Intrinsically Disordered Proteins Link Alternative Splicing and Post-translational Modifications to Complex Cell Signaling and Regulation

A systematic analysis of the effects of splicing on the diversity of post-translational modifications in protein isoforms

Post-translational modifications (PTMs) and splicing are known to be important regulatory processes for controlling protein function and activity. However, there have been limitations in analyzing the interplay of alternative splicing and PTMs, which stems from the deep differences in genomic and proteomic databases. In this work, we bridged the protein- and genome-centric world views to map PTMs to genomic locations for subsequent projection of PTMs onto alternative isoforms. We then performed a systematic analysis of the diversification of PTMs by alternative splicing, including exploration of the modification-specific rates of inclusion across isoforms and how often the regulatory sequences directly flanking a PTM are impacted by splicing, which might indicate altered regulatory or binding interactions in the alternatively spliced isoform. We found that 6-51% of PTMs are excluded from at least one isoform, depending on the modification type. Further, approximately 2% of prospective PTM sites exhibited altered regulatory sequences surrounding the modification site, suggesting that regulatory or binding interactions might be diversified in these proteoforms. Lastly, we applied this PTM-to-isoform mapping approach to explore the impacts of disease-related splicing in prostate cancer, identifying possible new hypotheses explaining the variable consequences of ESRP1 expression in different cancers. As a part of this work, we have provided an easily implementable tool for annotating splice events identified from RNA-sequencing with PTMs and their functional consequences, called PTM-POSE.

The molecular basis for cellular function of intrinsically disordered protein regions

Intrinsically disordered protein regions exist in a collection of dynamic interconverting conformations that lack a stable 3D structure. These regions are structurally heterogeneous, ubiquitous and found across all kingdoms of life. Despite the absence of a defined 3D structure, disordered regions are essential for cellular processes ranging from transcriptional control and cell signalling to subcellular organization. Through their conformational malleability and adaptability, disordered regions extend the repertoire of macromolecular interactions and are readily tunable by their structural and chemical context, making them ideal responders to regulatory cues. Recent work has led to major advances in understanding the link between protein sequence and conformational behaviour in disordered regions, yet the link between sequence and molecular function is less well defined. Here we consider the biochemical and biophysical foundations that underlie how and why disordered regions can engage in productive cellular functions, provide examples of emerging concepts and discuss how protein disorder contributes to intracellular information processing and regulation of cellular function.

DisoFLAG: accurate prediction of protein intrinsic disorder and its functions using graph-based interaction protein language model

Intrinsically disordered proteins and regions (IDPs/IDRs) are functionally important proteins and regions that exist as highly dynamic conformations under natural physiological conditions. IDPs/IDRs exhibit a broad range of molecular functions, and their functions involve binding interactions with partners and remaining native structural flexibility. The rapid increase in the number of proteins in sequence databases and the diversity of disordered functions challenge existing computational methods for predicting protein intrinsic disorder and disordered functions. A disordered region interacts with different partners to perform multiple functions, and these disordered functions exhibit different dependencies and correlations. In this study, we introduce DisoFLAG, a computational method that leverages a graph-based interaction protein language model (GiPLM) for jointly predicting disorder and its multiple potential functions. GiPLM integrates protein semantic information based on pre-trained protein language models into graph-based interaction units to enhance the correlation of the semantic representation of multiple disordered functions. The DisoFLAG predictor takes amino acid sequences as the only inputs and provides predictions of intrinsic disorder and six disordered functions for proteins, including protein-binding, DNA-binding, RNA-binding, ion-binding, lipid-binding, and flexible linker. We evaluated the predictive performance of DisoFLAG following the Critical Assessment of protein Intrinsic Disorder (CAID) experiments, and the results demonstrated that DisoFLAG offers accurate and comprehensive predictions of disordered functions, extending the current coverage of computationally predicted disordered function categories. The standalone package and web server of DisoFLAG have been established to provide accurate prediction tools for intrinsic disorders and their associated functions.

Phosphorylation motif dictates GPCR C-terminal domain conformation and arrestin interaction

Arrestin-dependent G protein-coupled receptor (GPCR) signaling pathway is regulated by the phosphorylation state of GPCR's C-terminal domain, but the molecular bases of arrestin:receptor interaction are to be further illuminated. Here we investigated the impact of phosphorylation on the conformational features of the C-terminal region from three rhodopsin-like GPCRs, the vasopressin V2 receptor (V2R), the growth hormone secretagogue or ghrelin receptor type 1a (GHSR), and the β2-adernergic receptor (β2AR). Using phosphomimetic variants, we identified pre-formed secondary structure elements, or short linear motifs (SLiMs), that undergo specific conformational transitions upon phosphorylation. Of importance, such conformational transitions appear to favor arrestin-2 binding. Hence, our results suggest a model in which the phosphorylation-dependent structuration of the GPCR C-terminal regions would modulate arrestin binding and therefore signaling outcomes in arrestin-dependent pathways.

Tutorial: a guide for the selection of fast and accurate computational tools for the prediction of intrinsic disorder in proteins

Intrinsic disorder is instrumental for a wide range of protein functions, and its analysis, using computational predictions from primary structures, complements secondary and tertiary structure-based approaches. In this Tutorial, we provide an overview and comparison of 23 publicly available computational tools with complementary parameters useful for intrinsic disorder prediction, partly relying on results from the Critical Assessment of protein Intrinsic Disorder prediction experiment. We consider factors such as accuracy, runtime, availability and the need for functional insights. The selected tools are available as web servers and downloadable programs, offer state-of-the-art predictions and can be used in a high-throughput manner. We provide examples and instructions for the selected tools to illustrate practical aspects related to the submission, collection and interpretation of predictions, as well as the timing and their limitations. We highlight two predictors for intrinsically disordered proteins, flDPnn as accurate and fast and IUPred as very fast and moderately accurate, while suggesting ANCHOR2 and MoRFchibi as two of the best-performing predictors for intrinsically disordered region binding. We link these tools to additional resources, including databases of predictions and web servers that integrate multiple predictive methods. Altogether, this Tutorial provides a hands-on guide to comparatively evaluating multiple predictors, submitting and collecting their own predictions, and reading and interpreting results. It is suitable for experimentalists and computational biologists interested in accurately and conveniently identifying intrinsic disorder, facilitating the functional characterization of the rapidly growing collections of protein sequences.

Unveiling the complexity: assessing models describing the structure and function of the nuclear pore complex

The nuclear pore complex (NPC) serves as a pivotal subcellular structure, acting as a gateway that orchestrates nucleocytoplasmic transport through a selectively permeable barrier. Nucleoporins (Nups), particularly those containing phenylalanine-glycine (FG) motifs, play indispensable roles within this barrier. Recent advancements in technology have significantly deepened our understanding of the NPC's architecture and operational intricacies, owing to comprehensive investigations. Nevertheless, the conspicuous presence of intrinsically disordered regions within FG-Nups continues to present a formidable challenge to conventional static characterization techniques. Historically, a multitude of strategies have been employed to unravel the intricate organization and behavior of FG-Nups within the NPC. These endeavors have given rise to multiple models that strive to elucidate the structural layout and functional significance of FG-Nups. Within this exhaustive review, we present a comprehensive overview of these prominent models, underscoring their proposed dynamic and structural attributes, supported by pertinent research. Through a comparative analysis, we endeavor to shed light on the distinct characteristics and contributions inherent in each model. Simultaneously, it remains crucial to acknowledge the scarcity of unequivocal validation for any of these models, as substantiated by empirical evidence.

Visualizing single-molecule conformational transition and binding dynamics of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) play crucial roles in cellular processes and hold promise as drug targets. However, the dynamic nature of IDPs remains poorly understood. Here, we construct a single-molecule electrical nanocircuit based on silicon nanowire field-effect transistors (SiNW-FETs) and functionalize it with an individual disordered c-Myc bHLH-LZ domain to enable label-free, in situ, and long-term measurements at the single-molecule level. We use the device to study c-Myc interaction with Max and/or small molecule inhibitors. We observe the self-folding/unfolding process of c-Myc and reveal its interaction mechanism with Max and inhibitors through ultrasensitive real-time monitoring. We capture a relatively stable encounter intermediate ensemble of c-Myc during its transition from the unbound state to the fully folded state. The c-Myc/Max and c-Myc/inhibitor dissociation constants derived are consistent with other ensemble experiments. These proof-of-concept results provide an understanding of the IDP-binding/folding mechanism and represent a promising nanotechnology for IDP conformation/interaction studies and drug discovery.

Modulation of Functional Phosphorylation Sites by Basic Residues in the Unique Domain of c-Src

In contrast to the well-studied canonical regulatory mechanisms, the way by which the recently discovered Src N-terminal regulatory element (SNRE) modulates Src activity is not yet well understood. Phosphorylation of serine and threonine residues modulates the charge distribution along the disordered region of the SNRE and may affect a fuzzy complex with the SH3 domain that is believed to act as an information transduction element. The pre-existing positively charged sites can interact with the newly introduced phosphate groups by modulating their acidity, introducing local conformational restrictions, or by coupling various phosphosites into a functional unit. In this paper, we use pH-dependent NMR measurements combined with single point mutations to identify the interactions of basic residues with physiologically important phosphorylated residues and to characterize the effect of these interactions in neighbor residues, thus providing insight into the electrostatic network in the isolated disordered regions and in the entire SNRE. From a methodological point of view, the linear relationships observed between the mutation-induced pKa changes of the phosphate groups of phosphoserine and phosphothreonine and the pH-induced chemical shifts of the NH groups of these residues provide a very convenient alternative to identify interacting phosphate groups without the need to introduce point mutations on specific basic residues.

Pre- and Post-Transcriptional Control of HBV Gene Expression: The Road Traveled towards the New Paradigm of HBx, Its Isoforms, and Their Diverse Functions

Hepatitis B virus (HBV) is an enveloped DNA human virus belonging to the Hepadnaviridae family. Perhaps its main distinguishable characteristic is the replication of its genome through a reverse transcription process. The HBV circular genome encodes only four overlapping reading frames, encoding for the main canonical proteins named core, P, surface, and X (or HBx protein). However, pre- and post-transcriptional gene regulation diversifies the full HBV proteome into diverse isoform proteins. In line with this, hepatitis B virus X protein (HBx) is a viral multifunctional and regulatory protein of 16.5 kDa, whose canonical reading frame presents two phylogenetically conserved internal in-frame translational initiation codons, and which results as well in the expression of two divergent N-terminal smaller isoforms of 8.6 and 5.8 kDa, during translation. The canonical HBx, as well as the smaller isoform proteins, displays different roles during viral replication and subcellular localizations. In this article, we reviewed the different mechanisms of pre- and post-transcriptional regulation of protein expression that take place during viral replication. We also investigated all the past and recent evidence about HBV HBx gene regulation and its divergent N-terminal isoform proteins. Evidence has been collected for over 30 years. The accumulated evidence simply strengthens the concept of a new paradigm of the canonical HBx, and its smaller divergent N-terminal isoform proteins, not only during viral replication, but also throughout cell pathogenesis.

Comparative evaluation of AlphaFold2 and disorder predictors for prediction of intrinsic disorder, disorder content and fully disordered proteins

We expand studies of AlphaFold2 (AF2) in the context of intrinsic disorder prediction by comparing it against a broad selection of 20 accurate, popular and recently released disorder predictors. We use 25% larger benchmark dataset with 646 proteins and cover protein-level predictions of disorder content and fully disordered proteins. AF2-based disorder predictions secure a relatively high Area Under receiver operating characteristic Curve (AUC) of 0.77 and are statistically outperformed by several modern disorder predictors that secure AUCs around 0.8 with median runtime of about 20 s compared to 1200 s for AF2. Moreover, AF2 provides modestly accurate predictions of fully disordered proteins (F1 = 0.59 vs. 0.91 for the best disorder predictor) and disorder content (mean absolute error of 0.21 vs. 0.15). AF2 also generates statistically more accurate disorder predictions for about 20% of proteins that have relatively short sequences and a few disordered regions that tend to be located at the sequence termini, and which are absent of disordered protein-binding regions. Interestingly, AF2 and the most accurate disorder predictors rely on deep neural networks, suggesting that these models are useful for protein structure and disorder predictions.

DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction

Intrinsic disorder in proteins is relatively abundant in nature and essential for a broad spectrum of cellular functions. While disorder can be accurately predicted from protein sequences, as it was empirically demonstrated in recent community-organized assessments, it is rather challenging to collect and compile a comprehensive prediction that covers multiple disorder functions. To this end, we introduce the DEPICTER2 (DisorderEd PredictIon CenTER) webserver that offers convenient access to a curated collection of fast and accurate disorder and disorder function predictors. This server includes a state-of-the-art disorder predictor, flDPnn, and five modern methods that cover all currently predictable disorder functions: disordered linkers and protein, peptide, DNA, RNA and lipid binding. DEPICTER2 allows selection of any combination of the six methods, batch predictions of up to 25 proteins per request and provides interactive visualization of the resulting predictions. The webserver is freely available at http://biomine.cs.vcu.edu/servers/DEPICTER2/.

Computational prediction of disordered binding regions

One of the key features of intrinsically disordered regions (IDRs) is their ability to interact with a broad range of partner molecules. Multiple types of interacting IDRs were identified including molecular recognition fragments (MoRFs), short linear sequence motifs (SLiMs), and protein-, nucleic acids- and lipid-binding regions. Prediction of binding IDRs in protein sequences is gaining momentum in recent years. We survey 38 predictors of binding IDRs that target interactions with a diverse set of partners, such as peptides, proteins, RNA, DNA and lipids. We offer a historical perspective and highlight key events that fueled efforts to develop these methods. These tools rely on a diverse range of predictive architectures that include scoring functions, regular expressions, traditional and deep machine learning and meta-models. Recent efforts focus on the development of deep neural network-based architectures and extending coverage to RNA, DNA and lipid-binding IDRs. We analyze availability of these methods and show that providing implementations and webservers results in much higher rates of citations/use. We also make several recommendations to take advantage of modern deep network architectures, develop tools that bundle predictions of multiple and different types of binding IDRs, and work on algorithms that model structures of the resulting complexes.

Where protein structure and cell diversity meet

Protein-protein interaction networks - interactomes - are charted with the hope to understand how phenotypes emerge and how they are altered in disease states. Early efforts to map interactomes have focused on the assembly of context agnostic, reference networks. However, recent studies have mapped interactomes across different cell lines and tissues, finding highly variable interactomes due to the rewiring of protein-protein interactions in different contexts. Increasing evidence points to significant links between protein structure and interactome diversity seen across cell types and tissues. We discuss how recent findings support the key role of alternative splicing and phosphorylation, two well-established regulators of protein structural and functional diversity, in defining cell type- and tissue-specific interactomes. Moreover, we show that intrinsically disordered protein regions are most favorably equipped to support interactome rewiring by acting as hubs of protein structure and function regulation.

Compositional Bias of Intrinsically Disordered Proteins and Regions and Their Predictions

Intrinsically disordered regions (IDRs) carry out many cellular functions and vary in length and placement in protein sequences. This diversity leads to variations in the underlying compositional biases, which were demonstrated for the short vs. long IDRs. We analyze compositional biases across four classes of disorder: fully disordered proteins; short IDRs; long IDRs; and binding IDRs. We identify three distinct biases: for the fully disordered proteins, the short IDRs and the long and binding IDRs combined. We also investigate compositional bias for putative disorder produced by leading disorder predictors and find that it is similar to the bias of the native disorder. Interestingly, the accuracy of disorder predictions across different methods is correlated with the correctness of the compositional bias of their predictions highlighting the importance of the compositional bias. The predictive quality is relatively low for the disorder classes with compositional bias that is the most different from the “generic” disorder bias, while being much higher for the classes with the most similar bias. We discover that different predictors perform best across different classes of disorder. This suggests that no single predictor is universally best and motivates the development of new architectures that combine models that target specific disorder classes.

Short Linear Motifs (SLiMs) in “Core” RxLR Effectors of Phytophthora parasitica var. nicotianae : a Case of PpRxLR1 Effector

Oomycetes of the genus Phytophthora encompass several of the most successful plant pathogens described to date. The success of infection by Phytophthora species is attributed to the pathogens’ ability to secrete effector proteins that alter the host’s physiological processes. Structural analyses of effector proteins mainly from bacterial and viral pathogens have revealed the presence of intrinsically disordered regions that host short linear motifs (SLiMs). These motifs play important biological roles by facilitating protein-protein interactions as well as protein translocation. Nonetheless, SLiMs in Phytophthora species RxLR effectors have not been investigated previously and their roles remain unknown. Using a bioinformatics pipeline, we identified 333 candidate RxLR effectors in the strain INRA 310 of Phytophthora parasitica. Of these, 71 (21%) were also found to be present in 10 other genomes of P. parasitica, and hence, these were designated core RxLR effectors (CREs). Within the CRE sequences, the N terminus exhibited enrichment in intrinsically disordered regions compared to the C terminus, suggesting a potential role of disorder in effector translocation. Although the disorder content was reduced in the C-terminal regions, it is important to mention that most SLiMs were in this terminus. PpRxLR1 is one of the 71 CREs identified in this study, and its genes encode a 6-amino acid (aa)-long SLiM at the C terminus. We showed that PpRxLR1 interacts with several host proteins that are implicated in defense. Structural analysis of this effector using homology modeling revealed the presence of potential ligand-binding sites. Among key residues that were predicted to be crucial for ligand binding, L¹⁰² and Y¹⁰⁶ were of interest since they form part of the 6-aa-long PpRxLR1 SLiM. In silico substitution of these two residues to alanine was predicted to have a significant effect on both the function and the structure of PpRxLR1 effector. Molecular docking simulations revealed possible interactions between PpRxLR1 effector and ubiquitin-associated proteins. The ubiquitin-like SLiM carried in this effector was shown to be a potential mediator of these interactions. Further studies are required to validate and elucidate the underlying molecular mechanism of action.

IMPORTANCE The continuous gain and loss of RxLR effectors makes the control of Phytophthora spp. difficult. Therefore, in this study, we endeavored to identify RxLR effectors that are highly conserved among species, also known as “core” RxLR effectors (CREs). We reason that these highly conserved effectors target conserved proteins or processes; thus, they can be harnessed in breeding for durable resistance in plants. To further understand the mechanisms of action of CREs, structural dissection of these proteins is crucial. Intrinsically disordered regions (IDRs) that do not adopt a fixed, three-dimensional fold carry short linear motifs (SLiMs) that mediate biological functions of proteins. The presence and potential role of these SLiMs in CREs of Phytophthora spp. have been overlooked. To our knowledge, we have effectively identified CREs as well as SLiMs with the potential of promoting effector virulence. Together, this work has advanced our comprehension of Phytophthora RxLR effector function and may facilitate the development of innovative and effective control strategies.

Characterization of intrinsically disordered regions in proteins informed by human genetic diversity

All proteomes contain both proteins and polypeptide segments that don’t form a defined three-dimensional structure yet are biologically active—called intrinsically disordered proteins and regions (IDPs and IDRs). Most of these IDPs/IDRs lack useful functional annotation limiting our understanding of their importance for organism fitness. Here we characterized IDRs using protein sequence annotations of functional sites and regions available in the UniProt knowledgebase (“UniProt features”: active site, ligand-binding pocket, regions mediating protein-protein interactions, etc.). By measuring the statistical enrichment of twenty-five UniProt features in 981 IDRs of 561 human proteins, we identified eight features that are commonly located in IDRs. We then collected the genetic variant data from the general population and patient-based databases and evaluated the prevalence of population and pathogenic variations in IDPs/IDRs. We observed that some IDRs tolerate 2 to 12-times more single amino acid-substituting missense mutations than synonymous changes in the general population. However, we also found that 37% of all germline pathogenic mutations are located in disordered regions of 96 proteins. Based on the observed-to-expected frequency of mutations, we categorized 34 IDRs in 20 proteins (DDX3X, KIT, RB1, etc.) as intolerant to mutation. Finally, using statistical analysis and a machine learning approach, we demonstrate that mutation-intolerant IDRs carry a distinct signature of functional features. Our study presents a novel approach to assign functional importance to IDRs by leveraging the wealth of available genetic data, which will aid in a deeper understating of the role of IDRs in biological processes and disease mechanisms.

Intrinsically disordered proteins play diverse roles in cell signaling

Abstract

Signaling pathways allow cells to detect and respond to a wide variety of chemical (e.g. Ca²⁺ or chemokine proteins) and physical stimuli (e.g., sheer stress, light). Together, these pathways form an extensive communication network that regulates basic cell activities and coordinates the function of multiple cells or tissues. The process of cell signaling imposes many demands on the proteins that comprise these pathways, including the abilities to form active and inactive states, and to engage in multiple protein interactions. Furthermore, successful signaling often requires amplifying the signal, regulating or tuning the response to the signal, combining information sourced from multiple pathways, all while ensuring fidelity of the process. This sensitivity, adaptability, and tunability are possible, in part, due to the inclusion of intrinsically disordered regions in many proteins involved in cell signaling. The goal of this collection is to highlight the many roles of intrinsic disorder in cell signaling. Following an overview of resources that can be used to study intrinsically disordered proteins, this review highlights the critical role of intrinsically disordered proteins for signaling in widely diverse organisms (animals, plants, bacteria, fungi), in every category of cell signaling pathway (autocrine, juxtacrine, intracrine, paracrine, and endocrine) and at each stage (ligand, receptor, transducer, effector, terminator) in the cell signaling process. Thus, a cell signaling pathway cannot be fully described without understanding how intrinsically disordered protein regions contribute to its function. The ubiquitous presence of intrinsic disorder in different stages of diverse cell signaling pathways suggest that more mechanisms by which disorder modulates intra- and inter-cell signals remain to be discovered.

Graphical abstract

A FRET-Based Biosensor for the Src N-Terminal Regulatory Element

In signaling proteins, intrinsically disordered regions often represent regulatory elements, which are sensitive to environmental effects, ligand binding, and post-translational modifications. The conformational space sampled by disordered regions can be affected by environmental stimuli and these changes trigger, vis a vis effector domain, downstream processes. The disordered nature of these regulatory elements enables signal integration and graded responses but prevents the application of classical approaches for drug screening based on the existence of a fixed three-dimensional structure. We have designed a genetically encodable biosensor for the N-terminal regulatory element of the c-Src kinase, the first discovered protooncogene and lead representative of the Src family of kinases. The biosensor is formed by two fluorescent proteins forming a FRET pair fused at the two extremes of a construct including the SH4, unique and SH3 domains of Src. An internal control is provided by an engineered proteolytic site allowing the generation of an identical mixture of the disconnected fluorophores. We show FRET variations induced by ligand binding. The biosensor has been used for a high-throughput screening of a library of 1669 compounds with seven hits confirmed by NMR.

Drugging the Undruggable: Targeting the N-Terminal Domain of Nuclear Hormone Receptors

This chapter focuses on the development of drugs targeting the N-terminal domain of nuclear hormone receptors, using progress with the androgen receptor as an example. Historically, development of therapies targeting nuclear hormone receptors has focused on the folded C-terminal ligand-binding domain. Therapies were traditionally not developed to target the intrinsically disordered N-terminal domain as it was considered "undruggable". Recent developments have now shown it is possible to direct therapies to the N-terminal domain. This chapter will provide an introduction of the structure and function of the domains of nuclear hormone receptors, followed by a discussion of the rationale supporting the development of N-terminal domain inhibitors. Chemistry and mechanisms of action of small molecule inhibitors will be described with emphasis on N-terminal domain inhibitors developed to the androgen receptor including those in clinical trials.

High-throughput total RNA sequencing in single cells using VASA-seq

Most methods for single-cell transcriptome sequencing amplify the termini of polyadenylated transcripts, capturing only a small fraction of the total cellular transcriptome. This precludes the detection of many long non-coding, short non-coding and non-polyadenylated protein-coding transcripts and hinders alternative splicing analysis. We, therefore, developed VASA-seq to detect the total transcriptome in single cells, which is enabled by fragmenting and tailing all RNA molecules subsequent to cell lysis. The method is compatible with both plate-based formats and droplet microfluidics. We applied VASA-seq to more than 30,000 single cells in the developing mouse embryo during gastrulation and early organogenesis. Analyzing the dynamics of the total single-cell transcriptome, we discovered cell type markers, many based on non-coding RNA, and performed in vivo cell cycle analysis via detection of non-polyadenylated histone genes. RNA velocity characterization was improved, accurately retracing blood maturation trajectories. Moreover, our VASA-seq data provide a comprehensive analysis of alternative splicing during mammalian development, which highlighted substantial rearrangements during blood development and heart morphogenesis.

Circulating extracellular vesicles and rheumatoid arthritis: a proteomic analysis

Circulating extracellular vesicles (EVs) are membrane-bound nanoparticles secreted by most cells for intracellular communication and transportation of biomolecules. EVs carry proteins, lipids, nucleic acids, and receptors that are involved in human physiology and pathology. EV cargo is variable and highly related to the type and state of the cellular origin. Three subtypes of EVs have been identified: exosomes, microvesicles, and apoptotic bodies. Exosomes are the smallest and the most well-studied class of EVs that regulate different biological processes and participate in several diseases, such as cancers and autoimmune diseases. Proteomic analysis of exosomes succeeded in profiling numerous types of proteins involved in disease development and prognosis. In rheumatoid arthritis (RA), exosomes revealed a potential function in joint inflammation. These EVs possess a unique function, as they can transfer specific autoantigens and mediators between distant cells. Current proteomic data demonstrated that exosomes could provide beneficial effects against autoimmunity and exert an immunosuppressive action, particularly in RA. Based on these observations, effective therapeutic strategies have been developed for arthritis and other inflammatory disorders.

Cross-Linking Mass Spectrometry for Investigating Protein Conformations and Protein-Protein Interactions─A Method for All Seasons

Mass spectrometry (MS) has become one of the key technologies of structural biology. In this review, the contributions of chemical cross-linking combined with mass spectrometry (XL-MS) for studying three-dimensional structures of proteins and for investigating protein-protein interactions are outlined. We summarize the most important cross-linking reagents, software tools, and XL-MS workflows and highlight prominent examples for characterizing proteins, their assemblies, and interaction networks in vitro and in vivo. Computational modeling plays a crucial role in deriving 3D-structural information from XL-MS data. Integrating XL-MS with other techniques of structural biology, such as cryo-electron microscopy, has been successful in addressing biological questions that to date could not be answered. XL-MS is therefore expected to play an increasingly important role in structural biology in the future.

Canonical and Divergent N-Terminal HBx Isoform Proteins Unveiled: Characteristics and Roles during HBV Replication

Hepatitis B virus (HBV) X protein (HBx) is a viral regulatory and multifunctional protein. It is well-known that the canonical HBx reading frame bears two phylogenetically conserved internal in-frame translational initiation codons at Met2 and Met3, thus possibly generating divergent N-terminal smaller isoforms during translation. Here, we demonstrate that the three distinct HBx isoforms are generated from the ectopically expressed HBV HBx gene, named XF (full-length), XM (medium-length), and XS (short-length); they display different subcellular localizations when expressed individually in cultured hepatoma cells. Particularly, the smallest HBx isoform, XS, displayed a predominantly cytoplasmic localization. To study HBx proteins during viral replication, we performed site-directed mutagenesis to target the individual or combinatorial expression of the HBx isoforms within the HBV viral backbone (full viral genome). Our results indicate that of all HBx isoforms, only the smallest HBx isoform, XS, can restore WT levels of HBV replication, and bind to the viral mini chromosome, thereby establishing an active chromatin state, highlighting its crucial activities during HBV replication. Intriguingly, we found that sequences of HBV HBx genotype H are devoid of the conserved Met3 position, and therefore HBV genotype H infection is naturally silent for the expression of the HBx XS isoform. Finally, we found that the HBx XM (medium-length) isoform shares significant sequence similarity with the N-terminus domain of the COMMD8 protein, a member of the copper metabolism MURR1 domain-containing (COMMD) protein family. This novel finding might facilitate studies on the phylogenetic origin of the HBV X protein. The identification and functional characterization of its isoforms will shift the paradigm by changing the concept of HBx from being a unique, canonical, and multifunctional protein toward the occurrence of different HBx isoforms, carrying out different overlapping functions at different subcellular localizations during HBV genome replication. Significantly, our current work unveils new crucial HBV targets to study for potential antiviral research, and human virus pathogenesis.

What's in the BAGs? Intrinsic disorder angle of the multifunctionality of the members of a family of chaperone regulators

In humans, the family of Bcl-2 associated athanogene (BAG) proteins includes six members characterized by exceptional multifunctionality and engagement in the pathogenesis of various diseases. All of them are capable of interacting with a multitude of often unrelated binding partners. Such binding promiscuity and related functional and pathological multifacetedness cannot be explained or understood within the frames of the classical "one protein-one structure-one function" model, which also fails to explain the presence of multiple isoforms generated for BAG proteins by alternative splicing or alternative translation initiation and their extensive posttranslational modifications. However, all these mysteries can be solved by taking into account the intrinsic disorder phenomenon. In fact, high binding promiscuity and potential to participate in a broad spectrum of interactions with multiple binding partners, as well as a capability to be multifunctional and multipathogenic, are some of the characteristic features of intrinsically disordered proteins and intrinsically disordered protein regions. Such functional proteins or protein regions lacking unique tertiary structures constitute a cornerstone of the protein structure-function continuum concept. The aim of this paper is to provide an overview of the functional roles of human BAG proteins from the perspective of protein intrinsic disorder which will provide a means for understanding their binding promiscuity, multifunctionality, and relation to the pathogenesis of various diseases.

DeepSSPred: A Deep Learning Based Sulfenylation Site Predictor Via a Novel nSegmented Optimize Federated Feature Encoder

BACKGROUND

S-sulfenylation (S-sulphenylation, or sulfenic acid) proteins, are special kinds of post-translation modification, which plays an important role in various physiological and pathological processes such as cytokine signaling, transcriptional regulation, and apoptosis. Despite these aforementioned significances, and by complementing existing wet methods, several computational models have been developed for sulfenylation cysteine sites prediction. However, the performance of these models was not satisfactory due to inefficient feature schemes, severe imbalance issues, and lack of an intelligent learning engine.

OBJECTIVE

In this study, our motivation is to establish a strong and novel computational predictor for discrimination of sulfenylation and non-sulfenylation sites.

METHODS

In this study, we report an innovative bioinformatics feature encoding tool, named DeepSSPred, in which, resulting encoded features is obtained via nSegmented hybrid feature, and then the resampling technique called synthetic minority oversampling was employed to cope with the severe imbalance issue between SC-sites (minority class) and non-SC sites (majority class). State of the art 2D-Convolutional Neural Network was employed over rigorous 10-fold jackknife cross-validation technique for model validation and authentication.

RESULTS

Following the proposed framework, with a strong discrete presentation of feature space, machine learning engine, and unbiased presentation of the underline training data yielded into an excellent model that outperforms with all existing established studies. The proposed approach is 6% higher in terms of MCC from the first best. On an independent dataset, the existing first best study failed to provide sufficient details. The model obtained an increase of 7.5% in accuracy, 1.22% in Sn, 12.91% in Sp and 13.12% in MCC on the training data and12.13% of ACC, 27.25% in Sn, 2.25% in Sp, and 30.37% in MCC on an independent dataset in comparison with 2nd best method. These empirical analyses show the superlative performance of the proposed model over both training and Independent dataset in comparison with existing literature studies.

CONCLUSION

In this research, we have developed a novel sequence-based automated predictor for SC-sites, called DeepSSPred. The empirical simulations outcomes with a training dataset and independent validation dataset have revealed the efficacy of the proposed theoretical model. The good performance of DeepSSPred is due to several reasons, such as novel discriminative feature encoding schemes, SMOTE technique, and careful construction of the prediction model through the tuned 2D-CNN classifier. We believe that our research work will provide a potential insight into a further prediction of S-sulfenylation characteristics and functionalities. Thus, we hope that our developed predictor will significantly helpful for large scale discrimination of unknown SC-sites in particular and designing new pharmaceutical drugs in general.

Unstructural Biology of TRP Ion Channels: The Role of Intrinsically Disordered Regions in Channel Function and Regulation

The first genuine high-resolution single particle cryo-electron microscopy structure of a membrane protein determined was a transient receptor potential (TRP) ion channel, TRPV1, in 2013. This methodical breakthrough opened up a whole new world for structural biology and ion channel aficionados alike. TRP channels capture the imagination due to the sheer endless number of tasks they carry out in all aspects of animal physiology. To date, structures of at least one representative member of each of the six mammalian TRP channel subfamilies as well as of a few non-mammalian families have been determined. These structures were instrumental for a better understanding of TRP channel function and regulation. However, all of the TRP channel structures solved so far are incomplete since they miss important information about highly flexible regions found mostly in the channel N- and C-termini. These intrinsically disordered regions (IDRs) can represent between a quarter to almost half of the entire protein sequence and act as important recruitment hubs for lipids and regulatory proteins. Here, we analyze the currently available TRP channel structures with regard to the extent of these "missing" regions and compare these findings to disorder predictions. We discuss select examples of intra- and intermolecular crosstalk of TRP channel IDRs with proteins and lipids as well as the effect of splicing and post-translational modifications, to illuminate their importance for channel function and to complement the prevalently discussed structural biology of these versatile and fascinating proteins with their equally relevant 'unstructural' biology.

Abelson kinase's intrinsically disordered region plays essential roles in protein function and protein stability

Background

The non-receptor tyrosine kinase Abelson (Abl) is a key player in oncogenesis, with kinase inhibitors serving as paradigms of targeted therapy. Abl also is a critical regulator of normal development, playing conserved roles in regulating cell behavior, brain development and morphogenesis. Drosophila offers a superb model for studying Abl’s normal function, because, unlike mammals, there is only a single fly Abl family member. In exploring the mechanism of action of multi-domain scaffolding proteins like Abl, one route is to define the roles of their individual domains. Research into Abl’s diverse roles in embryonic morphogenesis revealed many surprises. For instance, kinase activity, while important, is not crucial for all Abl activities, and the C-terminal F-actin binding domain plays a very modest role. This turned our attention to one of Abl’s least understood features—the long intrinsically-disordered region (IDR) linking Abl’s kinase and F-actin binding domains. The past decade revealed unexpected, important roles for IDRs in diverse cell functions, as sites of posttranslational modifications, mediating multivalent interactions and enabling assembly of biomolecular condensates via phase separation. Previous work deleting conserved regions in Abl’s IDR revealed an important role for a PXXP motif, but did not identify any other essential regions.

Methods

Here we extend this analysis by deleting the entire IDR, and asking whether Abl∆IDR rescues the diverse roles of Abl in viability and embryonic morphogenesis in Drosophila.

Results

This revealed that the IDR is essential for embryonic and adult viability, and for cell shape changes and cytoskeletal regulation during embryonic morphogenesis, and, most surprisingly, revealed a role in modulating protein stability.

Conclusion

Our data provide new insights into the role of the IDR in an important signaling protein, the non-receptor kinase Abl, suggesting that it is essential for all aspects of protein function during embryogenesis, and revealing a role in protein stability. These data will stimulate new explorations of the mechanisms by which the IDR regulates Abl stability and function, both in Drosophila and also in mammals. They also will stimulate further interest in the broader roles IDRs play in diverse signaling proteins.

Heritable pattern of oxidized DNA base repair coincides with pre-targeting of repair complexes to open chromatin

Human genome stability requires efficient repair of oxidized bases, which is initiated via damage recognition and excision by NEIL1 and other base excision repair (BER) pathway DNA glycosylases (DGs). However, the biological mechanisms underlying detection of damaged bases among the million-fold excess of undamaged bases remain enigmatic. Indeed, mutation rates vary greatly within individual genomes, and lesion recognition by purified DGs in the chromatin context is inefficient. Employing super-resolution microscopy and co-immunoprecipitation assays, we find that acetylated NEIL1 (AcNEIL1), but not its non-acetylated form, is predominantly localized in the nucleus in association with epigenetic marks of uncondensed chromatin. Furthermore, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) revealed non-random AcNEIL1 binding near transcription start sites of weakly transcribed genes and along highly transcribed chromatin domains. Bioinformatic analyses revealed a striking correspondence between AcNEIL1 occupancy along the genome and mutation rates, with AcNEIL1-occupied sites exhibiting fewer mutations compared to AcNEIL1-free domains, both in cancer genomes and in population variation. Intriguingly, from the evolutionarily conserved unstructured domain that targets NEIL1 to open chromatin, its damage surveillance of highly oxidation-susceptible sites to preserve essential gene function and to limit instability and cancer likely originated ∼500 million years ago during the buildup of free atmospheric oxygen.

Intrinsic disorder is an essential characteristic of components in the conserved circadian circuit

INTRODUCTION

The circadian circuit, a roughly 24 h molecular feedback loop, or clock, is conserved from bacteria to animals and allows for enhanced organismal survival by facilitating the anticipation of the day/night cycle. With circadian regulation reportedly impacting as high as 80% of protein coding genes in higher eukaryotes, the protein-based circadian clock broadly regulates physiology and behavior. Due to the extensive interconnection between the clock and other cellular systems, chronic disruption of these molecular rhythms leads to a decrease in organismal fitness as well as an increase of disease rates in humans. Importantly, recent research has demonstrated that proteins comprising the circadian clock network display a significant amount of intrinsic disorder.

MAIN BODY

In this work, we focus on the extent of intrinsic disorder in the circadian clock and its potential mechanistic role in circadian timing. We highlight the conservation of disorder by quantifying the extent of computationally-predicted protein disorder in the core clock of the key eukaryotic circadian model organisms Drosophila melanogaster, Neurospora crassa, and Mus musculus. We further examine previously published work, as well as feature novel experimental evidence, demonstrating that the core negative arm circadian period drivers FREQUENCY (Neurospora crassa) and PERIOD-2 (PER2) (Mus musculus), possess biochemical characteristics of intrinsically disordered proteins. Finally, we discuss the potential contributions of the inherent biophysical principals of intrinsically disordered proteins that may explain the vital mechanistic roles they play in the clock to drive their broad evolutionary conservation in circadian timekeeping.

CONCLUSION

The pervasive conservation of disorder amongst the clock in the crown eukaryotes suggests that disorder is essential for optimal circadian timing from fungi to animals, providing vital homeostatic cellular maintenance and coordinating organismal physiology across phylogenetic kingdoms. Video abstract.

Combinatorial expression of GPCR isoforms affects signalling and drug responses

G-protein-coupled receptors (GPCRs) are membrane proteins that modulate physiology across human tissues in response to extracellular signals. GPCR-mediated signalling can differ because of changes in the sequence1,2 or expression3 of the receptors, leading to signalling bias when comparing diverse physiological systems4. An underexplored source of such bias is the generation of functionally diverse GPCR isoforms with different patterns of expression across different tissues. Here we integrate data from human tissue-level transcriptomes, GPCR sequences and structures, proteomics, single-cell transcriptomics, population-wide genetic association studies and pharmacological experiments. We show how a single GPCR gene can diversify into several isoforms with distinct signalling properties, and how unique isoform combinations expressed in different tissues can generate distinct signalling states. Depending on their structural changes and expression patterns, some of the detected isoforms may influence cellular responses to drugs and represent new targets for developing drugs with improved tissue selectivity. Our findings highlight the need to move from a canonical to a context-specific view of GPCR signalling that considers how combinatorial expression of isoforms in a particular cell type, tissue or organism collectively influences receptor signalling and drug responses.

Significance of alternative splicing in cancer cells

Objective

Alternative splicing can generate various structural and functional protein isoforms. Recently, accumulating evidence shows a relationship between alternative splicing and cancer. Cancer is a complex and chronic disease that involves malignant transformation. In this review, we consider alternative splicing events in relation to the hallmarks of cancer cells, and discuss current therapies to treat cancer-related to alternative splicing.

Data sources

Data cited in this article are from the PubMed and Embase database, primarily focusing on research published from 2000 to 2018.

Study selection

Articles were selected with the search terms “alternative splicing,” “cancer cell,” “tumor microenvironment,” and “therapy.”

Results

Alternative splicing plays an important role in tumorigenesis, development, and escape from cell death. Taking this trait of cancer cells into consideration will allow more definite diagnoses of cancer, and allow the development of more effective medicines to intervene in cancer that could focus on controlling alternative splicing or competitively binding to the final products.

Conclusions

Alternative splicing is common in cancer cells. Consideration of alternative splicing may allow different strategies for cancer therapy or the identification of novel biomarkers for cancer diagnosis.

Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome

The protein-level translational status and function of many alternative splicing events remain poorly understood. We use an RNA sequencing (RNA-seq)-guided proteomics method to identify protein alternative splicing isoforms in the human proteome by constructing tissue-specific protein databases that prioritize transcript splice junction pairs with high translational potential. Using the custom databases to reanalyze ~80 million mass spectra in public proteomics datasets, we identify more than 1,500 noncanonical protein isoforms across 12 human tissues, including ~400 sequences undocumented on TrEMBL and RefSeq databases. We apply the method to original quantitative mass spectrometry experiments and observe widespread isoform regulation during human induced pluripotent stem cell cardiomyocyte differentiation. On a proteome scale, alternative isoform regions overlap frequently with disordered sequences and post-translational modification sites, suggesting that alternative splicing may regulate protein function through modulating intrinsically disordered regions. The described approach may help elucidate functional consequences of alternative splicing and expand the scope of proteomics investigations in various systems.

The translation and function of many alternative splicing events await confirmation at the protein level. Lau et al. use an integrated proteotranscriptomics approach to identify non-canonical and undocumented isoforms from 12 organs in the human proteome. Alternative isoforms interfere with functional sequence features and are differentially regulated during iPSC cardiomyocyte differentiation.

Functional and structural features of proteins associated with alternative splicing

The alternative splicing is a mechanism increasing the number of expressed proteins and a variety of these functions. We uncovered the protein domains most frequently lacked or occurred in the splice variants. Proteins presented by several isoforms participate in such processes as transcription regulation, immune response, etc. Our results displayed the association of alternative splicing with branched regulatory pathways. By considering the published data on the protein proteins encoded by the 18th human chromosome, we noted that alternative products display the differences in several functional features, such as phosphorylation, subcellular location, ligand specificity, protein-protein interactions, etc. The investigation of alternative variants referred to the protein kinase domain was performed by comparing the alternative sequences with 3D structures. It was shown that large enough insertions/deletions could be compatible with the kinase fold if they match between the conserved secondary structures. Using the 3D data on human proteins, we showed that conformational flexibility could accommodate fold alterations in splice variants. The investigations of structural and functional differences in splice isoforms are required to understand how to distinguish the isoforms expressed as functioning proteins from the non-realized transcripts. These studies allow filling the gap between genomic and proteomic data.

Presence and structure-activity relationship of intrinsically disordered regions across mucins

Many members of the mucin family are evolutionarily conserved and are often aberrantly expressed and glycosylated in various benign and malignant pathologies leading to tumor invasion, metastasis, and immune evasion. The large size and extensive glycosylation present challenges to study the mucin structure using traditional methods, including crystallography. We offer the hypothesis that the functional versatility of mucins may be attributed to the presence of intrinsically disordered regions (IDRs) that provide dynamism and flexibility and that the IDRs offer potential therapeutic targets. Herein, we examined the links between the mucin structure and function based on IDRs, posttranslational modifications (PTMs), and potential impact on their interactome. Using sequence-based bioinformatics tools, we observed that mucins are predicted to be moderately (20%-40%) to highly (>40%) disordered and many conserved mucin domains could be disordered. Phosphorylation sites overlap with IDRs throughout the mucin sequences. Additionally, the majority of predicted O- and N- glycosylation sites in the tandem repeat regions occur within IDRs and these IDRs contain a large number of functional motifs, that is, molecular recognition features (MoRFs), which directly influence protein-protein interactions (PPIs). This investigation provides a novel perspective and offers an insight into the complexity and dynamic nature of mucins.

Computational Prediction of Intrinsic Disorder in Protein Sequences with the disCoP Meta-predictor

Intrinsically disordered proteins are either entirely disordered or contain disordered regions in their native state. These proteins and regions function without the prerequisite of a stable structure and were found to be abundant across all kingdoms of life. Experimental annotation of disorder lags behind the rapidly growing number of sequenced proteins, motivating the development of computational methods that predict disorder in protein sequences. DisCoP is a user-friendly webserver that provides accurate sequence-based prediction of protein disorder. It relies on meta-architecture in which the outputs generated by multiple disorder predictors are combined together to improve predictive performance. The architecture of disCoP is presented, and its accuracy relative to several other disorder predictors is briefly discussed. We describe usage of the web interface and explain how to access and read results generated by this computational tool. We also provide an example of prediction results and interpretation. The disCoP's webserver is publicly available at http://biomine.cs.vcu.edu/servers/disCoP/ .

IDP-LZerD: Software for Modeling Disordered Protein Interactions

Modeling the tertiary structure of protein-protein interaction complex has been well studied over many years, especially in the case where the structures of both binding partners are roughly the same before and after binding. However, the assembly of complexes with less-ordered partners is a much harder problem, and modeling even small amounts of flexibility can pose a challenge. In an extreme case, where one of the binding partners is intrinsically disordered before binding, we have previously shown that by initially disregarding the coupling between windows of these intrinsically disordered proteins (IDPs), we can reliably assemble complexes involving IDPs up to at least 69 residues long. Here, we detail the use of the IDP-LZerD package and protocol.

DISOselect: Disorder predictor selection at the protein level

The intense interest in the intrinsically disordered proteins in the life science community, together with the remarkable advancements in predictive technologies, have given rise to the development of a large number of computational predictors of intrinsic disorder from protein sequence. While the growing number of predictors is a positive trend, we have observed a considerable difference in predictive quality among predictors for individual proteins. Furthermore, variable predictor performance is often inconsistent between predictors for different proteins, and the predictor that shows the best predictive performance depends on the unique properties of each protein sequence. We propose a computational approach, DISOselect, to estimate the predictive performance of 12 selected predictors for individual proteins based on their unique sequence-derived properties. This estimation informs the users about the expected predictive quality for a selected disorder predictor and can be used to recommend methods that are likely to provide the best quality predictions. Our solution does not depend on the results of any disorder predictor; the estimations are made based solely on the protein sequence. Our solution significantly improves predictive performance, as judged with a test set of 1,000 proteins, when compared to other alternatives. We have empirically shown that by using the recommended methods the overall predictive performance for a given set of proteins can be improved by a statistically significant margin. DISOselect is freely available for non-commercial users through the webserver at http://biomine.cs.vcu.edu/servers/DISOselect/.

Features of molecular recognition of intrinsically disordered proteins via coupled folding and binding

The sequence-structure-function paradigm of proteins has been revolutionized by the discovery of intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). In contrast to traditional ordered proteins, IDPs/IDRs are unstructured under physiological conditions. The absence of well-defined three-dimensional structures in the free state of IDPs/IDRs is fundamental to their function. Folding upon binding is an important mode of molecular recognition for IDPs/IDRs. While great efforts have been devoted to investigating the complex structures and binding kinetics and affinities, our knowledge on the binding mechanisms of IDPs/IDRs remains very limited. Here, we review recent advances on the binding mechanisms of IDPs/IDRs. The structures and kinetic parameters of IDPs/IDRs can vary greatly, and the binding mechanisms can be highly dependent on the structural properties of IDPs/IDRs. IDPs/IDRs can employ various combinations of conformational selection and induced fit in a binding process, which can be templated by the target and/or encoded by the IDP/IDR. Further studies should provide deeper insights into the molecular recognition of IDPs/IDRs and enable the rational design of IDP/IDR binding mechanisms in the future.

Integrating disorder in globular multidomain proteins: Fuzzy sensors and the role of SH3 domains

Intrinsically disordered proteins represent about one third of eukaryotic proteins. An additional third correspond to proteins containing folded domains as well as large intrinsically disordered regions (IDR). While IDRs may represent functionally autonomous domains, in some instances it has become clear that they provide a new layer of regulation for the activity displayed by the folded domains. The sensitivity of the conformational ensembles defining the properties of IDR to small changes in the cellular environment and the capacity to modulate this response through post-translational modifications makes IDR ideal sensors enabling continuous, integrative responses to complex cellular inputs. Folded domains (FD), on the other hand, are ideal effectors, e.g. by catalyzing enzymatic reactions or participating in binary on/off switches. In this perspective review we discuss the possible role of intramolecular fuzzy complexes to integrate the very different dynamic scales of IDR and FD, inspired on the recent observations of such dynamic complexes in Src family kinases, and we explore the possible general role of the SH3 domains connecting IDRs and FD.

Intrinsically disordered proteins and structured proteins with intrinsically disordered regions have different functional roles in the cell

Many studies about classification and the functional annotation of intrinsically disordered proteins (IDPs) are based on either the occurrence of long disordered regions or the fraction of disordered residues in the sequence. Taking into account both criteria we separate the human proteome, taken as a case study, into three variants of proteins: i) ordered proteins (ORDPs), ii) structured proteins with intrinsically disordered regions (IDPRs), and iii) intrinsically disordered proteins (IDPs). The focus of this work is on the different functional roles of IDPs and IDPRs, which up until now have been generally considered as a whole. Previous studies assigned a large set of functional roles to the general category of IDPs. We show here that IDPs and IDPRs have non-overlapping functional spectra, play different roles in human diseases, and deserve to be treated as distinct categories of proteins. IDPs enrich only a few classes, functions, and processes: nucleic acid binding proteins, chromatin binding proteins, transcription factors, and developmental processes. In contrast, IDPRs are spread over several functional protein classes and GO annotations which they partly share with ORDPs. As regards to diseases, we observe that IDPs enrich only cancer-related proteins, at variance with previous results reporting that IDPs are widespread also in cardiovascular and neurodegenerative pathologies. Overall, the operational separation of IDPRs from IDPs is relevant towards correct estimates of the occurrence of intrinsically disordered proteins in genome-wide studies and in the understanding of the functional spectra associated to different flavors of protein disorder.

Entropy, Fluctuations, and Disordered Proteins

Entropy should directly reflect the extent of disorder in proteins. By clustering structurally related proteins and studying the multiple-sequence-alignment of the sequences of these clusters, we were able to link between sequence, structure, and disorder information. We introduced several parameters as measures of fluctuations at a given MSA site and used these as representative of the sequence and structure entropy at that site. In general, we found a tendency for negative correlations between disorder and structure, and significant positive correlations between disorder and the fluctuations in the system. We also found evidence for residue-type conservation for those residues proximate to potentially disordered sites. Mutation at the disorder site itself appear to be allowed. In addition, we found positive correlation for disorder and accessible surface area, validating that disordered residues occur in exposed regions of proteins. Finally, we also found that fluctuations in the dihedral angles at the original mutated residue and disorder are positively correlated while dihedral angle fluctuations in spatially proximal residues are negatively correlated with disorder. Our results seem to indicate permissible variability in the disordered site, but greater rigidity in the parts of the protein with which the disordered site interacts. This is another indication that disordered residues are involved in protein function.

Cyclophilin A allows the allosteric regulation of a structural motif in the disordered domain 2 of NS5A and thereby fine-tunes HCV RNA replication

Implicated in numerous human diseases, intrinsically disordered proteins (IDPs) are dynamic ensembles of interconverting conformers that often contain many proline residues. Whether and how proline conformation regulates the functional aspects of IDPs remains an open question, however. Here, we studied the disordered domain 2 of nonstructural protein 5A (NS5A-D2) of hepatitis C virus (HCV). NS5A-D2 comprises a short structural motif (PW-turn) embedded in a proline-rich sequence, whose interaction with the human prolyl isomerase cyclophilin A (CypA) is essential for viral RNA replication. Using NMR, we show here that the PW-turn motif exists in a conformational equilibrium between folded and disordered states. We found that the fraction of conformers in the NS5A-D2 ensemble that adopt the structured motif is allosterically modulated both by the cis/trans isomerization of the surrounding prolines that are CypA substrates and by substitutions conferring resistance to cyclophilin inhibitor. Moreover, we noted that this fraction is directly correlated with HCV RNA replication efficiency. We conclude that CypA can fine-tune the dynamic ensemble of the disordered NS5A-D2, thereby regulating viral RNA replication efficiency.

Functions of intrinsic disorder in proteins involved in DNA demethylation during pre-implantation embryonic development

DNA demethylation is involved in many biological processes during pre-implantation embryonic development in mammals. To date, the complicated mechanism of DNA demethylation is still not fully understood. Ten-eleven translocation family (TET3, TET1 and TET2), thymine DNA glycosylase (TDG) and DNA methyltransferase 1 (DNMT1) are considered the major protein enzymes of DNA demethylation in pre-implantation embryos. TET3, TET1, TET2, TDG, and DNMT1 contain abundant levels of intrinsically disordered protein regions (IDPRs), which contribute to increasing the functional diversity of proteins. Thus we tried to explore the complicated DNA demethylation in pre-implantation embryos from the intrinsic disorder perspective. These five biological macromolecules all have DNA demethylation-related functional domains. They can work together to fulfill DNA demethylation in pre-implantation embryos through complex protein-protein interaction networks. Intrinsic disorder analysis results showed these proteins were partial intrinsically disordered proteins. Many identifiable disorder-based DNA-binding sites, protein-binding sites and post-translational modification sites located in the intrinsically disordered regions, and DNA demethylation deficiency point mutations in the IDPRs could significantly change the local disorder propensity of these proteins. To the best of our knowledge, this work provides a new viewpoint for studying the mechanism of DNA methylation reprogramming during mammalian pre-implantation embryonic development.