PTMcode v2: a resource for functional associations of post-translational modifications within and between proteins

Unravelling the pathogenic role and genotype-phenotype correlation of the USH2A p.(Cys759Phe) variant among Spanish families

INTRODUCTION

Mutations in USH2A cause both isolated Retinitis Pigmentosa (RP) and Usher syndrome (that implies RP and hearing impairment). One of the most frequent variants identified in this gene and among these patients is the p.(Cys759Phe) change. However, the pathogenic role of this allele has been questioned since it was found in homozygosity in two healthy siblings of a Spanish family. To assess the causative role of USH2A p.(Cys759Phe) in autosomal recessive RP (ARRP) and Usher syndrome type II (USH2) and to establish possible genotype-phenotype correlations associated with p.(Cys759Phe), we performed a comprehensive genetic and clinical study in patients suffering from any of the two above-mentioned diseases and carrying at least one p.(Cys759Phe) allele.

MATERIALS AND METHODS

Diagnosis was set according to previously reported protocols. Genetic analyses were performed by using classical molecular and Next-Generation Sequencing approaches. Probands of 57 unrelated families were molecularly studied and 63 patients belonging to these families were phenotypically evaluated.

RESULTS

Molecular analysis characterized 100% of the cases, identifying: 11 homozygous patients for USH2A p.(Cys759Phe), 42 compound heterozygous patients (12 of them with another missense USH2A pathogenic variant and 30 with a truncating USH2A variant), and 4 patients carrying the p.(Cys759Phe) allele and a pathogenic variant in another RP gene (PROM1, CNGB1 or RP1). No additional causative variants were identified in symptomatic homozygous patients. Statistical analysis of clinical differences between zygosity states yielded differences (p≤0.05) in age at diagnosis of RP and hypoacusis, and progression of visual field loss. Homozygosity of p.(Cys759Phe) and compound heterozygosity with another USH2A missense variant is associated with ARRP or ARRP plus late onset hypoacusis (OR = 20.62, CI = 95%, p = 0.041).

CONCLUSIONS

The present study supports the role of USH2A p.(Cys759Phe) in ARRP and USH2 pathogenesis, and demonstrates the clinical differences between different zygosity states. Phenotype-genotype correlations may guide the genetic characterization based upon specific clinical signs and may advise on the clinical management and prognosis based upon a specific genotype.

Dissecting Structure-Encoded Determinants of Allosteric Cross-Talk between Post-Translational Modification Sites in the Hsp90 Chaperones

Post-translational modifications (PTMs) represent an important regulatory instrument that modulates structure, dynamics and function of proteins. The large number of PTM sites in the Hsp90 proteins that are scattered throughout different domains indicated that synchronization of multiple PTMs through a combinatorial code can be invoked as an important mechanism to orchestrate diverse chaperone functions and recognize multiple client proteins. In this study, we have combined structural and coevolutionary analysis with molecular simulations and perturbation response scanning analysis of the Hsp90 structures to characterize functional role of PTM sites in allosteric regulation. The results reveal a small group of conserved PTMs that act as global mediators of collective dynamics and allosteric communications in the Hsp90 structures, while the majority of flexible PTM sites serve as sensors and carriers of the allosteric structural changes. This study provides a comprehensive structural, dynamic and network analysis of PTM sites across Hsp90 proteins, identifying specific role of regulatory PTM hotspots in the allosteric mechanism of the Hsp90 cycle. We argue that plasticity of a combinatorial PTM code in the Hsp90 may be enacted through allosteric coupling between effector and sensor PTM residues, which would allow for timely response to structural requirements of multiple modified enzymes.

PTMscape: an open source tool to predict generic post-translational modifications and map modification crosstalk in protein domains and biological processes

PTMscape predicts PTM sites using descriptors of sequence and physico-chemical microenvironment, and tests enrichment of single or pairs of PTMs in protein domains.

While tandem mass spectrometry can detect post-translational modifications (PTM) at the proteome scale, reported PTM sites are often incomplete and include false positives. Computational approaches can complement these datasets by additional predictions, but most available tools use prediction models pre-trained for single PTM type by the developers and it remains a difficult task to perform large-scale batch prediction for multiple PTMs with flexible user control, including the choice of training data. We developed an R package called PTMscape which predicts PTM sites across the proteome based on a unified and comprehensive set of descriptors of the physico-chemical microenvironment of modified sites, with additional downstream analysis modules to test enrichment of individual or pairs of PTMs in protein domains. PTMscape is flexible in the ability to process any major modifications, such as phosphorylation and ubiquitination, while achieving the sensitivity and specificity comparable to single-PTM methods and outperforming other multi-PTM tools. Applying this framework, we expanded proteome-wide coverage of five major PTMs affecting different residues by prediction, especially for lysine and arginine modifications. Using a combination of experimentally acquired sites (PSP) and newly predicted sites, we discovered that the crosstalk among multiple PTMs occur more frequently than by random chance in key protein domains such as histone, protein kinase, and RNA recognition motifs, spanning various biological processes such as RNA processing, DNA damage response, signal transduction, and regulation of cell cycle. These results provide a proteome-scale analysis of crosstalk among major PTMs and can be easily extended to other types of PTM.

Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era

Advances in next-generation sequencing technologies have generated the data supporting a large volume of somatic alterations in several national and international cancer genome projects, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. These cancer genomics data have facilitated the revolution of a novel oncology drug discovery paradigm from candidate target or gene studies toward targeting clinically relevant driver mutations or molecular features for precision cancer therapy. This focuses on identifying the most appropriately targeted therapy to an individual patient harboring a particularly genetic profile or molecular feature. However, traditional experimental approaches that are used to develop new chemical entities for targeting the clinically relevant driver mutations are costly and high-risk. Drug repositioning, also known as drug repurposing, re-tasking or re-profiling, has been demonstrated as a promising strategy for drug discovery and development. Recently, computational techniques and methods have been proposed for oncology drug repositioning and identifying pharmacogenomics biomarkers, but overall progress remains to be seen. In this review, we focus on introducing new developments and advances of the individualized network-based drug repositioning approaches by targeting the clinically relevant driver events or molecular features derived from cancer panomics data for the development of precision oncology drug therapies (e.g. one-person trials) to fully realize the promise of precision medicine. We discuss several potential challenges (e.g. tumor heterogeneity and cancer subclones) for precision oncology. Finally, we highlight several new directions for the precision oncology drug discovery via biotherapies (e.g. gene therapy and immunotherapy) that target the 'undruggable' cancer genome in the functional genomics era.

Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer

Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer.

Co-occurring protein phosphorylation are functionally associated

Post-translational modifications (PTMs) add a further layer of complexity to the proteome and regulate a wide range of cellular protein functions. With the increasing number of known PTM sites, it becomes imperative to understand their functional interplays. In this study, we proposed a novel analytical strategy to explore functional relationships between PTM sites by testing their tendency to be modified together (co-occurrence) under the same condition, and applied it to proteome-wide human phosphorylation data collected under 88 different laboratory or physiological conditions. Co-occurring phosphorylation occurs significantly more frequently than randomly expected and include many known examples of cross-talk or functional connections. Such pairs, either within the same phosphoprotein or between interacting partners, are more likely to be in sequence or structural proximity, be phosphorylated by the same kinases, participate in similar biological processes, and show residue co-evolution across vertebrates. In addition, we also found that their co-occurrence states tend to be conserved in orthologous phosphosites in the mouse proteome. Together, our results support that the co-occurring phosphorylation are functionally associated. Comparison with existing methods further suggests that co-occurrence analysis can be a useful complement to uncover novel functional associations between PTM sites.

In addition to gene expression and translation control, post-translational modifications (PTMs) represent another level to regulate proteins functions. Different PTM sites within a protein usually co-operate to fulfill their functional roles. Recent advances in high-throughput mass spectrometry (MS) technologies have facilitated the proteome-wide identification of PTM sites, giving rise to both challenge and opportunity to understand their functional relationships. Previously, several data mining approaches have been developed to explore the global PTM interplays. In this study, we proposed to infer functional associations between PTM sites from the correlation of their modification status across many biological conditions, which was not exploited before. In practice, we tested if a pair of sites are modified together under the same condition significantly more often than expected (co-occurrence). As a proof of principle, we applied this analytical strategy to human phosphorylation because we could collect data sets of proteome-wide coverage under 88 different conditions. We demonstrated that sites with co-occurring phosphorylation status are functionally associated from several lines of evidence. The co-occurrence analysis can also uncover functionally connected phosphosites with clear biological evidence which are missed by other approaches. With increasing proteome-wide data for other types of PTMs under different conditions, the co-occurrence analysis can be integrated with other methods to identify novel PTM associations.

PTMOracle: A Cytoscape App for Covisualizing and Coanalyzing Post-Translational Modifications in Protein Interaction Networks

Post-translational modifications of proteins (PTMs) act as key regulators of protein activity and of protein-protein interactions (PPIs). To date, it has been difficult to comprehensively explore functional links between PTMs and PPIs. To address this, we developed PTMOracle, a Cytoscape app for coanalyzing PTMs within PPI networks. PTMOracle also allows extensive data to be integrated and coanalyzed with PPI networks, allowing the role of domains, motifs, and disordered regions to be considered. For proteins of interest, or a whole proteome, PTMOracle can generate network visualizations to reveal complex PTM-associated relationships. This is assisted by OraclePainter for coloring proteins by modifications, OracleTools for network analytics, and OracleResults for exploring tabulated findings. To illustrate the use of PTMOracle, we investigate PTM-associated relationships and their role in PPIs in four case studies. In the yeast interactome and its rich set of PTMs, we construct and explore histone-associated and domain-domain interaction networks and show how integrative approaches can predict kinases involved in phosphodegrons. In the human interactome, a phosphotyrosine-associated network is analyzed but highlights the sparse nature of human PPI networks and lack of PTM-associated data. PTMOracle is open source and available at the Cytoscape app store: http://apps.cytoscape.org/apps/ptmoracle .

Systematic identification of phosphorylation-mediated protein interaction switches

Proteomics techniques can identify thousands of phosphorylation sites in a single experiment, the majority of which are new and lack precise information about function or molecular mechanism. Here we present a fast method to predict potential phosphorylation switches by mapping phosphorylation sites to protein-protein interactions of known structure and analysing the properties of the protein interface. We predict 1024 sites that could potentially enable or disable particular interactions. We tested a selection of these switches and showed that phosphomimetic mutations indeed affect interactions. We estimate that there are likely thousands of phosphorylation mediated switches yet to be uncovered, even among existing phosphorylation datasets. The results suggest that phosphorylation sites on globular, as distinct from disordered, parts of the proteome frequently function as switches, which might be one of the ancient roles for kinase phosphorylation.

Bioinformatics Analysis of Functional Associations of PTMs

Post-translational modifications (PTMs) are an important source of protein regulation; they fine-tune the function, localization, and interaction with other molecules of the majority of proteins and are partially responsible for their multifunctionality. Usually, proteins have several potential modification sites, and their patterns of occupancy are associated with certain functional states. These patterns imply cross talk among PTMs within and between proteins, the majority of which are still to be discovered. Several methods detect associations between PTMs; these have recently combined into a global resource, the PTMcode database, which contains already known and predicted functional associations between pairs of PTMs from more than 45,000 proteins in 19 eukaryotic species.

proGenomes: a resource for consistent functional and taxonomic annotations of prokaryotic genomes

The availability of microbial genomes has opened many new avenues of research within microbiology. This has been driven primarily by comparative genomics approaches, which rely on accurate and consistent characterization of genomic sequences. It is nevertheless difficult to obtain consistent taxonomic and integrated functional annotations for defined prokaryotic clades. Thus, we developed proGenomes, a resource that provides user-friendly access to currently 25 038 high-quality genomes whose sequences and consistent annotations can be retrieved individually or by taxonomic clade. These genomes are assigned to 5306 consistent and accurate taxonomic species clusters based on previously established methodology. proGenomes also contains functional information for almost 80 million protein-coding genes, including a comprehensive set of general annotations and more focused annotations for carbohydrate-active enzymes and antibiotic resistance genes. Additionally, broad habitat information is provided for many genomes. All genomes and associated information can be downloaded by user-selected clade or multiple habitat-specific sets of representative genomes. We expect that the availability of high-quality genomes with comprehensive functional annotations will promote advances in clinical microbial genomics, functional evolution and other subfields of microbiology. proGenomes is available at http://progenomes.embl.de.

DAPPLE 2: a Tool for the Homology-Based Prediction of Post-Translational Modification Sites

The post-translational modification of proteins is critical for regulating their function. Although many post-translational modification sites have been experimentally determined, particularly in certain model organisms, experimental knowledge of these sites is severely lacking for many species. Thus, it is important to be able to predict sites of post-translational modification in such species. Previously, we described DAPPLE, a tool that facilitates the homology-based prediction of one particular post-translational modification, phosphorylation, in an organism of interest using known phosphorylation sites from other organisms. Here, we describe DAPPLE 2, which expands and improves upon DAPPLE in three major ways. First, it predicts sites for many post-translational modifications (20 different types) using data from several sources (15 online databases). Second, it has the ability to make predictions approximately 2-7 times faster than DAPPLE depending on the database size and the organism of interest. Third, it simplifies and accelerates the process of selecting predicted sites of interest by categorizing them based on gene ontology terms, keywords, and signaling pathways. We show that DAPPLE 2 can successfully predict known human post-translational modification sites using, as input, known sites from species that are either closely (e.g., mouse) or distantly (e.g., yeast) related to humans. DAPPLE 2 can be accessed at http://saphire.usask.ca/saphire/dapple2 .

Systems Level Analysis of Histone H3 Post-translational Modifications (PTMs) Reveals Features of PTM Crosstalk in Chromatin Regulation

Histones are abundant chromatin constituents carrying numerous post-translational modifications (PTMs). Such PTMs mediate a variety of biological functions, including recruitment of enzymatic readers, writers and erasers that modulate DNA replication, transcription and repair. Individual histone molecules contain multiple coexisting PTMs, some of which exhibit crosstalk, i.e. coordinated or mutually exclusive activities. Here, we present an integrated experimental and computational systems level molecular characterization of histone PTMs and PTM crosstalk. Using wild type and engineered mouse embryonic stem cells (mESCs) knocked out in components of the Polycomb Repressive Complex 2 (PRC2, Suz12(-/-)), PRC1 (Ring1A/B(-/-)) and (Dnmt1/3a/3b(-/-)) we performed comprehensive PTM analysis of histone H3 tails (50 aa) by utilizing quantitative middle-down proteome analysis by tandem mass spectrometry. We characterized combinatorial PTM features across the four mESC lines and then applied statistical data analysis to predict crosstalk between histone H3 PTMs. We detected an overrepresentation of positive crosstalk (codependent marks) between adjacent mono-methylated and acetylated marks, and negative crosstalk (mutually exclusive marks) among most of the seven characterized di- and tri-methylated lysine residues in the H3 tails. We report novel features of PTM interplay involving hitherto poorly characterized arginine methylation and lysine methylation sites, including H3R2me, H3R8me and H3K37me. Integration of the H3 data with RNAseq data by coabundance clustering analysis of histone PTMs and histone modifying enzymes revealed correlations between PTM and enzyme levels. We conclude that middle-down proteomics is a powerful tool to determine conserved or dynamic interdependencies between histone marks, which paves the way for detailed investigations of the histone code. Histone H3 PTM data is publicly available in the CrossTalkDB repository at http://crosstalkdb.bmb.sdu.dk.

Engineering of Methylation State Specific 3xMBT Domain Using ELISA Screening

The ε-amino group of lysine residues may be mono-, di- or tri-methylated by protein lysine methyltransferases. In the past few years it has been highly considered that methylation of both histone and non-histone proteins has fundamental role in development and progression of various human diseases. Thus, the establishment of tools to study lysine methylation that will distinguish between the different states of methylation is required to elucidate their cellular functions. The 3X malignant brain tumor domain (3XMBT) repeats of the Lethal(3)malignant brain tumor-like protein 1 (L3MBTL1) have been utilized in the past as an affinity reagent for the identification of mono- and di-methylated lysine residues on individual proteins and on a proteomic scale. Here, we have utilized the 3XMBT domain to develop an enzyme-linked immunosorbent assay (ELISA) that allows the high-throughput detection of 3XMBT binding to methylated lysines. We demonstrated that this system allows the detection of methylated peptides, methylated proteins and PKMT activity on both peptides and proteins. We also optimized the assay to detect 3XMBT binding in crude E. coli lysates which facilitated the high throughput screening of 3XMBT mutant libraries. We have utilized protein engineering tools and generated a double site saturation 3XMBT library of residues 361 and 411 that were shown before to be important for binding mono and di-methylated substrates and identified variants that can exclusively recognize only di-methylated peptides. Together, our results demonstrate a powerful new approach that will contribute to deeper understanding of lysine methylation biology and that can be utilized for the engineering of domains for specific binders of other post-translational modifications.

Spatiotemporal variation of mammalian protein complex stoichiometries

Background

Recent large-scale studies revealed cell-type specific proteomes. However, protein complexes, the basic functional modules of a cell, have been so far mostly considered as static entities with well-defined structures. The co-expression of their members has not been systematically charted at the protein level.

Results

We used measurements of protein abundance across 11 cell types and five temporal states to analyze the co-expression and the compositional variations of 182 well-characterized protein complexes. We show that although the abundance of protein complex members is generally co-regulated, a considerable fraction of all investigated protein complexes is subject to stoichiometric changes. Compositional variation is most frequently seen in complexes involved in chromatin regulation and cellular transport, and often involves paralog switching as a mechanism for the regulation of complex stoichiometry. We demonstrate that compositional signatures of variable protein complexes have discriminative power beyond individual cell states and can distinguish cancer cells from healthy ones.

Conclusions

Our work demonstrates that many protein complexes contain variable members that cause distinct stoichometries and functionally fine-tune complexes spatiotemporally. Only a fraction of these compositional variations is mediated by changes in transcription and other mechanisms regulating protein abundance contribute to determine protein complex stoichiometries. Our work highlights the superior power of proteome profiles to study protein complexes and their variants across cell states.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-0912-5) contains supplementary material, which is available to authorized users.

In silico prediction and characterization of protein post-translational modifications

This review outlines the computational approaches and procedures for predicting post translational modification (PTM)-induced changes in protein conformation and their influence on protein function(s), the latter being assessed as differential affinity in interaction with either low (ligands for receptors or transporters, substrates for enzymes) or high molecular mass molecules (proteins or nucleic acids in supramolecular assemblies). The scope for an in silico approach is discussed against a summary of the in vitro evidence on the structural and functional outcome of protein PTM.

In situ structural analysis of the human nuclear pore complex

Nuclear pore complexes are fundamental components of all eukaryotic cells that mediate nucleocytoplasmic exchange. Determining their 110-megadalton structure imposes a formidable challenge and requires in situ structural biology approaches. Of approximately 30 nucleoporins (Nups), 15 are structured and form the Y and inner-ring complexes. These two major scaffolding modules assemble in multiple copies into an eight-fold rotationally symmetric structure that fuses the inner and outer nuclear membranes to form a central channel of ~60 nm in diameter. The scaffold is decorated with transport-channel Nups that often contain phenylalanine-repeat sequences and mediate the interaction with cargo complexes. Although the architectural arrangement of parts of the Y complex has been elucidated, it is unclear how exactly it oligomerizes in situ. Here we combine cryo-electron tomography with mass spectrometry, biochemical analysis, perturbation experiments and structural modelling to generate, to our knowledge, the most comprehensive architectural model of the human nuclear pore complex to date. Our data suggest previously unknown protein interfaces across Y complexes and to inner-ring complex members. We show that the transport-channel Nup358 (also known as Ranbp2) has a previously unanticipated role in Y-complex oligomerization. Our findings blur the established boundaries between scaffold and transport-channel Nups. We conclude that, similar to coated vesicles, several copies of the same structural building block--although compositionally identical--engage in different local sets of interactions and conformations.

Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes

Cancer is often driven by the accumulation of genetic alterations, including single nucleotide variants, small insertions or deletions, gene fusions, copy-number variations, and large chromosomal rearrangements. Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data and catalog somatic mutations in both common and rare cancer types. So far, the somatic mutation landscapes and signatures of >10 major cancer types have been reported; however, pinpointing driver mutations and cancer genes from millions of available cancer somatic mutations remains a monumental challenge. To tackle this important task, many methods and computational tools have been developed during the past several years and, thus, a review of its advances is urgently needed. Here, we first summarize the main features of these methods and tools for whole-exome, whole-genome and whole-transcriptome sequencing data. Then, we discuss major challenges like tumor intra-heterogeneity, tumor sample saturation and functionality of synonymous mutations in cancer, all of which may result in false-positive discoveries. Finally, we highlight new directions in studying regulatory roles of noncoding somatic mutations and quantitatively measuring circulating tumor DNA in cancer. This review may help investigators find an appropriate tool for detecting potential driver or actionable mutations in rapidly emerging precision cancer medicine.

Computational and statistical methods for high-throughput analysis of post-translational modifications of proteins

The investigation of post-translational modifications (PTMs) represents one of the main research focuses for the study of protein function and cell signaling. Mass spectrometry instrumentation with increasing sensitivity improved protocols for PTM enrichment and recently established pipelines for high-throughput experiments allow large-scale identification and quantification of several PTM types. This review addresses the concurrently emerging challenges for the computational analysis of the resulting data and presents PTM-centered approaches for spectra identification, statistical analysis, multivariate analysis and data interpretation. We furthermore discuss the potential of future developments that will help to gain deep insight into the PTM-ome and its biological role in cells. This article is part of a Special Issue entitled: Computational Proteomics.

The 2015 Nucleic Acids Research Database Issue and molecular biology database collection

The 2015 Nucleic Acids Research Database Issue contains 172 papers that include descriptions of 56 new molecular biology databases, and updates on 115 databases whose descriptions have been previously published in NAR or other journals. Following the classification that has been introduced last year in order to simplify navigation of the entire issue, these articles are divided into eight subject categories. This year's highlights include RNAcentral, an international community portal to various databases on noncoding RNA; ValidatorDB, a validation database for protein structures and their ligands; SASBDB, a primary repository for small-angle scattering data of various macromolecular complexes; MoonProt, a database of 'moonlighting' proteins, and two new databases of protein-protein and other macromolecular complexes, ComPPI and the Complex Portal. This issue also includes an unusually high number of cancer-related databases and other databases dedicated to genomic basics of disease and potential drugs and drug targets. The size of NAR online Molecular Biology Database Collection, http://www.oxfordjournals.org/nar/database/a/, remained approximately the same, following the addition of 74 new resources and removal of 77 obsolete web sites. The entire Database Issue is freely available online on the Nucleic Acids Research web site (http://nar.oxfordjournals.org/).

PEIMAN 1.0: Post-translational modification Enrichment, Integration and Matching ANalysis

Conventional proteomics has discovered a wide gap between protein sequences and biological functions. The third generation of proteomics was provoked to bridge this gap. Targeted and untargeted post-translational modification (PTM) studies are the most important parts of today’s proteomics. Considering the expensive and time-consuming nature of experimental methods, computational methods are developed to study, analyze, predict, count and compute the PTM annotations on proteins. The enrichment analysis softwares are among the common computational biology and bioinformatic software packages. The focus of such softwares is to find the probability of occurrence of the desired biological features in any arbitrary list of genes/proteins. We introduce Post-translational modification Enrichment Integration and Matching Analysis (PEIMAN) software to explore more probable and enriched PTMs on proteins. Here, we also represent the statistics of detected PTM terms used in enrichment analysis in PEIMAN software based on the latest released version of UniProtKB/Swiss-Prot. These results, in addition to giving insight to any given list of proteins, could be useful to design targeted PTM studies for identification and characterization of special chemical groups.

Database URL:http://bs.ipm.ir/softwares/PEIMAN/

Systematic characterization and prediction of post-translational modification cross-talk

Post-translational modification (PTM)(1) plays an important role in regulating the functions of proteins. PTMs of multiple residues on one protein may work together to determine a functional outcome, which is known as PTM cross-talk. Identification of PTM cross-talks is an emerging theme in proteomics and has elicited great interest, but their properties remain to be systematically characterized. To this end, we collected 193 PTM cross-talk pairs in 77 human proteins from the literature and then tested location preference and co-evolution at the residue and modification levels. We found that cross-talk events preferentially occurred among nearby PTM sites, especially in disordered protein regions, and cross-talk pairs tended to co-evolve. Given the properties of PTM cross-talk pairs, a naïve Bayes classifier integrating different features was built to predict cross-talks for pairwise combination of PTM sites. By using a 10-fold cross-validation, the integrated prediction model showed an area under the receiver operating characteristic (ROC) curve of 0.833, superior to using any individual feature alone. The prediction performance was also demonstrated to be robust to the biases in the collected PTM cross-talk pairs. The integrated approach has the potential for large-scale prioritization of PTM cross-talk candidates for functional validation and was implemented as a web server available at http://bioinfo.bjmu.edu.cn/ptm-x/.