Role of intrinsic disorder in transient interactions of hub proteins

Intrinsic disorder and protein multibinding in domain, terminal, and linker regions

Intrinsic disorder is believed to contribute to the ability of some proteins to interact with multiple partners which is important for protein functional promiscuity and regulation of the cross-talk between pathways. To better understand the mechanisms of molecular recognition through disordered regions, here, we systematically investigate the coupling between disorder and binding within domain families in a structure interaction network and in terminal and inter-domain linker regions. We showed that the canonical domain-domain interaction model should take into account contributions of N- and C-termini and inter-domain linkers, which may form all or part of the binding interfaces. For the majority of proteins, binding interfaces on domain and terminal regions were predicted to be less disordered than non-interface regions. Analysis of all domain families revealed several exceptions, such as kinases, DNA/RNA binding proteins, certain enzymes, and regulatory proteins, which are candidates for disorder-to-order transitions that can occur upon binding. Domain interfaces that bind single or multiple partners do not exhibit significant difference in disorder content if normalized by the number of interactions. In general, protein families with more diverse interactions exhibit less average disorder over all members of the family. Our results shed light on recent controversies regarding the relationship between disorder and binding of multiple partners at common interfaces. In particular, they support the hypothesis that protein domains with many interacting partners should have a pleiotropic effect on functional pathways and consequently might be more constrained in evolution.

Understanding protein non-folding

This review describes the family of intrinsically disordered proteins, members of which fail to form rigid 3-D structures under physiological conditions, either along their entire lengths or only in localized regions. Instead, these intriguing proteins/regions exist as dynamic ensembles within which atom positions and backbone Ramachandran angles exhibit extreme temporal fluctuations without specific equilibrium values. Many of these intrinsically disordered proteins are known to carry out important biological functions which, in fact, depend on the absence of a specific 3-D structure. The existence of such proteins does not fit the prevailing structure-function paradigm, which states that a unique 3-D structure is a prerequisite to function. Thus, the protein structure-function paradigm has to be expanded to include intrinsically disordered proteins and alternative relationships among protein sequence, structure, and function. This shift in the paradigm represents a major breakthrough for biochemistry, biophysics and molecular biology, as it opens new levels of understanding with regard to the complex life of proteins. This review will try to answer the following questions: how were intrinsically disordered proteins discovered? Why don't these proteins fold? What is so special about intrinsic disorder? What are the functional advantages of disordered proteins/regions? What is the functional repertoire of these proteins? What are the relationships between intrinsically disordered proteins and human diseases?

Hub promiscuity in protein-protein interaction networks

Hubs are proteins with a large number of interactions in a protein-protein interaction network. They are the principal agents in the interaction network and affect its function and stability. Their specific recognition of many different protein partners is of great interest from the structural viewpoint. Over the last few years, the structural properties of hubs have been extensively studied. We review the currently known features that are particular to hubs, possibly affecting their binding ability. Specifically, we look at the levels of intrinsic disorder, surface charge and domain distribution in hubs, as compared to non-hubs, along with differences in their functional domains.

Modularity of intrinsic disorder in the human proteome

Predicting regions of disorder has become of increasing interest when determining protein structure and function. With approximately 33% of eukaryotic proteins having significant disordered regions, and an increasing occurrence of disorder in higher organisms, an analysis of the importance of disorder from an evolutionary perspective was clearly warranted. Focusing on the human proteome, we have studied how abundant disorder is and its relevance to protein function and structure. We have shown that disordered regions frequently appear to be independent functional units, and judged by complete association to certain protein domains, may be evolutionarily conserved. Our work also supports previous analyses on association between disorder and alternate splicing and provides support for the modularity of disorder by showing that with respect to splicing events, disordered regions frequently appear to be spliced as whole units.

A comprehensive resource of interacting protein regions for refining human transcription factor networks

Large-scale data sets of protein-protein interactions (PPIs) are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in this study also include the sequences involved in the interactions (i.e., the interacting regions, IRs) suggested to correspond to functional and structural domains. Here we present the first large-scale IR data set obtained using mRNA display for 50 human transcription factors (TFs), including 12 transcription-related proteins. The core data set (966 IRs; 943 PPIs) displays a verification rate of 70%. Analysis of the IR data set revealed the existence of IRs that interact with multiple partners. Furthermore, these IRs were preferentially associated with intrinsic disorder. This finding supports the hypothesis that intrinsically disordered regions play a major role in the dynamics and diversity of TF networks through their ability to structurally adapt to and bind with multiple partners. Accordingly, this domain-based interaction resource represents an important step in refining protein interactions and networks at the domain level and in associating network analysis with biological structure and function.

Bayesian statistical modelling of human protein interaction network incorporating protein disorder information

BACKGROUND

We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive approaches. The model is capable to capture generic and structural properties of a network as emergent from local interdependencies and uses a limited number of parameters. Here, we consider one global parameter capturing the density of edges in the network, and local parameters representing each node's contribution to the formation of edges in the network. The modelling suggests a novel definition of important nodes in the network, namely social, as revealed based on the local sociality parameters of the model. Moreover, the sociality parameters help to reveal organizational principles of the network. An inherent advantage of our approach is the possibility of hypotheses testing: a priori knowledge about biological properties of the nodes can be incorporated into the statistical model to investigate its influence on the structure of the network.

RESULTS

We applied the statistical modelling to the human protein interaction network obtained with Y2H experiments. Bayesian approach for the estimation of the parameters was employed. We deduced social proteins, essential for the formation of the network, while incorporating into the model information on protein disorder. Intrinsically disordered are proteins which lack a well-defined three-dimensional structure under physiological conditions. We predicted the fold group (ordered or disordered) of proteins in the network from their primary sequences. The network analysis indicated that protein disorder has a positive effect on the connectivity of proteins in the network, but do not fully explains the interactivity.

CONCLUSIONS

The approach opens a perspective to study effects of biological properties of individual entities on the structure of biological networks.

Regulation of chromatin structure and function by HMGN proteins

High mobility group nucleosome-binding (HMGN) proteins are architectural non-histone chromosomal proteins that bind to nucleosomes and modulate the structure and function of chromatin. The interaction of HMGN proteins with nucleosomes is dynamic and the proteins compete with the linker histone H1 chromatin-binding sites. HMGNs reduce the H1-mediated compaction of the chromatin fiber and facilitate the targeting of regulatory factors to chromatin. They modulate the cellular epigenetic profile, affect gene expression and impact the biological processes such as development and the cellular response to environmental and hormonal signals. Here we review the role of HMGN in chromatin structure, the link between HMGN proteins and histone modifications, and discuss the consequence of this link on nuclear processes and cellular phenotype.

The importance of being flexible: the case of basic region leucine zipper transcriptional regulators

Large volumes of protein sequence and structure data acquired by proteomic studies led to the development of computational bioinformatic techniques that made possible the functional annotation and structural characterization of proteins based on their primary structure. It has become evident from genome-wide analyses that many proteins in eukaryotic cells are either completely disordered or contain long unstructured regions that are crucial for their biological functions. The content of disorder increases with evolution indicating a possibly important role of disorder in the regulation of cellular systems. Transcription factors are no exception and several proteins of this class have recently been characterized as premolten/molten globules. Yet, mammalian cells rely on these proteins to control expression of their 30,000 or so genes. Basic region:leucine zipper (bZIP) DNA-binding proteins constitute a major class of eukaryotic transcriptional regulators. This review discusses how conformational flexibility "built" into the amino acid sequence allows bZIP proteins to interact with a large number of diverse molecular partners and to accomplish their manifold cellular tasks in a strictly regulated and coordinated manner.

Unfoldomics of human diseases: linking protein intrinsic disorder with diseases

BACKGROUND

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) lack stable tertiary and/or secondary structure yet fulfills key biological functions. The recent recognition of IDPs and IDRs is leading to an entire field aimed at their systematic structural characterization and at determination of their mechanisms of action. Bioinformatics studies showed that IDPs and IDRs are highly abundant in different proteomes and carry out mostly regulatory functions related to molecular recognition and signal transduction. These activities complement the functions of structured proteins. IDPs and IDRs were shown to participate in both one-to-many and many-to-one signaling. Alternative splicing and posttranslational modifications are frequently used to tune the IDP functionality. Several individual IDPs were shown to be associated with human diseases, such as cancer, cardiovascular disease, amyloidoses, diabetes, neurodegenerative diseases, and others. This raises questions regarding the involvement of IDPs and IDRs in various diseases.

RESULTS

IDPs and IDRs were shown to be highly abundant in proteins associated with various human maladies. As the number of IDPs related to various diseases was found to be very large, the concepts of the disease-related unfoldome and unfoldomics were introduced. Novel bioinformatics tools were proposed to populate and characterize the disease-associated unfoldome. Structural characterization of the members of the disease-related unfoldome requires specialized experimental approaches. IDPs possess a number of unique structural and functional features that determine their broad involvement into the pathogenesis of various diseases.

CONCLUSION

Proteins associated with various human diseases are enriched in intrinsic disorder. These disease-associated IDPs and IDRs are real, abundant, diversified, vital, and dynamic. These proteins and regions comprise the disease-related unfoldome, which covers a significant part of the human proteome. Profound association between intrinsic disorder and various human diseases is determined by a set of unique structural and functional characteristics of IDPs and IDRs. Unfoldomics of human diseases utilizes unrivaled bioinformatics and experimental techniques, paves the road for better understanding of human diseases, their pathogenesis and molecular mechanisms, and helps develop new strategies for the analysis of disease-related proteins.

Rich can get poor: conversion of hub to non-hub proteins

Hubs are ubiquitous network elements with high connectivity. One of the common observations about hub proteins is their preferential attachment leading to scale-free network topology. Here we examine the question: does rich protein always get richer, or can it get poor too? To answer this question, we compared similar and well-annotated hub proteins in six organisms, from prokaryotes to eukaryotes. Our findings indicate that hub proteins retain, gain or lose connectivity based on the context. Furthermore, the loss or gain of connectivity appears to correlate with the functional role of the protein in a given system.

Identification and functional analysis of RNase E of Vibrio angustum S14 and two-hybrid analysis of its interaction partners

RNase E is an essential enzyme that catalyses RNA processing. Microdomains which mediate interactions between RNase E and other members of the degradosome have been defined. To further elucidate the role of these microdomains in molecular interactions, we studied RNase E from Vibrio angustum S14. Protein sequence analysis revealed that its C-terminal half is less conserved and structured than its N-terminal half. Within this structural disorder, however, exist five small regions of predicted structural propensity. Four are similar to interaction-mediating microdomains identified in other RNase E proteins; the fifth did not correspond to any known functional motif. The function of the V. angustum S14 enolase-binding microdomain was confirmed using bacterial two-hybrid analysis, demonstrating the conserved function of this microdomain for the first time in a species other than Escherichia coli. Further, PNPase in V. angustum S14 was shown to interact with the last 80 amino acids of the C-terminal region of RNase E. This raises the possibility that PNPase interacts with the small ordered region at residues 1026-1041. The role of RNase E as a hub protein and the implications of microdomain-mediated interactions in relation to specificity and function are discussed.

Intrinsic disorder explains diverse nuclear roles of chromatin remodeling proteins

Chromatin remodelers, a group of proteins involved in nucleosome re-positioning and modification, have extensive range of interacting partners. They form multimeric complexes and interact with modified histones, transcription, splicing, and replication factors, DNA, RNA, and the factors related to the maintenance of chromosome structure. Such diverse range of interactions is hard to explain with the presumed highly structured form of the protein. In the current analysis, the conformations of chromatin remodelers were explored using protein disorder prediction algorithms. The study revealed that a significant proportion (p < 2.2e-16) of these proteins harbor at least one long region of intrinsic disorder (>70 aa). These unstructured regions do not exhibit any preference to the N/C terminal or middle of the protein. They do not show any significant representation in the Protein Data Bank (PDB) structure repository. Limited examples from PDB indicate direct involvement of disordered regions in binding of chromatin remodeling proteins to naked or modified DNA, histones, and other chromatin-related factors. Furthermore, intrinsic disorder seen in these proteins correlates to the presence of low sequence complexity regions (p = 1.851e-10) particularly the tandem repeats of hydrophilic and charged amino acids. This probably hints at their evolutionary origin via repeat expansion. The disordered regions may enable these proteins to reversibly bind to various interacting partners and eventually contribute to functional diversity and specialization of chromatin remodeling complexes. These could also endow combinatorial action of multiple domains within a protein. We further discuss the prominent association of intrinsic disorder with other chromatin-related proteins and its functional relevance therein.

Improved disorder prediction by combination of orthogonal approaches

Disordered proteins are highly abundant in regulatory processes such as transcription and cell-signaling. Different methods have been developed to predict protein disorder often focusing on different types of disordered regions. Here, we present MD, a novel META-Disorder prediction method that molds various sources of information predominantly obtained from orthogonal prediction methods, to significantly improve in performance over its constituents. In sustained cross-validation, MD not only outperforms its origins, but it also compares favorably to other state-of-the-art prediction methods in a variety of tests that we applied. Availability: http://www.rostlab.org/services/md/

Quantitative assessment of the structural bias in protein-protein interaction assays

With recent publications of several large-scale protein-protein interaction (PPI) studies, the realization of the full yeast interaction network is getting closer. Here, we have analysed several yeast protein interaction datasets to understand their strengths and weaknesses. In particular, we investigate the effect of experimental biases on some of the protein properties suggested to be enriched in highly connected proteins. Finally, we use support vector machines (SVM) to assess the contribution of these properties to protein interactivity. We find that protein abundance is the most important factor for detecting interactions in tandem affinity purifications (TAP), while it is of less importance for Yeast Two Hybrid (Y2H) screens. Consequently, sequence conservation and/or essentiality of hubs may be related to their high abundance. Further, proteins with disordered structure are over-represented in Y2H screens and in one, but not the other, large-scale TAP assay. Hence, disordered regions may be important both in transient interactions and interactions in complexes. Finally, a few domain families seem to be responsible for a large part of all interactions. Most importantly, we show that there are method-specific biases in PPI experiments. Thus, care should be taken before drawing strong conclusions based on a single dataset.

Exploring the evolutionary rate differences of party hub and date hub proteins in Saccharomyces cerevisiae protein-protein interaction network

Evolutionary rates of party hub and date hub proteins of Saccharomyces cerevisiae are analyzed under the perspective of ordered/disordered ness of proteins and the three dimensional structural context such as the solvent accessibility of the amino acid residues. Our results suggest that the lowering of evolutionary rate of the party hub proteins than the date hub proteins is solely contributed by the ordered regions of the corresponding proteins. Moreover the slower evolutionary rate of the party hub proteins than the date hub counterparts can be attributed to the presence of buried amino acid residues. Thus, our work endeavors further into the understanding of the evolutionary rate differences of the two different types of hub proteins of S. cerevisiae.

Intrinsic disorder in scaffold proteins: getting more from less

Regulation, recognition and cell signaling involve the coordinated actions of many players. Signaling scaffolds, with their ability to bring together proteins belonging to common and/or interlinked pathways, play crucial roles in orchestrating numerous events by coordinating specific interactions among signaling proteins. This review examines the roles of intrinsic disorder (ID) in signaling scaffold protein function. Several well-characterized scaffold proteins with structurally and functionally characterized ID regions are used here to illustrate the importance of ID for scaffolding function. These examples include scaffolds that are mostly disordered, only partially disordered or those in which the ID resides in a scaffold partner. Specific scaffolds discussed include RNase, voltage-activated potassium channels, axin, BRCA1, GSK-3beta, p53, Ste5, titin, Fus3, BRCA1, MAP2, D-AKAP2 and AKAP250. Among the mechanisms discussed are: molecular recognition features, fly-casting, ease of encounter complex formation, structural isolation of partners, modulation of interactions between bound partners, masking of intramolecular interaction sites, maximized interaction surface per residue, toleration of high evolutionary rates, binding site overlap, allosteric modification, palindromic binding, reduced constraints for alternative splicing, efficient regulation via posttranslational modification, efficient regulation via rapid degradation, protection of normally solvent-exposed sites, enhancing the plasticity of interaction and molecular crowding. We conclude that ID can enhance scaffold function by a diverse array of mechanisms. In other words, scaffold proteins utilize several ID-facilitated mechanisms to enhance function, and by doing so, get more functionality from less structure.

The twilight zone between protein order and disorder

The amino acid composition of intrinsically disordered proteins and protein segments characteristically differs from that of ordered proteins. This observation forms the basis of several disorder prediction methods. These, however, usually perform worse for smaller proteins (or segments) than for larger ones. We show that the regions of amino acid composition space corresponding to ordered and disordered proteins overlap with each other, and the extent of the overlap (the "twilight zone") is larger for short than for long chains. To explain this finding, we used two-dimensional lattice model proteins containing hydrophobic, polar, and charged monomers and revealed the relation among chain length, amino acid composition, and disorder. Because the number of chain configurations exponentially grows with chain length, a larger fraction of longer chains can reach a low-energy, ordered state than do shorter chains. The amount of information carried by the amino acid composition about whether a protein or segment is (dis)ordered grows with increasing chain length. Smaller proteins rely more on specific interactions for stability, which limits the possible accuracy of disorder prediction methods. For proteins in the "twilight zone", size can determine order, as illustrated by the example of two-state homodimers.

Sticking together? Falling apart? Exploring the dynamics of the interactome

Advances in techniques for the study of protein-protein interactions have dramatically improved our understanding of the interactome. However, we know little about the dynamics of this complex system. To better understand the dynamics of the interactome, it is important to consider what happens when single proteins are perturbed. Changes in protein abundance and post-translational modification can function as switches in the interactome, affecting protein-complex assembly and function. Changes in protein sequence or a dramatic increase in abundance might cause a promiscuous gain of interactions. These effects are not identical for all proteins and will differ depending on the number and type of interaction partners that a protein has.

The role of disorder in interaction networks: a structural analysis

Recent studies have emphasized the value of including structural information into the topological analysis of protein networks. Here, we utilized structural information to investigate the role of intrinsic disorder in these networks. Hub proteins tend to be more disordered than other proteins (i.e. the proteome average); however, we find this only true for those with one or two binding interfaces (‘single'-interface hubs). In contrast, the distribution of disordered residues in multi-interface hubs is indistinguishable from the overall proteome. Surprisingly, we find that the binding interfaces in single-interface hubs are highly structured, as is the case for multi-interface hubs. However, the binding partners of single-interface hubs tend to have a higher level of disorder than the proteome average, suggesting that their binding promiscuity is related to the disorder of their binding partners. In turn, the higher level of disorder of single-interface hubs can be partly explained by their tendency to bind to each other in a cascade. A good illustration of this trend can be found in signaling pathways and, more specifically, in kinase cascades. Finally, our findings have implications for the current controversy related to party and date-hubs.

Regulation of Escherichia coli SOS mutagenesis by dimeric intrinsically disordered umuD gene products

Products of the umuD gene in Escherichia coli play key roles in coordinating the switch from accurate DNA repair to mutagenic translesion DNA synthesis (TLS) during the SOS response to DNA damage. Homodimeric UmuD(2) is up-regulated 10-fold immediately after damage, after which slow autocleavage removes the N-terminal 24 amino acids of each UmuD. The remaining fragment, UmuD'(2), is required for mutagenic TLS. The small proteins UmuD(2) and UmuD'(2) make a large number of specific protein-protein contacts, including three of the five known E. coli DNA polymerases, parts of the replication machinery, and RecA recombinase. We show that, despite forming stable homodimers, UmuD(2) and UmuD'(2) have circular dichroism (CD) spectra with almost no alpha-helix or beta-sheet signal at physiological concentrations in vitro. High protein concentrations, osmolytic crowding agents, and specific interactions with a partner protein can produce CD spectra that resemble the expected beta-sheet signature. A lack of secondary structure in vitro is characteristic of intrinsically disordered proteins (IDPs), many of which act as regulators. A stable homodimer that lacks significant secondary structure is unusual but not unprecedented. Furthermore, previous single-cysteine cross-linking studies of UmuD(2) and UmuD'(2) show that they have a nonrandom structure at physiologically relevant concentrations in vitro. Our results offer insights into structural characteristics of relatively poorly understood IDPs and provide a model for how the umuD gene products can regulate diverse aspects of the bacterial SOS response.

Intrinsic disorder in yeast transcriptional regulatory network

Intrinsic disorder has been shown to be important in mediating protein-protein and protein-DNA interactions. Proteins involved in regulatory functions are particularly enriched in intrinsic disorder. In this study we explored the role of intrinsic disorder in transcriptional regulatory network of yeast. Using disorder prediction programs we show that transcription factors (TFs) regulating large number of targets (transcriptional hubs) have significantly increased intrinsic disorder, though targets regulated by multiple TFs did not show increased intrinsic disorder. Intrinsic disorder may allow these transcriptional hubs to bind to diverse promoter regions of their targets in different contexts, and may also allow complex regulatory control of transcriptional hubs that are involved in coordinating different cellular processes.

Probabilistic prediction and ranking of human protein-protein interactions

Background

Although the prediction of protein-protein interactions has been extensively investigated for yeast, few such datasets exist for the far larger proteome in human. Furthermore, it has recently been estimated that the overall average false positive rate of available computational and high-throughput experimental interaction datasets is as high as 90%.

Results

The prediction of human protein-protein interactions was investigated by combining orthogonal protein features within a probabilistic framework. The features include co-expression, orthology to known interacting proteins and the full-Bayesian combination of subcellular localization, co-occurrence of domains and post-translational modifications. A novel scoring function for local network topology was also investigated. This topology feature greatly enhanced the predictions and together with the full-Bayes combined features, made the largest contribution to the predictions. Using a conservative threshold, our most accurate predictor identifies 37606 human interactions, 32892 (80%) of which are not present in other publicly available large human interaction datasets, thus substantially increasing the coverage of the human interaction map. A subset of the 32892 novel predicted interactions have been independently validated. Comparison of the prediction dataset to other available human interaction datasets estimates the false positive rate of the new method to be below 80% which is competitive with other methods. Since the new method scores and ranks all human protein pairs, smaller subsets of higher quality can be generated thus leading to even lower false positive prediction rates.

Conclusion

The set of interactions predicted in this work increases the coverage of the human interaction map and will help determine the highest confidence human interactions.