing the importance of considering evolutionary conservation in assessing the global functional landscape of phosphosites. This leads us to review studies that examined the impact of phosphorylation on evolutionary conservation. While all these studies have shown that conservation is greater among phosphorylated sites compared with non-phosphorylated ones, the magnitude of this difference varies greatly. Further, not all studies have considered key factors that may influence the rate of phosphosite evolution. Such key factors are their localization in ordered or disordered regions, their stoichiometry or the abundance of their corresponding protein. Here we take into account all of these factors simultaneously, which reveals remarkable evolutionary patterns. First, while it is well established that protein conservation increases with abundance, we show that phosphosites partly follow an opposite trend. More precisely, Saccharomyces cerevisiae phosphosites present among abundant proteins are 1.5 times more likely to diverge in the closely related species Saccharomyces bayanus when compared with phosphosites present in the 5 per cent least abundant proteins. Second, we show that conservation is coupled to stoichiometry, whereby sites frequently phosphorylated are more conserved than those rarely phosphorylated. Finally, we provide a model of functional and noisy or 'accidental' phosphorylation that explains these observations.     

A highly multiplexed quantitative phosphosite assay for biology and preclinical studies

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho‐signaling in drug‐treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.     

Protein kinases phosphorylate long disordered regions in intrinsically disordered proteins

Phosphorylation is a major post‐translational modification that plays a central role in signaling pathways. Protein kinases phosphorylate substrates (phosphoproteins) by adding phosphate at Ser/Thr or Tyr residues (phosphosites). A large amount of data identifying and describing phosphosites in phosphoproteins has been reported but the specificity of phosphorylation is not fully resolved. In this report, data of kinase‐substrate pairs identified by the Kinase‐Interacting Substrate Screening (KISS) method were used to analyze phosphosites in intrinsically disordered regions (IDRs) of intrinsically disordered proteins. We compared phosphorylated and nonphosphorylated IDRs and found that the phosphorylated IDRs were significantly longer than nonphosphorylated IDRs. The phosphorylated IDR is often the longest IDR (71%) in a phosphoprotein when only a single phosphosite exists in the IDR, and when the phosphoprotein has multiple phosphosites in an IDR(s), the phosphosites are primarily localized in a single IDR (78%) and this IDR is usually the longest one (81%). We constructed a stochastic model of phosphorylation to estimate the effect of IDR length. The model that accounted for IDR length produced more realistic results when compared with a model that excluded the IDR length. We propose that the IDR length is a significant determinant for locating kinase phosphorylation sites in phosphoproteins.