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This minireview provides an overview on the current knowledge of protein–protein interactions, common characterisation methods to characterise them, and their role in protein complex formation with some examples. A deep understanding of protein–protein interactions and their molecular interactions is important for a number of applications, including drug design. Protein–protein interactions and their discovery are thus an interesting avenue for understanding how protein complexes, which make up the majority of proteins, work.

Using in vitro protein complex formation assay, ability of SNAP-25 isoforms to generate SDS-resistant ternary SNARE complexes with Syntaxin-1 and VAMP-2 was investigated. Major SNAP-25 family proteins were found to generate heat-resistant ternary complexes with varying efficiency. Compared to human SNAP-25, its non-neuronal counterparts SNAP-23 and SNAP-29 formed lower amounts of ternary complexes. Changing Pro182 in human SNAP-23 to Arg182 (SNAP-23 P182R) improved its ability to bind partners and form complexes. In silico analysis of C-terminal helical content in various SNAP-25 family members showed that except human SNAP-23, all others displayed secondary α-helical conformation. We also report that human SNAP-29 is resistant to the proteolytic action of botulinum neurotoxin A even when applied at large concentration., Highlights • Human SNAP-23 forms reduced amounts of ternary SNARE complexes than human SNAP-25. • SNAP-25 family proteins show varying levels of secondary structure at the C-terminus. • C-terminal coil content influences neurotoxin sensitivity and ability to form stable ternary SNARE complexes.

Direct coupling analysis (DCA) is a global statistical approach that uses information encoded in protein sequence data to predict spatial contacts in a three-dimensional structure of a folded protein. DCA has been widely used to predict the monomeric fold at amino acid resolution and to identify biologically relevant interaction sites within a folded protein. Going beyond single proteins, DCA has also been used to identify spatial contacts that stabilize the interaction in protein complex formation. However, extracting this higher order information necessary to predict dimer contacts presents a significant challenge. A DCA evolutionary signal is much stronger at the single protein level (intraprotein contacts) than at the protein-protein interface (interprotein contacts). Therefore, if DCA-derived information is to be used to predict the structure of these complexes, there is a need to identify statistically significant DCA predictions. We propose a simple Z-score measure that can filter good predictions despite noisy, limited data. This new methodology not only improves our prediction ability but also provides a quantitative measure for the validity of the prediction.

A high-throughput analysis of protein complex variants among orthologs provides a mechanistic model for neofunctionalization., Whole-genome duplications are common during evolution, creating genetic redundancy that can enable cellular innovations. Novel protein-protein interactions provide a route to diversified gene functions, but, at present, there is limited proteome-scale knowledge on the extent to which variability in protein complex formation drives neofunctionalization. Here, we used protein correlation profiling to test for variability in apparent mass among thousands of orthologous proteins isolated from diverse species and cell types. Variants in protein complex size were unexpectedly common, in some cases appearing after relatively recent whole-genome duplications or an allopolyploidy event. In other instances, variants such as those in the carbonic anhydrase orthologous group reflected the neofunctionalization of ancient paralogs that have been preserved in extant species. Our results demonstrate that homo- and heteromer formation have the potential to drive neofunctionalization in diverse classes of enzymes, signaling, and structural proteins.

The postsynaptic density (PSD) is a neuronal organelle that consists of thousands of protein complexes, having a role in signal transduction. The emergence of the complexes is dependent on the presence of proteins provided by gene expression. In this research we used Chip-seq data supported by protein level information. We developed a pipeline using data from five neuronal transcription factors, which reduces the false-positive hits of identified binding sites. In addition we found correlation between co-regulation and protein complex formation. The developed method paves the way for a future for large scale analysis utilizing a more comprehensive set of transcription factors.

Understanding protein-protein interactions is key to unraveling protein function in vivo. Here we describe a dual/triple-plasmid system that enables co-expression of two, or three, recombinant proteins harboring different affinity tags in the same Escherichia coli cell. This novel protein expression system provides a platform to understand protein-protein interactions and enables researchers to study protein complex formation and in vivo localization.

Geophytes, the plants that form vegetative storage organs, are characterized by a dual reproduction system, in which vegetative and sexual propagation are tightly regulated to ensure fitness in harsh climatic conditions. Recent findings highlight the role of the PEBP (PHOSPHATIDYLETHANOLAMINE-BINDING PROTEIN) gene family in geophytes as major players in the molecular cascades underlying both types of reproduction. In this review, we briefly explain the life cycle and reproduction strategies of different geophytes and what is known about the physiological aspects related to these processes. Subsequently, an in-depth overview is provided of the molecular and genetic pathways driving these processes. In the evolution of plants, the PEBP gene family has expanded, followed by neo- and subfunctionalization. Careful characterization revealed that differential expression and differential protein complex formation provide the members of this gene family with unique functions, enabling them to mediate the crosstalk between the two reproductive events in geophytes in response to environmental and endogenous cues. Taking all these studies into account, we propose to regard the PEBPs as conductors of geophyte reproductive development.

The effect of milk pH before heating on casein–whey protein interactions and ultimate gel properties of the free-fat yoghurt was investigated. Reconstituted skim milk at different pH values (6.4, 6.8 and 7.2) was heated at 80 °C for 30 min. The type of protein and size of casein micelle in milk were determined. The storage modulus (G′), loss tangent (tan δ), flow behaviour as well as microstructure, firmness and water holding capacity of the yoghurt samples were measured. Heating milk at pH 7.2 formed mostly soluble protein complexes whereas at pH 6.4 micelle bound complexes was dominant. However, heating milk at pH 6.8 resulted in a relatively compact protein network due to a balanced contribution from both soluble protein/κ-casein complexes and whey protein-casein micelle associated complexes. Yoghurt prepared with milk heated at pH 6.8 showed significantly higher G′ values, shorter gelation times, higher water holding capacity, firmness and more compact protein network compared to those at pH 6.4, 7.2 and unheated milk. The obtained results demonstrated that milk pH adjustment before heating could be an important factor governing uniform quality yoghurt production.

AMPA-type glutamate receptors (AMPARs) mediate fast excitatory synaptic transmission in the central nervous system. Dysregulation of AMPAR function is associated with many kinds of neurological, neurodegenerative, and psychiatric disorders. As a result, molecules capable of controlling AMPAR functions are potential therapeutic agents. Fluorescent semisynthetic biosensors have attracted considerable interest for the discovery of ligands selectively acting on target proteins. Given the large protein complex formation of AMPARs in live cells, biosensors using full-length AMPARs retaining original functionality are ideal for drug screening. Here, we demonstrate that fluorophore-labeled AMPARs prepared by ligand-directed acyl imidazole chemistry can act as turn-on fluorescent biosensors for AMPAR ligands in living cells. These biosensors selectively detect orthosteric ligands of AMPARs among the glutamate receptor family. Notably, the dissociation constants of agonists and antagonists for AMPARs were determined in live cells, which revealed that the ligand-binding properties of AMPARs to agonists are largely different in living cells, compared with noncellular conditions. We also show that these sensors can be applied to detecting allosteric modulators or subunit-selective ligands of AMPARs. Thus, our protein-based biosensors can be useful for discovering pharmaceutical agents to treat AMPAR-related neurological disorders.

Heat-induced coacervation of triblock copolymer solution was described, and its application in the purification of Lycium barbarum polysaccharide (LBP) was investigated. The formation of coacervate micelles–protein complex combined with the incompatibility between coacervate micelles and polysaccharide made it an ideal system for the separation of protein and LBP. This separation process was governed by a series of parameters including polymer concentration, amount of crude LBP solution, and pH. In the primary coacervation extraction process, LBP was preferentially distributed to dilute phase with a high recovery ratio of 82%, whereas 87% of protein was partitioned to the coacervate phase. The coacervate micelles–protein interaction and the interphase potential was regulated by temperature and electrolytes, respectively, which contributed to the recovery and recycling of the polymer. After phase separation, LBP was precipitated with the addition of ethanol. The FTIR spectrum was used to identify LBP. In addition, the antioxidant activity of LBP was measured.

Interactions between MADS box transcription factors are critical in the regulation of floral development, and shifting MADS box protein-protein interactions are predicted to have influenced floral evolution. However, precisely how evolutionary variation in protein-protein interactions affects MADS box protein function remains unknown. To assess the impact of changing MADS box protein-protein interactions on transcription factor function, we turned to the grasses, where interactions between B-class MADS box proteins vary. We tested the functional consequences of this evolutionary variability using maize (Zea mays) as an experimental system. We found that differential B-class dimerization was associated with subtle, quantitative differences in stamen shape. In contrast, differential dimerization resulted in large-scale changes to downstream gene expression. Differential dimerization also affected B-class complex composition and abundance, independent of transcript levels. This indicates that differential B-class dimerization affects protein degradation, revealing an important consequence for evolutionary variability in MADS box interactions. Our results highlight complexity in the evolution of developmental gene networks: changing protein-protein interactions could affect not only the composition of transcription factor complexes but also their degradation and persistence in developing flowers. Our results also show how coding change in a pleiotropic master regulator could have small, quantitative effects on development.

The basic study of protein provides insight into their role in health and diseases. Protein–protein interaction (PPI) networks are intrinsic to virtually every cellular process and of vital importance in systems biology. Besides the knowledge of protein three-dimensional structures, their dynamics and interaction profiles are important to completely understand the biochemical mechanisms at the molecular level and utilize it for the benefit of mankind. Protein–protein interactions can alter the kinetic properties of proteins, and this can be reflected in the form of crucial alteration in specificity to substrates, catalysis, or altered allosteric properties of the complex. Understanding of protein complex formation allows an analysis of molecular functions, and hence needed to redesign and produce tailor-made proteins suitable for desired work. In the last decades, a vast amount of PPI data was generated by high-throughput experimental methods. However, voluminous unexplored proteins, creating the computational analysis of the PPI network a mandatory tool. Moreover, each method carries its advantages and disadvantages to reproduce a true PPI model that precisely set up under physiological conditions. To properly understand the significance of PPI in the cell, one needs to thoroughly verify through the physical, molecular biological, and genetic approaches that have been used to detect protein–protein interactions. This chapter describes the various wet and dry lab approaches to study the molecular details of interactions and to consider the reliability of each method.

Ubiquitination is a versatile and dynamic post-translational modification in which single ubiquitin molecules or polyubiquitin chains are attached to target proteins, giving rise to mono- or poly-ubiquitination, respectively. The majority of research in the ubiquitin field focused on degradative polyubiquitination, whereas more recent studies uncovered the role of single ubiquitin modification in important physiological processes. Monoubiquitination can modulate the stability, subcellular localization, binding properties, and activity of the target proteins. Understanding the function of monoubiquitination in normal physiology and pathology has important therapeutic implications, as alterations in the monoubiquitin pathway are found in a broad range of genetic diseases. This review highlights a link between monoubiquitin signaling and the pathogenesis of genetic disorders. ispartof: International Journal of Molecular Sciences vol:21 issue:9 ispartof: location:Switzerland status: published

The activation of G proteins by G protein-coupled receptors (GPCRs) underlies the majority of transmembrane signaling by hormones and neurotransmitters. Recent structures of GPCR-G protein complexes obtained by crystallography and cryo-electron microscopy (cryo-EM) reveal similar interactions between GPCRs and the alpha subunit of different G protein isoforms. While some G protein subtype-specific differences are observed, there is no clear structural explanation for G protein subtype-selectivity. All of these complexes are stabilized in the nucleotide-free state, a condition that does not exist in living cells. In an effort to better understand the structural basis of coupling specificity, we used time-resolved structural mass spectrometry techniques to investigate GPCR-G protein complex formation and G-protein activation. Our results suggest that coupling specificity is determined by one or more transient intermediate states that serve as selectivity filters and precede the formation of the stable nucleotide-free GPCR-G protein complexes observed in crystal and cryo-EM structures.

Paramagnetic NMR methods are excellently suited for the study of protein–protein complexes in solution. Intermolecular pseudocontact shifts (PCSs), residual dipolar couplings (RDCs) and paramagnetic relaxations enhancements (PREs) can be used, ideally in combination, for docking proteins and determining their orientation in the complex. PCSs can be used for breaking the structure symmetry in dimer complexes. PCSs also can be applied to detect structural differences in proteins and protein complexes in solution in comparison to crystal structures. RDCs are sensitive to the degree of alignment of both partners in a protein complex and are thus very useful to detect dynamics within complexes. PREs can detect states in which nuclei approach a paramagnetic centre closely, even if it exists only for a small fraction of the time. Thus, PREs are used to detect minor states and characterize ensembles. PRE studies have been the foundation for characterizing encounter states and the process of protein complex formation. In weak complexes, such as are found in electron transfer chains, proteins can be in an encounter state for a large fraction of the complex lifetime. Paramagnetic NMR tools thus have found many applications for studying protein complexes, and more may be on the horizon.

Periodically repeating DNA and protein elements are involved in various important biological events including genomic evolution, gene regulation, protein complex formation, and immunity. Notably, the currently used genome editing tools such as ZFNs, TALENs, and CRISPRs are also all associated with periodically repeating biomolecules of natural organisms. Despite the biological importance of periodically repeating sequences and the expectation that new genome editing modules could be discovered from such periodical repeats, no software that globally detects such structured elements in large genomic resources in a high-throughput and unsupervised manner has been developed. We developed new software, SPADE (Search for Patterned DNA Elements), that exhaustively explores periodic DNA and protein repeats from large-scale genomic datasets based on k-mer periodicity evaluation. With a simple constraint, sequence periodicity, SPADE captured reported genome-editing-associated sequences and other protein families involving repeating domains such as tetratricopeptide, ankyrin and WD40 repeats with better performance than the other software designed for limited sets of repetitive biomolecular sequences, suggesting the high potential of this software to contribute to the discovery of new biological events and new genome editing modules.

The base excision repair pathway plays an important role in correcting damage induced by either physiological or external effects. This repair pathway removes incorrect bases from the DNA. The uracil base is among the most frequently occurring erroneous bases in DNA, and is cut out from the phosphodiester backbone via the catalytic action of uracil‐DNA glycosylase. Uracil excision repair is an evolutionarily highly conserved pathway and can be specifically inhibited by a protein inhibitor of uracil‐DNA glycosylase. Interestingly, both uracil‐DNA glycosylase (Staphylococcus aureus uracil‐DNA glycosylase; SAUDG) and its inhibitor (S. aureus uracil‐DNA glycosylase inhibitor; SAUGI) are present in the staphylococcal cell. The interaction of these two proteins effectively decreases the efficiency of uracil‐DNA excision repair. The physiological relevance of this complexation has not yet been addressed in detailed; however, numerous mutations have been identified within SAUGI. Here, we investigated whether these mutations drastically perturb the interaction with SAUDG. To perform quantitative analysis of the macromolecular interactions, we applied native mass spectrometry and demonstrated that this is a highly efficient and specific method for determination of dissociation constants. Our results indicate that several naturally occurring mutations of SAUGI do indeed lead to appreciable changes in the dissociation constants for complex formation. However, all of these K d values remain in the nanomolar range and therefore the association of these two proteins is preserved. We conclude that complexation is most likely preserved even with the naturally occurring mutant uracil‐DNA glycosylase inhibitor proteins.

Purification of proteins containing disordered regions and participating in transient complexes is often challenging because of the small amounts available after purification, their heterogeneity, instability, and/or poor solubility. To circumvent these difficulties, we set up a methodology that enables the production of stable complexes in large amounts for structural and functional studies. In this chapter, we describe the methodology used to establish the best cell culture conditions and buffer compositions to optimize soluble protein production and their stabilization through protein complex formation. Two examples of challenging protein families are described, namely, the human steroid nuclear receptors and the HIV-1 pre-integration complexes.

Proteins interact with one another across a broad spectrum of affinities. Our understanding of the low end of this spectrum, as characterized by millimolar dissociation constants, relies on a handful of cases in which weak encounters have experimentally been identified. These weak interactions away from the specific target binding site can lead toward a higher-affinity complex. Recently, we detected weak encounters between two paralogous phosphotransferase pathways of Escherichia coli, which regulate various metabolic processes and stress responses. In addition to encounters that are known to occur between cognate proteins, i.e., those that can exchange phosphate groups with each other, surprisingly, encounters involving noncognates were also observed. It is not clear whether these “futile” encounters have a cooperative or competitive role. Using agent-based simulations, we find that the encounter complexes can be cooperative or competitive so as to increase or lower the effective binding affinity of the specific complex under different circumstances. This finding invites further questions into how organisms might exploit such low affinities to connect their signaling components.

Cellular functions are often performed by multiprotein structures called protein complexes. These complexes are dynamic structures that evolve during the cell cycle or in response to external and internal stimuli, and are tightly regulated by protein expression in different tissues resulting in quantitative and qualitative variation of protein complexes. Advances in high-throughput techniques, such as mass-spectrometry and yeast two-hybrid provided a large amount of data on protein-protein interactions. This sparked the development of computational methods able to predict protein complex formation under a variety of biological and clinical conditions. However, the challenges that need to be addressed for successful computational protein complex prediction are highly complex.The post-genomic era saw an emerging number of algorithms and software, which are able to predict protein complexes from protein-protein interaction networks and a variety of other sources. Despite the high capacity of these methods to qualitatively predict protein complexes, they could provide only limited or no quantitative information of the predicted complexes. Recently, a new large-scale simulation of protein complexes was able to achieve this task by simulating protein complex formation on the proteome scale.In this chapter, we review representative methods that can predict multiple protein complexes at different scales and discuss how these can be combined with emerging sources of data in order to improve protein complex characterization.

Summary To examine the scaffolding properties of PSD-95, we have taken advantage of established ligand/PDZ domain interactions and developed a cell-based assay for investigating protein complex formation. This assay enables quantitative analysis of PDZ domain-mediated protein clustering using bimolecular fluorescence complementation (BiFC). Two nonfluorescent halves of EYFP were fused to C-terminal PDZ ligand sequences to generate probes that sense for PDZ domain binding grooves of adjacent (interacting) molecules. When these probes are brought into proximity by the PDZ domains of a multiprotein scaffold, a functional fluorescent EYFP molecule can be detected. We have used this system to examine the properties of selected PSD-95 variants and thereby delineated regions of importance for PSD-95 complex formation. Further analysis led to the finding that PSD-95 multimerization is PDZ domain-mediated and promoted by ligand binding.

Current single-molecule techniques do not permit the real-time observation of multiple proteins interacting closely with each other. We here report an approach enabling us to determine the single-molecule fluorescence resonance energy transfer (FRET) kinetics of multiple protein–protein interactions occurring far below the diffraction limit. We observe a strongly cooperative formation of multimeric soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complexes, which suggests that formation of the first SNARE complex triggers a cascade of SNARE complex formation.

Protein-protein interactions are important in many essential biological functions, such as transcription, translation, and signal transduction. Much progress has been made in understanding protein-protein association in dilute solution via experimentation and simulation. Cells, however, contain various macromolecules, such as DNA, RNA, proteins, among many others, and a myriad of non-specific interactions (usually weak) are present between these cellular constituents. In this review article, we describe the important developments in recent years that have furthered our understanding and even allowed prediction of the consequences of macromolecular crowding on protein-protein interactions. We outline the development of our crowding theory that can predict the change in binding free energy due to crowding quantitatively for both repulsive and attractive protein-crowder interactions. One of the most important findings from our recent work is that weak attractive interactions between crowders and proteins can actually destabilize protein complex formation as opposed to the commonly assumed stabilizing effect predicted based on traditional crowding theories that only account for the entropic-excluded volume effects. We also discuss the implications of macromolecular crowding on the population of encounter versus specific native complex.

Spinocerebellar ataxia type 1 (SCA1) is a dominantly inherited neurodegenerative disease caused by polyglutamine expansion in Ataxin-1 (ATXN1). ATXN1 binds to the transcriptional repressor Capicua (CIC), and the interaction plays a critical role in SCA1 pathogenesis whereby reducing CIC levels rescues SCA1-like phenotypes in a mouse model. The ATXN1/HBP1 (AXH) domain of ATXN1 mediates its homodimerization as well as the interaction with CIC. Here, we present the crystal structure of ATXN1's AXH domain bound to CIC and show that the binding pocket of the AXH domain to CIC overlaps with the homodimerization pocket of the AXH domain. Thus, the binding to CIC disrupts the homodimerization of ATXN1. Furthermore, the binding of CIC reconfigures the complex to allow another form of dimerization mediated by CIC, showing the intricacy of protein complex formation and reconfiguration by ATXN1 and CIC. Identifying the surfaces mediating the interactions between CIC and ATXN1 reveals a critical role for CIC in the reconfiguration of the AXH dimers and might provide insight into ways to target the ATXN1/CIC interactions to modulate SCA1 pathogenesis.

Post-translational modifications by the Small Ubiquitin-like Modifier (SUMO) are essential for diverse cellular functions. Large-scale experiment and sequence-based predictions have identified thousands of SUMOylated proteins. However, the overlap between the datasets is small, suggesting many false positives with low functional relevance. Therefore, we integrated ~800 sequence features and protein characteristics such as cellular function and protein-protein interactions in a machine learning approach to score likely functional SUMOylation events (iSUMO). iSUMO is trained on a total of 24 large-scale datasets, and it predicts 2,291 and 706 SUMO targets in human and yeast, respectively. These estimates are five times higher than what existing sequence-based tools predict at the same 5% false positive rate. Protein-protein and protein-nucleic acid interactions are highly predictive of protein SUMOylation, supporting a role of the modification in protein complex formation. We note the marked prevalence of SUMOylation amongst RNA-binding proteins. We validate iSUMO predictions by experimental or other evidence. iSUMO therefore represents a comprehensive tool to identify high-confidence, functional SUMOylation events for human and yeast.

Starch-rich crops form the basis of our nutrition, but plants have still to yield all their secrets as to how they make this vital substance. Great progress has been made by studying both crop and model systems, and we approach the point of knowing the enzymatic machinery responsible for creating the massive, insoluble starch granules found in plant tissues. Here, we summarize our current understanding of these biosynthetic enzymes, highlighting recent progress in elucidating their specific functions. Yet, in many ways we have only scratched the surface: much uncertainty remains about how these components function together and are controlled. We flag-up recent observations suggesting a significant degree of flexibility during the synthesis of starch and that previously unsuspected non-enzymatic proteins may have a role. We conclude that starch research is not yet a mature subject and that novel experimental and theoretical approaches will be important to advance the field.

The crowded environment of cells poses a challenge for rapid protein-protein association. Yet, it has been established that the rates of association are similar in crowded and in dilute solutions. Here we probe the pathway leading to fast association between TEM1 β-lactamase and its inhibitor protein BLIP in crowded solutions. We show that the affinity of the encounter complex, the rate of final complex formation, and the structure of the transition state are similar in crowded solutions and in buffer. The experimental results were reproduced by calculations based on the transient-complex theory for protein association. Both experiments and calculations suggest that while crowding agents decrease the diffusion constant of the associating proteins, they also induce an effective excluded-volume attraction between them. The combination of the two opposing effects thus results in nearly identical overall association rates in diluted and crowded solutions.