Human proteins with target sites of multiple post-translational modification types are more prone to be involved in disease

MSModDetector: a tool for detecting mass shifts and post-translational modifications in individual ion mass spectrometry data

MOTIVATION

Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs on the same protein molecule, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even PTMs at distant sites to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein.

RESULTS

We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I2MS) data. I2MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I2MS data and experimental I2MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein's PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes.

AVAILABILITY AND IMPLEMENTATION

The source code is available at https://github.com/marjanfaizi/MSModDetector.

CarSitePred: an integrated algorithm for identifying carbonylated sites based on KNDUA-LNDOT resampling technique

Carbonylated sites are the determining factors for functional changes or deletions in carbonylated proteins, so identifying carbonylated sites is essential for understanding the process of protein carbonylated and exploring the pathogenesis of related diseases. The current wet experimental methods for predicting carbonylated modification sites ae not only expensive and time-consuming, but also have limited protein processing capabilities and cannot meet the needs of researchers. The identification of carbonylated sites using computational methods not only improves the functional characterization of proteins, but also provides researchers with free tools for predicting carbonylated sites. Therefore, it is essential to establish a model using computational methods that can accurately predict protein carbonylated sites. In this study, a prediction model, CarSitePred, is proposed to identify carbonylation sites. In CarSitePred, specific location amino acid hydrophobic hydrophilic, one-to-one numerical conversion of amino acids, and AlexNet convolutional neural networks convert preprocessed carbonylated sequences into valid numerical features. The K-means Normal Distribution-based Undersampling Algorithm (KNDUA) and Localized Normal Distribution Oversampling Technology (LNDOT) were firstly proposed and employed to balance the K, P, R and T carbonylation training dataset. And for the first time, carbonylation modification sites were transformed into the form of images and directly inputted into AlexNet convolutional neural network to extract features for fitting SVM classifiers. The 10-fold cross-validation and independent testing results show that CarSitePred achieves better prediction performance than the best currently available prediction models. Availability: https://github.com/zuoyun123/CarSitePred.Communicated by Ramaswamy H. Sarma.

L-ergothioneine reduces nitration of lactoferrin and loss of antibacterial activity associated with nitrosative stress

Lactoferrin (LF) is a multifunctional antimicrobial, anti-inflammatory, and antioxidant protein that occurs naturally in mammals, most notably in exocrine gland tissues and fluids, such as in the eye. Nitrosative stress can promote changes to tyrosine and other amino acid residues of the protein, which also reduces the activity of LF. l-ergothioneine (ET) is a potent anti-inflammatory antioxidant present in the eye and other tissues through nutrition or supplementation and that may play a role in the prevention or treatment of a variety of diseases. Here we investigated the ability of ET to reduce 3-nitrotyrosine (NTyr) formation using two separate substrates, with the goal of determining whether ET can protect the antibacterial function of LF and other proteins when exposed separately to peroxynitrite and tetranitromethane as nitrating reagents. Native human LF was used as a simple protein substrate, and lamb corneal lysate was chosen as one example of mammalian tissue with a more complex mixture of proteins and other biomolecules. Nitration was monitored by absorbance and fluorescence spectroscopy as well as sandwich (nitrated LF) and direct NTyr (corneal lysate) enzyme-linked immunosorbent assays (ELISAs). We found that pretreatment with ET reduced chemical modification of both native LF and corneal lysate samples and loss of antibacterial LF function due to exposure to the nitrating reagents. These initial results suggest that ET, raised to sufficiently elevated levels, could be tailored as a therapeutic agent to reduce effects of nitrosative stress on LF and in turn sustain the protein activity.

MSModDetector: A Tool for Detecting Mass Shifts and Post-Translational Modifications in Individual Ion Mass Spectrometry Data

Motivation

Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even widely separated PTMs to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein.

Results

We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I MS) data. I MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I MS data and experimental I MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein's PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes.

Availability

The source code is available at https://github.com/marjanfaizi/MSModDetector together with the scripts used for analyses and to generate the figures presented in this study.

Characterizing the top-down sequencing of protein ions prior to mobility separation in a timsTOF

Mass spectrometry (MS)-based proteomics workflows of intact protein ions have increasingly been utilized to study biological systems. These workflows, however, frequently result in convoluted and difficult to analyze mass spectra. Ion mobility spectrometry (IMS) is a promising tool to overcome these limitations by separating ions by their mass- and size-to-charge ratios. In this work, we further characterize a newly developed method to collisionally dissociate intact protein ions in a trapped ion mobility spectrometry (TIMS) device. Dissociation occurs prior to ion mobility separation and thus, all product ions are distributed throughout the mobility dimension, enabling facile assignment of near isobaric product ions. We demonstrate that collisional activation within a TIMS device is capable of dissociating protein ions up to 66 kDa. We also demonstrate that the ion population size within the TIMS device significantly influences the efficiency of fragmentation. Lastly, we compare CIDtims to the other modes of collisional activation available on the Bruker timsTOF and demonstrate that the mobility resolution in CIDtims enables the annotation of overlapping fragment ions and improves sequence coverage.

An atlas of posttranslational modifications on RNA binding proteins

RNA structure and function are intimately tied to RNA binding protein recognition and regulation. Posttranslational modifications are chemical modifications which can control protein biology. The role of PTMs in the regulation RBPs is not well understood, in part due to a lacking analysis of PTM deposition on RBPs. Herein, we present an analysis of posttranslational modifications (PTMs) on RNA binding proteins (RBPs; a PTM RBP Atlas). We curate published datasets and primary literature to understand the landscape of PTMs and use protein-protein interaction data to understand and potentially provide a framework for understanding which enzymes are controlling PTM deposition and removal on the RBP landscape. Intersection of our data with The Cancer Genome Atlas also provides researchers understanding of mutations that would alter PTM deposition. Additional characterization of the RNA-protein interface provided from in-cell UV crosslinking experiments provides a framework for hypotheses about which PTMs could be regulating RNA binding and thus RBP function. Finally, we provide an online database for our data that is easy to use for the community. It is our hope our efforts will provide researchers will an invaluable tool to test the function of PTMs controlling RBP function and thus RNA biology.

Current status of PTMs structural databases: applications, limitations and prospects

Protein 3D structures, determined by their amino acid sequences, are the support of major crucial biological functions. Post-translational modifications (PTMs) play an essential role in regulating these functions by altering the physicochemical properties of proteins. By virtue of their importance, several PTM databases have been developed and released in decades, but very few of these databases incorporate real 3D structural data. Since PTMs influence the function of the protein and their aberrant states are frequently implicated in human diseases, providing structural insights to understand the influence and dynamics of PTMs is crucial for unraveling the underlying processes. This review is dedicated to the current status of databases providing 3D structural data on PTM sites in proteins. Some of these databases are general, covering multiple types of PTMs in different organisms, while others are specific to one particular type of PTM, class of proteins or organism. The importance of these databases is illustrated with two major types of in silico applications: predicting PTM sites in proteins using machine learning approaches and investigating protein structure-function relationships involving PTMs. Finally, these databases suffer from multiple problems and care must be taken when analyzing the PTMs data.

The Participation of the Intrinsically Disordered Regions of the bHLH-PAS Transcription Factors in Disease Development

The basic helix–loop–helix/Per-ARNT-SIM (bHLH-PAS) proteins are a family of transcription factors regulating expression of a wide range of genes involved in different functions, ranging from differentiation and development control by oxygen and toxins sensing to circadian clock setting. In addition to the well-preserved DNA-binding bHLH and PAS domains, bHLH-PAS proteins contain long intrinsically disordered C-terminal regions, responsible for regulation of their activity. Our aim was to analyze the potential connection between disordered regions of the bHLH-PAS transcription factors, post-transcriptional modifications and liquid-liquid phase separation, in the context of disease-associated missense mutations. Highly flexible disordered regions, enriched in short motives which are more ordered, are responsible for a wide spectrum of interactions with transcriptional co-regulators. Based on our in silico analysis and taking into account the fact that the functions of transcription factors can be modulated by posttranslational modifications and spontaneous phase separation, we assume that the locations of missense mutations inducing disease states are clearly related to sequences directly undergoing these processes or to sequences responsible for their regulation.

Chemical Decorations of "MARs" Residents in Orchestrating Eukaryotic Gene Regulation

Genome organization plays a crucial role in gene regulation, orchestrating multiple cellular functions. A meshwork of proteins constituting a three-dimensional (3D) matrix helps in maintaining the genomic architecture. Sequences of DNA that are involved in tethering the chromatin to the matrix are called scaffold/matrix attachment regions (S/MARs), and the proteins that bind to these sequences and mediate tethering are termed S/MAR-binding proteins (S/MARBPs). The regulation of S/MARBPs is important for cellular functions and is altered under different conditions. Limited information is available presently to understand the structure–function relationship conclusively. Although all S/MARBPs bind to DNA, their context- and tissue-specific regulatory roles cannot be justified solely based on the available information on their structures. Conformational changes in a protein lead to changes in protein–protein interactions (PPIs) that essentially would regulate functional outcomes. A well-studied form of protein regulation is post-translational modification (PTM). It involves disulfide bond formation, cleavage of precursor proteins, and addition or removal of low-molecular-weight groups, leading to modifications like phosphorylation, methylation, SUMOylation, acetylation, PARylation, and ubiquitination. These chemical modifications lead to varied functional outcomes by mechanisms like modifying DNA–protein interactions and PPIs, altering protein function, stability, and crosstalk with other PTMs regulating subcellular localizations. S/MARBPs are reported to be regulated by PTMs, thereby contributing to gene regulation. In this review, we discuss the current understanding, scope, disease implications, and future perspectives of the diverse PTMs regulating functions of S/MARBPs.

Biotin proximity tagging favours unfolded proteins and enables the study of intrinsically disordered regions

Intrinsically Disordered Regions (IDRs) are enriched in disease-linked proteins known to have multiple post-translational modifications, but there is limited in vivo information about how locally unfolded protein regions contribute to biological functions. We reasoned that IDRs should be more accessible to targeted in vivo biotinylation than ordered protein regions, if they retain their flexibility in human cells. Indeed, we observed increased biotinylation density in predicted IDRs in several cellular compartments >20,000 biotin sites from four proximity proteomics studies. We show that in a biotin ‘painting’ time course experiment, biotinylation events in Escherichia coli ribosomes progress from unfolded and exposed regions at 10 s, to structured and less accessible regions after five minutes. We conclude that biotin proximity tagging favours sites of local disorder in proteins and suggest the possibility of using biotin painting as a method to gain unique insights into in vivo condition-dependent subcellular plasticity of proteins.

David-Paul Minde, Manasa Ramakrishna et al. look at intrinsically disordered regions of disease-linked proteins in vivo by biotinylation. They show that biotin “painting” could be used as a method to examine the condition-dependent plasticity of proteins in vivo.

Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases

Diagnosis of neurodegenerative diseases hinges on “seed” proteins detected in disease-specific aggregates. These inclusions contain diverse constituents, adhering through aberrant interactions that our prior data indicate are nonrandom. To define preferential protein-protein contacts mediating aggregate coalescence, we created click-chemistry reagents that cross-link neighboring proteins within human, APP_Sw-driven, neuroblastoma-cell aggregates. These reagents incorporate a biotinyl group to efficiently recover linked tryptic-peptide pairs. Mass-spectroscopy outputs were screened for all possible peptide pairs in the aggregate proteome. These empirical linkages, ranked by abundance, implicate a protein-adherence network termed the “aggregate contactome.” Critical hubs and hub-hub interactions were assessed by RNAi-mediated rescue of chemotaxis in aging nematodes, and aggregation-driving properties were inferred by multivariate regression and neural-network approaches. Aspirin, while disrupting aggregation, greatly simplified the aggregate contactome. This approach, and the dynamic model of aggregate accrual it implies, reveals the architecture of insoluble-aggregate networks and may reveal targets susceptible to interventions to ameliorate protein-aggregation diseases.

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Cross-link data support a preferred hierarchy of protein accrual into aggregates

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Contact networks can predict proteins that contribute functionally to aggregation

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RNAi knockdowns of key hubs and hub connectors imply functional roles in accrual

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Aspirin opposes protein aggregation by reducing contactome interactions >5-fold

Illuminating the dark phosphoproteome

Protein phosphorylation is a major regulator of protein function and biological outcomes. This was first recognized through functional biochemical experiments, and in the past decade, major technological advances in mass spectrometry have enabled the study of protein phosphorylation on a global scale. This rapidly growing field of phosphoproteomics has revealed that more than 100,000 distinct phosphorylation events occur in human cells, which likely affect the function of every protein. Phosphoproteomics has improved the understanding of the function of even the most well-characterized protein kinases by revealing new downstream substrates and biology. However, current biochemical and bioinformatic approaches have only identified kinases for less than 5% of the phosphoproteome, and functional assignments of phosphosites are almost negligible. Notably, our understanding of the relationship between kinases and their substrates follows a power law distribution, with almost 90% of phosphorylation sites currently assigned to the top 20% of kinases. In addition, more than 150 kinases do not have a single known substrate. Despite a small group of kinases dominating biomedical research, the number of substrates assigned to a kinase does not correlate with disease relevance as determined by pathogenic human mutation prevalence and mouse model phenotypes. Improving our understanding of the substrates targeted by all kinases and functionally annotating the phosphoproteome will be broadly beneficial. Advances in phosphoproteomics technologies, combined with functional screening approaches, should make it feasible to illuminate the connectivity and functionality of the entire phosphoproteome, providing enormous opportunities for discovering new biology, therapeutic targets, and possibly diagnostics.

Optimised methods (SDS/PAGE and LC-MS) reveal deamidation in all examined transglutaminase-mediated reactions

Transglutaminases (TGs) are a family of structurally and functionally related enzymes that catalyse calcium‐dependent post‐translational modifications of proteins through protein–protein crosslinking, amine incorporation, or deamidation. For many years deamidation mediated by TGs was considered to be a side reaction, but recently substrate‐specific deamidations have been reported. Here we describe an optimised SDS/PAGE assay for the easy and rapid monitoring of the TG reaction with small peptides. The relative proportion of deamidation to transamidation was evaluated by densitometric analysis and confirmed by nano‐liquid chromatography–nano‐electrospray ionisation MS. We further investigated the effect of reaction conditions on transamidation and deamidation of TG1, TG2 and blood coagulation factor XIII A‐subunit (FXIII‐A) enzymes using a panel of glutamine‐containing peptide substrates. The ratio of transamidation to deamidation was enhanced at high excess of the acyl‐acceptor substrate and increasing pH. In addition, it was influenced by peptide substrates as well. Whereas deamidation was favoured at low cadaverine concentrations and acidic pH, no significant effect of calcium was observed on the ratio of transamidation/deamidation. Under our experimental conditions, deamidation always occurred in vitro even at high excess of the acyl‐acceptor substrate, and the reaction outcome was shifted to deamidation at neutral pH. Our results provide clear evidence of the deamidation in the TG reaction, and may serve as an important approach for in vivo analysis of deamidation to better understand the role of TGs in biological events.

Visualizing Post-Translational Modifications in Protein Interaction Networks Using PTMOracle

Post-translational modifications (PTMs) of proteins act as key regulators of protein activity, including the regulation of protein-protein interactions (PPIs). However, exploring functional links between PTMs and PPIs can be difficult. PTMOracle is a Cytoscape app that facilitates the co-visualization and co-analysis of PTMs in the context of PPI networks. PTMOracle also allows extensive data to be integrated and co-analyzed, allowing the role of domains, motifs, and disordered regions to be considered. Here, we describe several PTMOracle protocols investigating complex PTM-associated relationships and their role in PPIs. This is assisted by OraclePainter for coloring proteins by the modifications present and visualizing these in the context of networks, by OracleTools for cross-matching PTMs with sequence feature for all nodes in the network, and by OracleResults for exploring specific proteins and visualizing their PTMs in the context of protein sequences. This unit aims to demonstrate how PTMOracle can be used to systematically explore network visualizations and generate testable hypotheses regarding the functional role of PTMs in PPIs, and how the results can be analyzed to better understand the regulatory role of PTMs in PPIs. © 2019 by John Wiley & Sons, Inc.

Structural insights into pro-aggregation effects of C. elegans CRAM-1 and its human ortholog SERF2

Toxic protein aggregates are key features of progressive neurodegenerative diseases. In addition to “seed” proteins diagnostic for each neuropathy (e.g., Aβ_1–42 and tau in Alzheimer’s disease), aggregates contain numerous other proteins, many of which are common to aggregates from diverse diseases. We reported that CRAM-1, discovered in insoluble aggregates of C. elegans expressing Q40::YFP, blocks proteasomal degradation of ubiquitinated proteins and thus promotes aggregation. We now show that CRAM-1 contains three α-helical segments forming a UBA-like domain, structurally similar to those of mammalian adaptor proteins (e.g. RAD23, SQSTM1/p62) that shuttle ubiquitinated cargos to proteasomes or autophagosomes for degradation. Molecular modeling indicates that CRAM-1, through this UBA-like domain, can form tight complexes with mono- and di-ubiquitin and may thus prevent tagged proteins from interacting with adaptor/shuttle proteins required for degradation. A human ortholog of CRAM-1, SERF2 (also largely disordered), promotes aggregation in SH-SY5Y-APP_Sw human neuroblastoma cells, since SERF2 knockdown protects these cells from amyloid formation. Atomistic molecular-dynamic simulations predict spontaneous unfolding of SERF2, and computational large-scale protein-protein interactions predict its stable binding to ubiquitins. SERF2 is also predicted to bind to most proteins screened at random, although with lower average stability than to ubiquitins, suggesting roles in aggregation initiation and/or progression.

Intrinsic Disorder and Posttranslational Modifications: The Darker Side of the Biological Dark Matter

Intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) are functional proteins and domains that devoid stable secondary and/or tertiary structure. IDPs/IDPRs are abundantly present in various proteomes, where they are involved in regulation, signaling, and control, thereby serving as crucial regulators of various cellular processes. Various mechanisms are utilized to tightly regulate and modulate biological functions, structural properties, cellular levels, and localization of these important controllers. Among these regulatory mechanisms are precisely controlled degradation and different posttranslational modifications (PTMs). Many normal cellular processes are associated with the presence of the right amounts of precisely activated IDPs at right places and in right time. However, wrecked regulation of IDPs/IDPRs might be associated with various human maladies, ranging from cancer and neurodegeneration to cardiovascular disease and diabetes. Pathogenic transformations of IDPs/IDPRs are often triggered by altered PTMs. This review considers some of the aspects of IDPs/IDPRs and their normal and aberrant regulation by PTMs.

Structural changes of homodimers in the PDB

Protein complexes are involved in various biological phenomena. These complexes are intrinsically flexible, and structural changes are essential to their functions. To perform a large-scale automated analysis of the structural changes of complexes, we combined two original methods. An application, SCPC, compares two structures of protein complexes and decides the match of binding mode. Another application, Motion Tree, identifies rigid-body motions in various sizes and magnitude from the two structural complexes with the same binding mode. This approach was applied to all available homodimers in the Protein Data Bank (PDB). We defined two complex-specific motions: interface motion and subunit-spanning motion. In the former, each subunit of a complex constitutes a rigid body, and the relative movement between subunits occurs at the interface. In the latter, structural parts from distinct subunits constitute a rigid body, providing the relative movement spanning subunits. All structural changes were classified and examined. It was revealed that the complex-specific motions were common in the homodimers, detected in around 40% of families. The dimeric interfaces were likely to be small and flat for interface motion, while large and rugged for subunit-spanning motion. Interface motion was accompanied by a drastic change in contacts at the interface, while the change in the subunit-spanning motion was moderate. These results indicate that the interface properties of homodimers correlated with the type of complex-specific motion. The study demonstrates that the pipeline of SCPC and Motion Tree is useful for the massive analysis of structural change of protein complexes.

Sequence and Solution Effects on the Prevalence of d-Isomers Produced by Deamidation

Deamidation of asparagine is a spontaneous and irreversible post-translational modification associated with a growing list of human diseases. While pervasive, deamidation is often overlooked because it represents a relatively minor chemical change. Structural and functional characterization of this modification is complicated because deamidation of asparagine yields four isomeric forms of Asp. Herein, radical directed dissociation (RDD), in conjunction with mass spectrometry, is used to identify and quantify all four isomers in a series of model peptides that were subjected to various deamidation conditions. Although primary sequence significantly influences the rate of deamidation, it has little impact on the relative proportions of the product isomers. Furthermore, the addition of ammonia can be used to increase the rate of deamidation without significantly perturbing isomer populations. Conversely, external factors such as buffer conditions and temperature alter product distributions but exhibit less dramatic effects on the deamidation rate. Strikingly, the common laboratory and biologically significant bicarbonate buffer is found to strongly promote racemization, yielding increased amounts of d-Asp and d-isoAsp. These outcomes following deamidation have broad implications in human aging and should be considered during the development of protein-based therapeutics.

Posttranslational Modification as a Critical Determinant of Cytoplasmic Innate Immune Recognition

Cell surface innate immune receptors can directly detect a variety of extracellular pathogens to which cytoplasmic innate immune sensors are rarely exposed. Instead, within the cytoplasm, the environment is rife with cellular machinery and signaling pathways that are indirectly perturbed by pathogenic microbes to activate intracellular sensors, such as pyrin, NLRP1, NLRP3, or NLRC4. Therefore, subtle changes in key intracellular processes such as phosphorylation, ubiquitination, and other pathways leading to posttranslational protein modification are key determinants of innate immune recognition in the cytoplasm. This concept is critical to establish the “guard hypothesis” whereby otherwise homeostatic pathways that keep innate immune sensors at bay are released in response to alterations in their posttranslational modification status. Originally identified in plants, evidence that a similar guardlike mechanism exists in humans has recently been identified, whereby a mutation that prevents phosphorylation of the innate immune sensor pyrin triggers a dominantly inherited autoinflammatory disease. It is also noteworthy that even when a cytoplasmic innate immune sensor has a direct ligand, such as bacterial peptidoglycan (NOD1 or NOD2), RNA (RIG-I or MDA5), or DNA (cGAS or IFI16), it can still be influenced by posttranslational modification to dramatically alter its response. Therefore, due to their existence in the cytoplasmic milieu, posttranslational modification is a key determinant of intracellular innate immune receptor functionality.

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 .

Quarterly intrinsic disorder digest (April-May-June, 2014)

This is the 6^th issue of the Digested Disorder series that continues to use only 2 criteria for inclusion of a paper to this digest: The publication date (a paper should be published within the covered time frame) and the topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest issue covers papers published during the second quarter of 2014; i.e., during the period of April, May, and June of 2014. Similar to previous issues, the papers are grouped hierarchically by topics they cover, and for each of the included papers a short description is given on its major findings.

Multiple-Localization and Hub Proteins

Protein-protein interactions are fundamental for all biological phenomena, and protein-protein interaction networks provide a global view of the interactions. The hub proteins, with many interaction partners, play vital roles in the networks. We investigated the subcellular localizations of proteins in the human network, and found that the ones localized in multiple subcellular compartments, especially the nucleus/cytoplasm proteins (NCP), the cytoplasm/cell membrane proteins (CMP), and the nucleus/cytoplasm/cell membrane proteins (NCMP), tend to be hubs. Examinations of keywords suggested that among NCP, those related to post-translational modifications and transcription functions are the major contributors to the large number of interactions. These types of proteins are characterized by a multi-domain architecture and intrinsic disorder. A survey of the typical hub proteins with prominent numbers of interaction partners in the type revealed that most are either transcription factors or co-regulators involved in signaling pathways. They translocate from the cytoplasm to the nucleus, triggered by the phosphorylation and/or ubiquitination of intrinsically disordered regions. Among CMP and NCMP, the contributors to the numerous interactions are related to either kinase or ubiquitin ligase activity. Many of them reside on the cytoplasmic side of the cell membrane, and act as the upstream regulators of signaling pathways. Overall, these hub proteins function to transfer external signals to the nucleus, through the cell membrane and the cytoplasm. Our analysis suggests that multiple-localization is a crucial concept to characterize groups of hub proteins and their biological functions in cellular information processing.

Identifying Similar Patterns of Structural Flexibility in Proteins by Disorder Prediction and Dynamic Programming

Computational methods are prevailing in identifying protein intrinsic disorder. The results from predictors are often given as per-residue disorder scores. The scores describe the disorder propensity of amino acids of a protein and can be further represented as a disorder curve. Many proteins share similar patterns in their disorder curves. The similar patterns are often associated with similar functions and evolutionary origins. Therefore, finding and characterizing specific patterns of disorder curves provides a unique and attractive perspective of studying the function of intrinsically disordered proteins. In this study, we developed a new computational tool named IDalign using dynamic programming. This tool is able to identify similar patterns among disorder curves, as well as to present the distribution of intrinsic disorder in query proteins. The disorder-based information generated by IDalign is significantly different from the information retrieved from classical sequence alignments. This tool can also be used to infer functions of disordered regions and disordered proteins. The web server of IDalign is available at (http://labs.cas.usf.edu/bioinfo/service.html).

An artificial receptor synthesized by surface-confined imprinting for the recognition of acetylation on histone H4 K16

Molecularly imprinted artificial receptor with high selectivity for the recognition of acetylation on histone H4 K16.

The structural and functional signatures of proteins that undergo multiple events of post-translational modification

The structural, functional, and mechanistic characterization of several types of post-translational modifications (PTMs) is well-documented. PTMs, however, may interact or interfere with one another when regulating protein function. Yet, characterization of the structural and functional signatures of their crosstalk has been hindered by the scarcity of data. To this end, we developed a unified sequence-based predictor of 23 types of PTM sites that, we believe, is a useful tool in guiding biological experiments and data interpretation. We then used experimentally determined and predicted PTM sites to investigate two particular cases of potential PTM crosstalk in eukaryotes. First, we identified proteins statistically enriched in multiple types of PTM sites and found that they show preferences toward intrinsically disordered regions as well as functional roles in transcriptional, posttranscriptional, and developmental processes. Second, we observed that target sites modified by more than one type of PTM, referred to as shared PTM sites, show even stronger preferences toward disordered regions than their single-PTM counterparts; we explain this by the need for these regions to accommodate multiple partners. Finally, we investigated the influence of single and shared PTMs on differential regulation of protein-protein interactions. We provide evidence that molecular recognition features (MoRFs) show significant preferences for PTM sites, particularly shared PTM sites, implicating PTMs in the modulation of this specific type of macromolecular recognition. We conclude that intrinsic disorder is a strong structural prerequisite for complex PTM-based regulation, particularly in context-dependent protein-protein interactions related to transcriptional and developmental processes.

AVAILABILITY

www.modpred.org.