Identification of RNA-protein contacts within functional ribonucleoprotein complexes by RNA site-specific labeling and UV crosslinking

A variety of cellular processes are carried out by highly complex ribonucleoprotein (RNP) particles in which multiple RNA-RNA, RNA-protein, and protein-protein interactions occur. The spliceosome, which executes the nuclear pre-mRNA splicing reaction, is a particularly striking example of a complex RNP, containing a minimum of 50 distinct protein components as well as five small nuclear RNAs. In order to identify which among the numerous proteins may play critical roles in the splicing reaction, we have assembled spliceosomal complexes on pre-mRNA containing a single 32P-labeled nucleotide, isolated the complexes by gel filtration, and then carried out UV crosslinking. The combination of these three methods has allowed the identification of proteins that crosslink to critical sequence elements during each stage in spliceosome assembly. These methods should be generally applicable to the analysis of RNP complexes assembled in vitro.     

Structural interpretation of protein-protein interaction network

Background

Currently a huge amount of protein-protein interaction data is available from high throughput experimental methods. In a large network of protein-protein interactions, groups of proteins can be identified as functional clusters having related functions where a single protein can occur in multiple clusters. However experimental methods are error-prone and thus the interactions in a functional cluster may include false positives or there may be unreported interactions. Therefore correctly identifying a functional cluster of proteins requires the knowledge of whether any two proteins in a cluster interact, whether an interaction can exclude other interactions, or how strong the affinity between two interacting proteins is.

Methods

In the present work the yeast protein-protein interaction network is clustered using a spectral clustering method proposed by us in 2006 and the individual clusters are investigated for functional relationships among the member proteins. 3D structural models of the proteins in one cluster have been built – the protein structures are retrieved from the Protein Data Bank or predicted using a comparative modeling approach. A rigid body protein docking method (Cluspro) is used to predict the protein-protein interaction complexes. Binding sites of the docked complexes are characterized by their buried surface areas in the docked complexes, as a measure of the strength of an interaction.

Results

The clustering method yields functionally coherent clusters. Some of the interactions in a cluster exclude other interactions because of shared binding sites. New interactions among the interacting proteins are uncovered, and thus higher order protein complexes in the cluster are proposed. Also the relative stability of each of the protein complexes in the cluster is reported.

Conclusions

Although the methods used are computationally expensive and require human intervention and judgment, they can identify the interactions that could occur together or ones that are mutually exclusive. In addition indirect interactions through another intermediate protein can be identified. These theoretical predictions might be useful for crystallographers to select targets for the X-ray crystallographic determination of protein complexes.

     

Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions

Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes.     

A method based on local density and random walks for complexes detection in protein interaction networks

In this paper, we present a method based on local density and random walks (LDRW) for core-attachment complexes detection in protein-protein interaction (PPI) networks whether they are weighted or not. Our LDRW method consists of two stages. Firstly, it finds all the protein-complex cores based on local density of subnetwork. Then it uses random walks with restarts for finding the attachment proteins of each detected core to form complexes. We evaluate the effectiveness of our method using two different yeast PPI networks and validate the biological significance of the predicted protein complexes using known complexes in the Munich Information Center for Protein Sequence (MIPS) and Gene Ontology (GO) databases. We also perform a comprehensive comparison between our method and other existing methods. The results show that our method can find more protein complexes with high biological significance and obtains a significant improvement. Furthermore, our method is able to identify biologically significant overlapped protein complexes.     

Physical interactions between tricarboxylic acid cycle enzymes in Bacillus subtilis: evidence for a metabolon

The majority of all proteins of a living cell is active in complexes rather than in an isolated way. These protein-protein interactions are of high relevance for many biological functions. In addition to many well established protein complexes an increasing number of protein-protein interactions, which form rather transient complexes has recently been discovered. The formation of such complexes seems to be a common feature especially for metabolic pathways. In the Gram-positive model organism Bacillus subtilis, we identified a protein complex of three citric acid cycle enzymes. This complex consists of the citrate synthase, the isocitrate dehydrogenase, and the malate dehydrogenase. Moreover, fumarase and aconitase interact with malate dehydrogenase and with each other. These five enzymes catalyze sequential reaction of the TCA cycle. Thus, this interaction might be important for a direct transfer of intermediates of the TCA cycle and thus for elevated metabolic fluxes via substrate channeling. In addition, we discovered a link between the TCA cycle and gluconeogenesis through a flexible interaction of two proteins: the association between the malate dehydrogenase and phosphoenolpyruvate carboxykinase is directly controlled by the metabolic flux. The phosphoenolpyruvate carboxykinase links the TCA cycle with gluconeogenesis and is essential for B. subtilis growing on gluconeogenic carbon sources. Only under gluconeogenic growth conditions an interaction of these two proteins is detectable and disappears under glycolytic growth conditions.     

The Bead blot: a method for identifying ligand-protein and protein-protein interactions using combinatorial libraries of peptide ligands

Small molecules that bind proteins can be used as ligands for protein purification and for investigating protein-protein and protein-drug interactions. Unfortunately, many methods used to identify new ligands to desired proteins suffer from common shortcomings, including the requirement that the target protein be purified and/or the requirement that the ligands be selected under conditions different from those under which it will be used. We have developed a new method called the Bead blot that can (i) select ligands to unpurified proteins, including trace proteins, present in complex materials (e.g., unfractionated plasma); (ii) select ligands to multiple proteins under a variety of conditions in a single experiment; and (iii) be used with libraries of different types of ligands. In the Bead blot, a library of ligands, synthesized on chromatography resin beads, is incubated with a starting material containing a target protein for which a ligand is sought. The proteins in the material bind to their complementary ligands according to specific affinity interactions. Then the protein-loaded beads are immobilized in a porous matrix, and the proteins are directionally eluted from the beads and captured on a membrane superimposed on the beads. The location of the target protein on the membrane is determined, and because the position of the protein(s) on the membrane reflects the position of the bead(s) in the matrix, the bead that originally bound the protein is identified, with subsequent elucidation of the ligand sequence. Ligands to several targets can be identified in one experiment. Here we demonstrate the broad utility of this method by the selection of ligands that purify plasma protein complexes or that remove pathogens from whole blood with very high affinity constants. We also select ligands to a protein based on competitive elution.     

Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions

Cell signaling networks propagate information from extracellular cues via dynamic modulation of protein-protein interactions in a context-dependent manner. Networks based on receptor tyrosine kinases (RTKs), for example, phosphorylate intracellular proteins in response to extracellular ligands, resulting in dynamic protein-protein interactions that drive phenotypic changes. Most commonly used methods for discovering these protein-protein interactions, however, are optimized for detecting stable, longer-lived complexes, rather than the type of transient interactions that are essential components of dynamic signaling networks such as those mediated by RTKs. Substrate phosphorylation downstream of RTK activation modifies substrate activity and induces phospho-specific binding interactions, resulting in the formation of large transient macromolecular signaling complexes. Since protein complex formation should follow the trajectory of events that drive it, we reasoned that mining phosphoproteomic datasets for highly similar dynamic behavior of measured phosphorylation sites on different proteins could be used to predict novel, transient protein-protein interactions that had not been previously identified. We applied this method to explore signaling events downstream of EGFR stimulation. Our computational analysis of robustly co-regulated phosphorylation sites, based on multiple clustering analysis of quantitative time-resolved mass-spectrometry phosphoproteomic data, not only identified known sitewise-specific recruitment of proteins to EGFR, but also predicted novel, a priori interactions. A particularly intriguing prediction of EGFR interaction with the cytoskeleton-associated protein PDLIM1 was verified within cells using co-immunoprecipitation and in situ proximity ligation assays. Our approach thus offers a new way to discover protein-protein interactions in a dynamic context- and phosphorylation site-specific manner.     

Homology modelling of protein-protein complexes: a simple method and its possibilities and limitations

Background  

Structure-based computational methods are needed to help identify and characterize protein-protein complexes and their function. For individual proteins, the most successful technique is homology modelling. We investigate a simple extension of this technique to protein-protein complexes. We consider a large set of complexes of known structures, involving pairs of single-domain proteins. The complexes are compared with each other to establish their sequence and structural similarities and the relation between the two. Compared to earlier studies, a simpler dataset, a simpler structural alignment procedure, and an additional energy criterion are used. Next, we compare the Xray structures to models obtained by threading the native sequence onto other, homologous complexes. An elementary requirement for a successful energy function is to rank the native structure above any threaded structure. We use the DFIRE _β energy function, whose quality and complexity are typical of the models used today. Finally, we compare near-native models to distinctly non-native models.     

Features and applications of blue-native and clear-native electrophoresis

1-D native electrophoresis is used for the separation of individual proteins, protein complexes, and supercomplexes. Stable and labile protein-protein interactions can be identified depending on detergent and buffer conditions. 1-D native gels are immediately applicable for in-gel detection of fluorescent-labeled proteins and for in-gel catalytic activity assays. 1-D native gels and blots are used to determine native mass and oligomeric state of membrane proteins. Protein extracts from 1-D native gels are used for generation of antibodies, for proteomic work, and for advanced structural investigations. 2-D separation of subunits of protein complexes by SDS-PAGE is mostly used for immunological and proteomic studies. Following the discussion of these general features, specific applications of native electrophoresis techniques in various research fields are highlighted: immunological and receptor studies, biogenesis and assembly of membrane protein complexes, protein import into organelles, dynamics of proteasomes, proteome and subproteome investigations, the identification and quantification of mitochondrial alterations in apoptosis, carcinogenesis, and neurodegenerative disorders like Parkinson's disease, Alzheimer's disease, and the vast variety of mitochondrial encephalomyopathies.     

An agarose-acrylamide composite native gel system suitable for separating ultra-large protein complexes

An agarose-acrylamide composite native gel (CNG) system has been developed for separating protein complexes of ultra-large molecular sizes (over 500kDa) and for analyzing protein-protein interactions in their native states. Various native gel conditions were explored and techniques were improved to facilitate the formation and performance of the CNG system. We demonstrate here that the CNG technique is capable of resolving a complex of RNA polymerase II and an associated factor from the free components, which had not been previously achieved with other methods. Furthermore, this CNG electrophoresis can be conveniently coupled to second-dimension sodium dodecyl sulfate-polyacrylamide gel electrophoresis for identification of protein components within discrete complexes separated during the CNG run. The CNG technique is particularly suitable for capturing dynamic protein-protein interactions as exemplified here by the formation and demonstration of RNA polymerase II-Fcp1 complex.     

The role of weak protein-protein interactions in multivalent lectin-carbohydrate binding: crystal structure of cross-linked FRIL

Binding of multivalent glycoconjugates by lectins often leads to the formation of cross-linked complexes. Type I cross-links, which are one-dimensional, are formed by a divalent lectin and a divalent glycoconjugate. Type II cross-links, which are two or three-dimensional, occur when a lectin or glycoconjugate has a valence greater than two. Type II complexes are a source of additional specificity, since homogeneous type II complexes are formed in the presence of mixtures of lectins and glycoconjugates. This additional specificity is thought to become important when a lectin interacts with clusters of glycoconjugates, e.g. as is present on the cell surface. The cryst1al structure of the Glc/Man binding legume lectin FRIL in complex with a trisaccharide provides a molecular snapshot of how weak protein-protein interactions, which are not observed in solution, can become important when a cross-linked complex is formed. In solution, FRIL is a divalent dimer, but in the crystal FRIL forms a tetramer, which allows for the formation of an intricate type II cross-linked complex with the divalent trisaccharide. The dependence on weak protein-protein interactions can ensure that a specific type II cross-linked complex and its associated specificity can occur only under stringent conditions, which explains why lectins are often found forming higher-order oligomers.     

Unraveling the dynamics of protein interactions with quantitative mass spectrometry

Knowledge of structure and dynamics of proteins and protein complexes is important to unveil the molecular basis and mechanisms involved in most biological processes. Protein complex dynamics can be defined as the changes in the composition of a protein complex during a cellular process. Protein dynamics can be defined as conformational changes in a protein during enzyme activation, for example, when a protein binds to a ligand or when a protein binds to another protein. Mass spectrometry (MS) combined with affinity purification has become the analytical tool of choice for mapping protein-protein interaction networks and the recent developments in the quantitative proteomics field has made it possible to identify dynamically interacting proteins. Furthermore, hydrogen/deuterium exchange MS is emerging as a powerful technique to study structure and conformational dynamics of proteins or protein assemblies in solution. Methods have been developed and applied for the identification of transient and/or weak dynamic interaction partners and for the analysis of conformational dynamics of proteins or protein complexes. This review is an overview of existing and recent developments in studying the overall dynamics of in vivo protein interaction networks and protein complexes using MS-based methods.     

Conformational Heterogeneity in Antibody-Protein Antigen Recognition: IMPLICATIONS FOR HIGH AFFINITY PROTEIN COMPLEX FORMATION

Specific, high affinity protein-protein interactions lie at the heart of many essential biological processes, including the recognition of an apparently limitless range of foreign proteins by natural antibodies, which has been exploited to develop therapeutic antibodies. To mediate biological processes, high affinity protein complexes need to form on appropriate, relatively rapid timescales, which presents a challenge for the productive engagement of complexes with large and complex contact surfaces (∼600–1800 Ų). We have obtained comprehensive backbone NMR assignments for two distinct, high affinity antibody fragments (single chain variable and antigen-binding (Fab) fragments), which recognize the structurally diverse cytokines interleukin-1β (IL-1β, β-sheet) and interleukin-6 (IL-6, α-helical). NMR studies have revealed that the hearts of the antigen binding sites in both free anti-IL-1β Fab and anti-IL-6 single chain variable exist in multiple conformations, which interconvert on a timescale comparable with the rates of antibody-antigen complex formation. In addition, we have identified a conserved antigen binding-induced change in the orientation of the two variable domains. The observed conformational heterogeneity and slow dynamics at protein antigen binding sites appears to be a conserved feature of many high affinity protein-protein interfaces structurally characterized by NMR, suggesting an essential role in protein complex formation. We propose that this behavior may reflect a soft capture, protein-protein docking mechanism, facilitating formation of high affinity protein complexes on a timescale consistent with biological processes.     

Rapid identification of protein-protein interfaces for the construction of a complex model based on multiple unassigned signals by using time-sharing NMR measurements

Protein-protein interactions are necessary for various cellular processes, and therefore, information related to protein-protein interactions and structural information of complexes is invaluable. To identify protein-protein interfaces using NMR, resonance assignments are generally necessary to analyze the data; however, they are time consuming to collect, especially for large proteins. In this paper, we present a rapid, effective, and unbiased approach for the identification of a protein-protein interface without resonance assignments. This approach requires only a single set of 2D titration experiments of a single protein sample, labeled with a unique combination of an (15)N-labeled amino acid and several amino acids (13)C-labeled on specific atoms. To rapidly obtain high resolution data, we applied a new pulse sequence for time-shared NMR measurements that allowed simultaneous detection of a ω(1)-TROSY-type backbone (1)H-(15)N and aromatic (1)H-(13)C shift correlations together with single quantum methyl (1)H-(13)C shift correlations. We developed a structure-based computational approach, that uses our experimental data to search the protein surfaces in an unbiased manner to identify the residues involved in the protein-protein interface. Finally, we demonstrated that the obtained information of the molecular interface could be directly leveraged to support protein-protein docking studies. Such rapid construction of a complex model provides valuable information and enables more efficient biochemical characterization of a protein-protein complex, for instance, as the first step in structure-guided drug development.     

Poxvirus Proteomics and Virus-Host Protein Interactions

Summary: Studies of the functional proteins encoded by the poxvirus genome provide information about the composition of the virus as well as individual virus-virus protein and virus-host protein interactions, which provides insight into viral pathogenesis and drug discovery. Widely used proteomic techniques to identify and characterize specific protein-protein interactions include yeast two-hybrid studies and coimmunoprecipitations. Recently, various mass spectrometry techniques have been employed to identify viral protein components of larger complexes. These methods, combined with structural studies, can provide new information about the putative functions of viral proteins as well as insights into virus-host interaction dynamics. For viral proteins of unknown function, identification of either viral or host binding partners provides clues about their putative function. In this review, we discuss poxvirus proteomics, including the use of proteomic methodologies to identify viral components and virus-host protein interactions. High-throughput global protein expression studies using protein chip technology as well as new methods for validating putative protein-protein interactions are also discussed.     

Requirement for GroEL/GroES-dependent protein folding under nonpermissive conditions of macromolecular crowding

Macromolecular crowding is a critical parameter affecting the efficiency of cellular protein folding. Here we show that the proteins dihydrofolate reductase, enolase, and green fluorescent protein, which can fold spontaneously in diluted buffer, lose this ability in a crowded environment. Instead, they accumulate as soluble, protease-sensitive non-native species. Their folding becomes dependent on the complete GroEL/GroES chaperonin system and is not affected by trap-GroEL, indicating that folding has to occur in the chaperonin cavity with release of nativelike proteins into the bulk solution. In addition, we demonstrate that efficient folding in the chaperonin cavity requires ATP hydrolysis, as formation of ternary GroEL/GroES complexes with substrate proteins in the presence of ADP results only in very inefficient reactivation. However, protein refolding reactions using ADP-fluoroaluminate complexes, or single-ring GroEL and GroES under conditions where only a single round of ATP hydrolysis occurs, yield large amounts of refolded enzymes. Thus, the mode of initial ternary complex formation appears to be critical for subsequent productive release of substrate into the cavity under certain crowding conditions, and is only efficient when triggered by ATP hydrolysis. Our data indicate that stringent conditions of crowding can impart a stronger dependence of folding proteins on the assistance by chaperonins.     

Methods for mapping of interaction networks involving membrane proteins

Nearly one-third of all genes in various organisms encode membrane-associated proteins that participate in numerous protein-protein interactions important to the processes of life. However, membrane protein interactions pose significant challenges due to the need to solubilize membranes without disrupting protein-protein interactions. Traditionally, analysis of isolated protein complexes by high-resolution 2D gel electrophoresis has been the main method used to obtain an overall picture of proteome constituents and interactions. However, this method is time consuming, labor intensive, detects only abundant proteins and is limited with respect to the coverage required to elucidate large interaction networks. In this review, we discuss the application of various methods to elucidate interactions involving membrane proteins. These techniques include methods for the direct isolation of single complexes or interactors as well as methods for characterization of entire subcellular and cellular interactomes.