Use of Mechanistic Models to Integrate and Analyze Multiple Proteomic Datasets

Proteins in cell signaling networks tend to interact promiscuously through low-affinity interactions. Consequently, evaluating the physiological importance of mapped interactions can be difficult. Attempts to do so have tended to focus on single, measurable physicochemical factors, such as affinity or abundance. For example, interaction importance has been assessed on the basis of the relative affinities of binding partners for a protein of interest, such as a receptor. However, multiple factors can be expected to simultaneously influence the recruitment of proteins to a receptor (and the potential of these proteins to contribute to receptor signaling), including affinity, abundance, and competition, which is a network property. Here, we demonstrate that measurements of protein copy numbers and binding affinities can be integrated within the framework of a mechanistic, computational model that accounts for mass action and competition. We use cell line-specific models to rank the relative importance of protein-protein interactions in the epidermal growth factor receptor (EGFR) signaling network for 11 different cell lines. Each model accounts for experimentally characterized interactions of six autophosphorylation sites in EGFR with proteins containing a Src homology 2 and/or phosphotyrosine-binding domain. We measure importance as the predicted maximal extent of recruitment of a protein to EGFR following ligand-stimulated activation of EGFR signaling. We find that interactions ranked highly by this metric include experimentally detected interactions. Proteins with high importance rank in multiple cell lines include proteins with recognized, well-characterized roles in EGFR signaling, such as GRB2 and SHC1, as well as a protein with a less well-defined role, YES1. Our results reveal potential cell line-specific differences in recruitment.     

Flexible nets. The roles of intrinsic disorder in protein interaction networks

Proteins participate in complex sets of interactions that represent the mechanistic foundation for much of the physiology and function of the cell. These protein-protein interactions are organized into exquisitely complex networks. The architecture of protein-protein interaction networks was recently proposed to be scale-free, with most of the proteins having only one or two connections but with relatively fewer 'hubs' possessing tens, hundreds or more links. The high level of hub connectivity must somehow be reflected in protein structure. What structural quality of hub proteins enables them to interact with large numbers of diverse targets? One possibility would be to employ binding regions that have the ability to bind multiple, structurally diverse partners. This trait can be imparted by the incorporation of intrinsic disorder in one or both partners. To illustrate the value of such contributions, this review examines the roles of intrinsic disorder in protein network architecture. We show that there are three general ways that intrinsic disorder can contribute: First, intrinsic disorder can serve as the structural basis for hub protein promiscuity; secondly, intrinsically disordered proteins can bind to structured hub proteins; and thirdly, intrinsic disorder can provide flexible linkers between functional domains with the linkers enabling mechanisms that facilitate binding diversity. An important research direction will be to determine what fraction of protein-protein interaction in regulatory networks relies on intrinsic disorder.     

Hidden partners: Using cross‐docking calculations to predict binding sites for proteins with multiple interactions

Protein‐protein interactions control a large range of biological processes and their identification is essential to understand the underlying biological mechanisms. To complement experimental approaches, in silico methods are available to investigate protein‐protein interactions. Cross‐docking methods, in particular, can be used to predict protein binding sites. However, proteins can interact with numerous partners and can present multiple binding sites on their surface, which may alter the binding site prediction quality. We evaluate the binding site predictions obtained using complete cross‐docking simulations of 358 proteins with 2 different scoring schemes accounting for multiple binding sites. Despite overall good binding site prediction performances, 68 cases were still associated with very low prediction quality, presenting individual area under the specificity‐sensitivity ROC curve (AUC) values below the random AUC threshold of 0.5, since cross‐docking calculations can lead to the identification of alternate protein binding sites (that are different from the reference experimental sites). For the large majority of these proteins, we show that the predicted alternate binding sites correspond to interaction sites with hidden partners, that is, partners not included in the original cross‐docking dataset. Among those new partners, we find proteins, but also nucleic acid molecules. Finally, for proteins with multiple binding sites on their surface, we investigated the structural determinants associated with the binding sites the most targeted by the docking partners.     

Matrix models for quantifying competitive intransitivity from species abundance data

In a network of competing species, a competitive intransitivity occurs when the ranking of competitive abilities does not follow a linear hierarchy (A > B > C but C > A). A variety of mathematical models suggests that intransitive networks can prevent or slow down competitive exclusion and maintain biodiversity by enhancing species coexistence. However, it has been difficult to assess empirically the relative importance of intransitive competition because a large number of pairwise species competition experiments are needed to construct a competition matrix that is used to parameterize existing models. Here we introduce a statistical framework for evaluating the contribution of intransitivity to community structure using species abundance matrices that are commonly generated from replicated sampling of species assemblages. We provide metrics and analytical methods for using abundance matrices to estimate species competition and patch transition matrices by using reverse‐engineering and a colonization–competition model. These matrices provide complementary metrics to estimate the degree of intransitivity in the competition network of the sampled communities. Benchmark tests reveal that the proposed methods could successfully detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. To illustrate the approach, we analyzed patterns of abundance and biomass of five species of necrophagous Diptera and eight species of their hymenopteran parasitoids that co‐occur in beech forests in Germany. We found evidence for a strong competitive hierarchy within communities of flies and parasitoids. However, for parasitoids, there was a tendency towards increasing intransitivity in higher weight classes, which represented larger resource patches. These tests provide novel methods for empirically estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to experimental measures of pairwise species interactions, as well as to spatio‐temporal samples of assemblages in homogenous environments or environmental gradients.     

Bim, Bad and Bmf: intrinsically unstructured BH3-only proteins that undergo a localized conformational change upon binding to prosurvival Bcl-2 targets

All BH3-only proteins, key initiators of programmed cell death, interact tightly with multiple binding partners and have sequences of low complexity, properties that are the hallmark of intrinsically unstructured proteins (IUPs). We show, using spectroscopic methods, that the BH3-only proteins Bim, Bad and Bmf are unstructured in the absence of binding partners. Detailed sequence analyses are consistent with this observation and suggest that most BH3-only proteins are unstructured. When Bim binds and inactivates prosurvival proteins, most residues remain disordered, only the BH3 element becomes structured, and the short alpha-helical molecular recognition element can be considered to behave as a 'bead on a string'. Coupled folding and binding is typical of many IUPs that have important signaling roles, such as BH3-only proteins, as the inherent structural plasticity favors interaction with multiple targets. This understanding offers promise for the development of BH3 mimetics, as multiple modes of binding are tolerated.     

Four-dimensional visualisation and analysis of protein-protein interaction networks

Protein-protein interaction networks are typically built with interactions collated from many experiments. These networks are thus composite and show all interactions that are currently known to occur in a cell. However, these representations are static and ignore the constant changes in protein-protein interactions. Here we present software for the generation and analysis of dynamic, four-dimensional (4-D) protein interaction networks. In this, time-course-derived abundance data are mapped onto three-dimensional networks to generate network movies. These networks can be navigated, manipulated and queried in real time. Two types of dynamic networks can be generated: a 4-D network that maps expression data onto protein nodes and one that employs 'real-time rendering' by which protein nodes and their interactions appear and disappear in association with temporal changes in expression data. We illustrate the utility of this software by the analysis of singlish interface date hub interactions during the yeast cell cycle. In this, we show that proteins MLC1 and YPT52 show strict temporal control of when their interaction partners are expressed. Since these proteins have one and two interaction interfaces, respectively, it suggests that temporal control of gene expression may be used to limit competition at the interaction interfaces of some hub proteins. The software and movies of the 4-D networks are available at http://www.systemsbiology.org.au/downloads_geomi.html.     

Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process.     

Dynamic Hubs Show Competitive and Static Hubs Non-Competitive Regulation of Their Interaction Partners

Date hub proteins have 1 or 2 interaction interfaces but many interaction partners. This raises the question of whether all partner proteins compete for the interaction interface of the hub or if the cell carefully regulates aspects of this process? Here, we have used real-time rendering of protein interaction networks to analyse the interactions of all the 1 or 2 interface hubs of Saccharomyces cerevisiae during the cell cycle. By integrating previously determined structural and gene expression data, and visually hiding the nodes (proteins) and their edges (interactions) during their troughs of expression, we predict when interactions of hubs and their partners are likely to exist. This revealed that 20 out of all 36 one- or two- interface hubs in the yeast interactome fell within two main groups. The first was dynamic hubs with static partners, which can be considered as ‘competitive hubs’. Their interaction partners will compete for the interaction interface of the hub and the success of any interaction will be dictated by the kinetics of interaction (abundance and affinity) and subcellular localisation. The second was static hubs with dynamic partners, which we term ‘non-competitive hubs’. Regulatory mechanisms are finely tuned to lessen the presence and/or effects of competition between the interaction partners of the hub. It is possible that these regulatory processes may also be used by the cell for the regulation of other, non-cell cycle processes.     

Analysis of Molecular Recognition Features (MoRFs) in membrane proteins

Molecular Recognition Features (MoRFs) are defined as short, intrinsically disordered regions in proteins that undergo disorder-to-order transition upon binding to their partners. As their name suggests, they are implicated in molecular recognition, which serves as the initial step for protein–protein interactions. Membrane proteins constitute approximately 30% of fully sequenced proteomes and are responsible for a wide variety of cellular functions. The aim of the current study was to identify and analyze MoRFs in membrane proteins. Two datasets of MoRFs, transmembrane and peripheral membrane protein MoRFs, were constructed from the Protein Data Bank, and sequence, structural and functional analysis was performed. Characterization of our datasets revealed their unique compositional biases and membrane protein MoRFs were categorized depending on their secondary structure after the interaction with their partners. Moreover, the position of transmembrane protein MoRFs in relation with the protein's topology was determined. Further studies were focused on functional analyses of MoRF-containing proteins and MoRFs' partners, associating them with protein binding, regulation and cell signaling, indicating half of them as putative hubs in protein–protein interaction networks. In conclusion, we provide insights into the disorder-based protein–protein interactions involving membrane proteins.     

AKAP79/150 interacts with the neuronal calcium-binding protein caldendrin

The A kinase-anchoring protein AKAP79/150 is a postsynaptic scaffold molecule and a key regulator of signaling events. At the postsynapse it coordinates phosphorylation and dephosphorylation of receptors via anchoring kinases and phosphatases near their substrates. Interactions between AKAP79 and two Ca(2+) -binding proteins caldendrin and calmodulin have been investigated here. Calmodulin is a known interaction partner of AKAP79/150 that has been shown to regulate activity of the kinase PKC in a Ca(2+) -dependent manner. Pull-down experiments and surface plasmon resonance biosensor analyses have been used here to demonstrate that AKAP79 can also interact with caldendrin, a neuronal calcium-binding protein implicated in regulation of Ca(2+) -influx and release. We demonstrate that calmodulin and caldendrin compete for a partially overlapping binding site on AKAP79 and that their binding is differentially dependent on calcium. Therefore, this competition is regulated by calcium levels. Moreover, both proteins have different binding characteristics suggesting that the two proteins might play complementary roles. The postsynaptic enrichment, the complex binding mechanism, and the competition with calmodulin, makes caldendrin an interesting novel player in the signaling toolkit of the AKAP interactome.     

Molecular Recognition Features in Zika Virus Proteome

Viruses have compact genomes that encode limited number of proteins in comparison to other biological entities. Interestingly, viral proteins have shown natural abundance of either completely disordered proteins that are recognized as intrinsically disorder proteins (IDPs) or partially disordered segments known as intrinsically disordered protein regions (IDPRs). IDPRs are involved in interactions with multiple binding partners to accomplish signaling, regulation, and control functions in cells. Tuning of IDPs and IDPRs are mediated through post-translational modification and alternative splicing. Often, the interactions of IDPRs with their binding protein partner(s) lead to transition from the state of disorder to ordered form. Such interaction-prone protein IDPRs are identified as molecular recognition features (MoRFs). Molecular recognition is an important initial step for the biomolecular interactions and their functional proceedings. Although previous studies have established occurrence of the IDPRs in Zika virus proteome, which provide the functional diversity and structural plasticity to viral proteins, the MoRF analysis has not been performed as of yet. Many computational methods have been developed for the identification of the MoRFs in protein sequences including ANCHOR, MoRFpred, DISOPRED3, and MoRFchibi_web server. In the current study, we have investigated the presence of MoRF regions in structural and non-structural proteins of Zika virus using an aforementioned set of computational techniques. Furthermore, we have experimentally validated the intrinsic disorderness of NS2B cofactor region of NS2B–NS3 protease. NS2B has one of the longest MoRF regions in Zika virus proteome. In future, this study may provide valuable information while investigating the virus host protein interaction networks.     

Disorder and sequence repeats in hub proteins and their implications for network evolution

Protein interaction networks display approximate scale-free topology, in which hub proteins that interact with a large number of other proteins determine the overall organization of the network. In this study, we aim to determine whether hubs are distinguishable from other networked proteins by specific sequence features. Proteins of different connectednesses were compared in the interaction networks of Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, and Homo sapienswith respect to the distribution of predicted structural disorder, sequence repeats, low complexity regions, and chain length. Highly connected proteins ("hub proteins") contained significantly more of, and greater proportion of, these sequence features and tended to be longer overall as compared to less connected proteins. These sequence features provide two different functional means for realizing multiple interactions: (1) extended interaction surface and (2) flexibility and adaptability, providing a mechanism for the same region to bind distinct partners. Our view contradicts the prevailing view that scaling in protein interactomes arose from gene duplication and preferential attachment of equivalent proteins. We propose an alternative evolutionary network specialization process, in which certain components of the protein interactome improved their fitness for binding by becoming longer or accruing regions of disorder and/or internal repeats and have therefore become specialized in network organization.     

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.     

The C terminus of tubulin, a versatile partner for cationic molecules: binding of Tau, polyamines, and calcium

The C-terminal region of tubulin is involved in multiple aspects of the regulation of microtubule assembly. To elucidate the molecular mechanisms of this regulation, we study here, using different approaches, the interaction of Tau, spermine, and calcium, three representative partners of the tubulin C-terminal region, with a peptide composed of the last 42 residues of α1a-tubulin. The results show that their binding involves overlapping amino acid stretches in the C-terminal tubulin region: amino acid residues 421-441 for Tau, 430-432 and 444-451 for spermine, and 421-443 for calcium. Isothermal titration calorimetry, NMR, and cosedimentation experiments show that Tau and spermine have similar micromolar binding affinities, whereas their binding stoichiometry differs (C-terminal tubulin peptide/spermine stoichiometry 1:2, and C-terminal tubulin peptide/Tau stoichiometry 8:1). Interestingly, calcium, known as a negative regulator of microtubule assembly, can compete with the binding of Tau and spermine with the C-terminal domain of tubulin and with the positive effect of these two partners on microtubule assembly in vitro. This observation opens up the possibility that calcium may participate in the regulation of microtubule assembly in vivo through direct (still unknown) or indirect mechanism (displacement of microtubule partners). The functional importance of this part of tubulin was also underlined by the observation that an α-tubulin mutant deleted from the last 23 amino acid residues does not incorporate properly into the microtubule network of HeLa cells. Together, these results provide a structural basis for a better understanding of the complex interactions and putative competition of tubulin cationic partners with the C-terminal region of tubulin.     

Inhibition of protein interactions with the beta 2 sliding clamp of Escherichia coli DNA polymerase III by peptides from beta 2-binding proteins

The sliding clamp of the Escherichia coli replisome is now understood to interact with many proteins involved in DNA synthesis and repair. A universal interaction motif is proposed to be one mechanism by which those proteins bind the E. coli sliding clamp, a homodimer of the beta subunit, at a single site on the dimer. The numerous beta(2)-binding proteins have various versions of the consensus interaction motif, including a related hexameric sequence. To determine if the variants of the motif could contribute to the competition of the beta-binding proteins for the beta(2) site, synthetic peptides derived from the putative beta(2)-binding motifs were assessed for their abilities to inhibit protein-beta(2) interactions, to bind directly to beta(2), and to inhibit DNA synthesis in vitro. A hierarchy emerged, which was consistent with sequence similarity to the pentameric consensus motif, QL(S/D)LF, and peptides containing proposed hexameric motifs were shown to have activities comparable to those containing the consensus sequence. The hierarchy of peptide binding may be indicative of a competitive hierarchy for the binding of proteins to beta(2) in various stages or circumstances of DNA replication and repair.     

The multiple‐specificity landscape of modular peptide recognition domains

Modular protein interaction domains form the building blocks of eukaryotic signaling pathways. Many of them, known as peptide recognition domains, mediate protein interactions by recognizing short, linear amino acid stretches on the surface of their cognate partners with high specificity. Residues in these stretches are usually assumed to contribute independently to binding, which has led to a simplified understanding of protein interactions. Conversely, we observe in large binding peptide data sets that different residue positions display highly significant correlations for many domains in three distinct families (PDZ, SH3 and WW). These correlation patterns reveal a widespread occurrence of multiple binding specificities and give novel structural insights into protein interactions. For example, we predict a new binding mode of PDZ domains and structurally rationalize it for DLG1 PDZ1. We show that multiple specificity more accurately predicts protein interactions and experimentally validate some of the predictions for the human proteins DLG1 and SCRIB. Overall, our results reveal a rich specificity landscape in peptide recognition domains, suggesting new ways of encoding specificity in protein interaction networks.     

Chemical shift assignments of the C-terminal Eps15 homology domain-3 EH domain

The C-terminal Eps15 homology (EH) domain 3 (EHD3) belongs to a eukaryotic family of endocytic regulatory proteins and is involved in the recycling of various receptors from the early endosome to the endocytic recycling compartment or in retrograde transport from the endosomes to the Golgi. EH domains are highly conserved in the EHD family and function as protein-protein interaction units that bind to Asn-Pro-Phe (NPF) motif-containing proteins. The EH domain of EHD1 was the first C-terminal EH domain from the EHD family to be solved by NMR. The differences observed between this domain and proteins with N-terminal EH domains helped describe a mechanism for the differential binding of NPF-containing proteins. Here, structural studies were expanded to include the EHD3 EH domain. While the EHD1 and EHD3 EH domains are highly homologous, they have different protein partners. A comparison of these structures will help determine the selectivity in protein binding between the EHD family members and lead to a better understanding of their unique roles in endocytic regulation.     

Association of Multiple Phosphorylated Proteins with the 14-3-3 Regulatory Hubs: Problems and Perspectives

14-3-3 proteins are well-known universal regulators binding a vast number of partners by recognizing their phosphorylated motifs, typically located within the intrinsically disordered regions. The abundance of such phosphomotifs ensures the involvement of 14-3-3 proteins in sophisticated protein–protein interaction networks that govern vital cellular processes. Thousands of 14-3-3 partners have been either experimentally identified or predicted, but the spatiotemporal hierarchy of the processes based on 14-3-3 interactions is not clearly understood. This is exacerbated by the lack of available structural information on full regulatory complexes involving 14-3-3, which resist high-resolution structural studies due to the presence of intrinsically disordered regions. Although deducing three-dimensional structures is of particular urgency, structural advances are lagging behind the rate at which novel 14-3-3 partners are discovered. Here I attempted to critically review the current state of the field and in particular to dissect the unknowns, focusing on questions that could help in moving the frontiers forward.     

Structural changes in the carboxyl terminus of the gap junction protein connexin43 indicates signaling between binding domains for c-Src and zonula occludens-1

Regulation of cell-cell communication by the gap junction protein connexin43 can be modulated by a variety of connexin-associating proteins. In particular, c-Src can disrupt the connexin43 (Cx43)-zonula occludens-1 (ZO-1) interaction, leading to down-regulation of gap junction intercellular communication. The binding sites for ZO-1 and c-Src correspond to widely separated Cx43 domains (approximately 100 residues apart); however, little is known about the structural modifications that may allow information to be transferred over this distance. Here, we have characterized the structure of the connexin43 carboxyl-terminal domain (Cx43CT) to assess its ability to interact with domains from ZO-1 and c-Src. NMR data indicate that the Cx43CT exists primarily as an elongated random coil, with two regions of alpha-helical structure. NMR titration experiments determined that the ZO-1 PDZ-2 domain affected the last 19 Cx43CT residues, a region larger than that reported to be required for Cx43CT-ZO-1 binding. The c-Src SH3 domain affected Cx43CT residues Lys-264-Lys-287, Ser-306-Glu-316, His-331-Phe-337, Leu-356-Val-359, and Ala-367-Ser-372. Only region Lys-264-Lys-287 contains the residues previously reported to act as an SH3 binding domain. The specificity of these interactions was verified by peptide competition experiments. Finally, we demonstrated that the SH3 domain could partially displace the Cx43CT-PDZ-2 complex. These studies represent the first structural characterization of a connexin domain when integrated in a multimolecular complex. Furthermore, we demonstrate that the structural characteristics of a disordered Cx43CT are advantageous for signaling between different binding partners that may be important in describing the mechanism of channel closure or internalization in response to pathophysiological stimuli.