Binary Protein Complexes Research Articles

Inducing the structural interplay of binary pulse protein complex to stimulate the solubilization of chickpea (Cicer arietinum L.) protein isolate

Chickpea protein (CP) is an exceptional nutrient-dense pulse protein prevailing in the development of plant-based foods. However, its relatively low solubility, compared to other legume proteins, hinders the practical uses of CP in food matrix. To resolve this problem, pea protein (PP), another popular pulse protein, was co-assembled with CP to form a binary complex during the alkaline pH-shifting process. Results indicated that the complexed CP exhibited significantly increased solubility to that of the pristine protein (more than 50%), whose aqueous stability was also enhanced against different environmental stresses (pH, salt, heat/frozen treatment, and centrifugation). Structural and morphology analysis confirmed the interplay between unfolded CP and PP during pH shifting, which enabled their resistance to acid-induced structural over-folding. Our experiments that induce the co-assembling of two pulse proteins provide a novel routine and scientific basis for tailoring CP functionalities, as well as the formulation of pulse protein-based products.

Computed cancer interactome explains the effects of somatic mutations in cancers.

Protein-protein interactions (PPIs) are involved in almost all essential cellular processes. Perturbation of PPI networks plays critical roles in tumorigenesis, cancer progression, and metastasis. While numerous high-throughput experiments have produced a vast amount of data for PPIs, these data sets suffer from high false positive rates and exhibit a high degree of discrepancy. Coevolution of amino acid positions between protein pairs has proven to be useful in identifying interacting proteins and providing structural details of the interaction interfaces with the help of deep learning methods like AlphaFold (AF). In this study, we applied AF to investigate the cancer protein-protein interactome. We predicted 1,798 PPIs for cancer driver proteins involved in diverse cellular processes such as transcription regulation, signal transduction, DNA repair, and cell cycle. We modeled the spatial structures for the predicted binary protein complexes, 1,087 of which lacked previous 3D structure information. Our predictions offer novel structural insight into many cancer-related processes such as the MAP kinase cascade and Fanconi anemia pathway. We further investigated the cancer mutation landscape by mapping somatic missense mutations (SMMs) in cancer to the predicted PPI interfaces and performing enrichment and depletion analyses. Interfaces enriched or depleted with SMMs exhibit different preferences for functional categories. Interfaces enriched in mutations tend to function in pathways that are deregulated in cancers and they may help explain the molecular mechanisms of cancers in patients; interfaces lacking mutations appear to be essential for the survival of cancer cells and thus may be future targets for PPI modulating drugs.

Characterization of toxicity and structure of PirABvc -like proteins that are structurally almost identical to shrimp AHPND-causing PirAB toxin.

PirAB is a binary toxic protein that causes acute hepatopancreatic necrosis disease (AHPND) in shrimp. Their closest homologs, PirAvc -like and PirBvc -like proteins, are encoded by two adjacent genes on a non-pVH plasmid from a Vibrio campbellii strain. Herein, PirABvc -like protein caused neither abnormalities nor death in shrimp postlarvae (Litopenaeus vannamei); furthermore, typical AHPND clinical signs were not observed. PirAvc -like protein corresponds to Cry toxin domain III (ligand-binding domain) and likely binds to N-acetylgalactosamine. The C-terminal and N-terminal of PirBvc -like resemble Cry toxin domain II (receptor-binding domain) and domain I (pore-forming domain), respectively. PirAvc -like and PirBvc -like proteins are structurally similar to PirA and PirB, respectively. Subtle structural differences between PirAvc -like protein and PirA appear to be involved in ligand-binding and binary protein complex formation. The difference in virulence of PirABvc -like and PirAB may result from the specific binding of the protein complex to distinct host receptors. These results shed light on the potential functions and host receptors of PirABvc -like proteins and their relationship with PirAB.

Small molecule induces mitochondrial fusion for neuroprotection via targeting CK2 without affecting its conventional kinase activity

Mitochondrial fusion/fission dynamics plays a fundamental role in neuroprotection; however, there is still a severe lack of therapeutic targets for this biological process. Here, we found that the naturally derived small molecule echinacoside (ECH) significantly promotes mitochondrial fusion progression. ECH selectively binds to the previously uncharacterized casein kinase 2 (CK2) α′ subunit (CK2α′) as a direct cellular target, and genetic knockdown of CK2α′ abolishes ECH-mediated mitochondrial fusion. Mechanistically, ECH allosterically regulates CK2α′ conformation to recruit basic transcription factor 3 (BTF3) to form a binary protein complex. Then, the CK2α′/BTF3 complex facilitates β-catenin nuclear translocation to activate TCF/LEF transcription factors and stimulate transcription of the mitochondrial fusion gene Mfn2. Strikingly, in a mouse middle cerebral artery occlusion (MCAO) model, ECH administration was found to significantly improve cerebral injuries and behavioral deficits by enhancing Mfn2 expression in wild-type but not CK2α′+/− mice. Taken together, our findings reveal, for the first time, that CK2 is essential for promoting mitochondrial fusion in a Wnt/β-catenin-dependent manner and suggest that pharmacologically targeting CK2 is a promising therapeutic strategy for ischemic stroke.

Peptidomimetics Targeting Protein-Protein Interactions for Therapeutic Development.

Interactions between proteins play a key role in nearly all cellular process, and therefore, its dysregulation may lead to many different types of cellular dysfunctions. Hence, pathologic Protein-Protein Interactions (PPIs) constitute highly attractive drug targets and hold great potential for developing novel therapeutic agents for the treatment of incurable human diseases. Unfortunately, the identification of PPI inhibitors is an extremely challenging task, since traditionally used small molecules ligands are mostly unable to cover and anchor on the extensive and flat surfaces that define those binary protein complexes. In contrast, large biomolecules such as proteins or peptides are ideal fits for this so-called "undruggable" sites. However, their poor pharmacokinetic properties have also limited their applications as therapeutics. In this context, peptidomimetic molecules have emerged as an alternative and viable solution to this problem, since they conserve the architectural and structural features of peptides and also exhibit substantially improved pharmacokinetic profiles. In the last decades, a wide array of chemical approaches granting access to conformationally constrained peptides with substantially improved pharmacokinetic profiles have been described, with a special focus on those affording stapled peptides and allowing large-scale macrocyclizations. These peptidomimetic molecules have been successfully applied to target a plethora of biological hosts, which highlights their promising future as novel therapeutics for the treatment of incurable human diseases.

Assessing Exhaustiveness of Stochastic Sampling for Integrative Modeling of Macromolecular Structures

Modeling of macromolecular structures involves structural sampling guided by a scoring function, resulting in an ensemble of good-scoring models. By necessity, the sampling is often stochastic, and must be exhaustive at a precision sufficient for accurate modeling and assessment of model uncertainty. Therefore, the very first step in analyzing the ensemble is an estimation of the highest precision at which the sampling is exhaustive. Here, we present an objective and automated method for this task. As a proxy for sampling exhaustiveness, we evaluate whether two independently and stochastically generated sets of models are sufficiently similar. The protocol includes testing 1) convergence of the model score, 2) whether model scores for the two samples were drawn from the same parent distribution, 3) whether each structural cluster includes models from each sample proportionally to its size, and 4) whether there is sufficient structural similarity between the two model samples in each cluster. The evaluation also provides the sampling precision, defined as the smallest clustering threshold that satisfies the third, most stringent test. We validate the protocol with the aid of enumerated good-scoring models for five illustrative cases of binary protein complexes. Passing the proposed four tests is necessary, but not sufficient for thorough sampling. The protocol is general in nature and can be applied to the stochastic sampling of any set of models, not just structural models. In addition, the tests can be used to stop stochastic sampling as soon as exhaustiveness at desired precision is reached, thereby improving sampling efficiency; they may also help in selecting a model representation that is sufficiently detailed to be informative, yet also sufficiently coarse for sampling to be exhaustive.

Quantitative analysis of protein interaction network dynamics in yeast

Many cellular functions are mediated by protein–protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment‐dependent protein complex dynamics, we used a DNA‐barcode‐based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that “concerted” protein‐centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass‐action‐based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.

LC-MS/MS-based targeted proteomics quantitatively detects the interaction between p53 and MDM2 in breast cancer

In breast cancer, p53 could be functionally compromised by interaction with several proteins. Among those proteins, MDM2 serves as a pivotal negative regulator and counteracts p53 activation. Thus, the ability to quantitatively and accurately monitor the changes in level of p53-MDM2 interaction with disease state can enable an improved understanding of this protein-protein interaction (PPI), provide a better insight into cancer development and allow the emergence of advanced treatments. However, rare studies have evaluated the quantitative extent of PPI including p53-MDM2 interaction so far. In this study, a LC-MS/MS-based targeted proteomics assay was developed and coupled with co-immunoprecipitation (Co-IP) for the quantification of p53-MDM2 complex. A p53 antibody with the epitope residing at 156–214 residues achieved the greatest IP efficiency. 321KPLDGEYFTLQIR333 (p53) and 327ENWLPEDK334 (MDM2) were selected as surrogate peptides in the targeted analysis. Stable isotope-labeled synthetic peptides were used as internal standards. An LOQ (limit of quantification) of 2ng/mL was obtained. Then, the assay was applied to quantitatively detect total p53, total MDM2 and p53-MDM2 in breast cells and tissue samples. Western blotting was performed for a comparison. Finally, a quantitative time-course analysis in MCF-7 cells with the treatment of nutlin-3 as a PPI inhibitor was also monitored. Biological significanceProteins do not function as single entities but rather as a team player that has to communicate. Protein-protein interaction (PPI), normally by means of non-covalent contact among binary or large protein complex, is essential for many cellular processes including cancer progression. Thus, the ability to quantitatively and accurately monitor the changes in level of PPI with disease state can enable an improved understanding of PPI, provide a better insight into cancer development and allow the emergence of advanced treatments. However, rare studies have evaluated the quantitative extent of PPI so far. The major issue of current available approaches is the trade-off between sensitivity and specificity. Thus, techniques with the ability to quantify PPIs with both high sensitivity (low false-negative rate) and high specificity (low false-positive rate) are eagerly desired. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based targeted proteomics has shown its potential to study biomolecules because of its high sensitivity, high selectivity and wide dynamic range. In this study, we made an effort to develop a LC-MS/MS-based targeted proteomics assay for the quantitative detection of p53-MDM2 interaction in breast cells and tissue samples.

Effect of the ostreolysin A/pleurotolysin B pore-forming complex on intracellular Ca2 + activity in the vascular smooth muscle cell line A10

Ostreolysin A/pleurotolysin B (OlyA/PlyB) is a binary pore-forming protein complex that produces a rapid cardiorespiratory arrest. Increased tonus of the coronary vascular wall produced by OlyA/PlyB may lead to ischemia, arrhythmias, the hypoxic injury of cardiomyocytes and cardiotoxicity. We evaluated the effects of OlyA/PlyB in cultured vascular smooth muscle A10 cells. Fluorometric measurements using the Ca2+ indicator Fluo-4 AM and Fura-2 AM revealed that nanomolar concentrations of OlyA/PlyB increased the intracellular Ca2+ activity [Ca2+]i in A10 cells. This effect was absent in a Ca2+-free medium, indicating that OlyA/PlyB-induced [Ca2+]i increase was dependent on Ca2+ influx into cells. The increase in [Ca2+]i by OlyA/PlyB was partially prevented by: i) the calcium channel blockers verapamil and La3+, ii) the inhibitor of the sodium–calcium exchanger (NCX) benzamil, and iii) the iso-osmotic replacement of NaCl by sucrose. The pre-treatment of cells with the Ca2+-ATPase inhibitor thapsigargin reduced the [Ca2+]i increase evoked by OlyA/PlyB, whereas the plasma membrane depolarization with high K+ in the medium did not prevent OlyA/PlyB-induced [Ca2+]i. In summary, our data could suggest that the OlyA/PlyB-induced increase in [Ca2+]i is due to an influx of Ca2+ through a variety of co-existing plasma membrane Ca2+-permeable channels, Ca2+ entry through non-selective ion permeable pores formed de novo by OlyA/PlyB in the plasma membrane and calcium-induced intracellular Ca2+ release, altogether leading to disturbed Ca2+ homeostasis in A10 cells.

DisVis: quantifying and visualizing accessible interaction space of distance-restrained biomolecular complexes.

Summary: We present DisVis, a Python package and command line tool to calculate the reduced accessible interaction space of distance-restrained binary protein complexes, allowing for direct visualization and quantification of the information content of the distance restraints. The approach is general and can also be used as a knowledge-based distance energy term in FFT-based docking directly during the sampling stage.Availability and implementation: The source code with documentation is freely available from https://github.com/haddocking/disvis.Contact: a.m.j.j.bonvin@uu.nlSupplementary information: Supplementary data are available at Bioinformatics online.

The road to linking genomics and proteomics of pathogenic bacteria: from binary protein complexes to interaction pathways

Background The availability of fully sequenced genomes of many bacterial organisms has enabled mapping networks of binary protein interactions that form the basic building blocks of molecular pathways and dynamic assemblies defining all cellular activities. Few proteome-scale studies have been reported for pathogenic bacteria though, suggesting that a systems-wide network analysis of binary interaction partners could reveal groups of proteins that coordinate to achieve specific biological tasks important to pathogenesis and provide a functional map useful to the discovery of new antibiotics, vaccines, and diagnostic tools.

Structural and biophysical methods to analyze clock function and mechanism.

Structural approaches have provided insight into the mechanisms of circadian clock oscillators. This review focuses upon the myriad structural methods that have been applied to the molecular architecture of cyanobacterial circadian proteins, their interactions with each other, and the mechanism of the KaiABC posttranslational oscillator. X-ray crystallography and solution NMR were deployed to gain an understanding of the three-dimensional structures of the three proteins KaiA, KaiB, and KaiC that make up the inner timer in cyanobacteria. A hybrid structural biology approach including crystallography, electron microscopy, and solution scattering has shed light on the shapes of binary and ternary Kai protein complexes. Structural studies of the cyanobacterial oscillator demonstrate both the strengths and the limitations of the divide-and-conquer strategy. Thus, investigations of complexes involving domains and/or peptides have afforded valuable information into Kai protein interactions. However, high-resolution structural data are still needed at the level of complexes between the 360-kDa KaiC hexamer that forms the heart of the clock and its KaiA and KaiB partners.

Udock, the interactive docking entertainment system.

Protein-protein interactions play a crucial role in biological processes. Protein docking calculations' goal is to predict, given two proteins of known structures, the associate conformation of the corresponding complex. Here, we present a new interactive protein docking system, Udock, that makes use of users' cognitive capabilities added up. In Udock, the users tackle simplified representations of protein structures and explore protein-protein interfaces' conformational space using a gamified interactive docking system with on the fly scoring. We assumed that if given appropriate tools, a naïve user's cognitive capabilities could provide relevant data for (1) the prediction of correct interfaces in binary protein complexes and (2) the identification of the experimental partner in interaction among a set of decoys. To explore this approach experimentally, we conducted a preliminary two week long playtest where the registered users could perform a cross-docking on a dataset comprising 4 binary protein complexes. The users explored almost all the surface of the proteins that were available in the dataset but favored certain regions that seemed more attractive as potential docking spots. These favored regions were located inside or nearby the experimental binding interface for 5 out of the 8 proteins in the dataset. For most of them, the best scores were obtained with the experimental partner. The alpha version of Udock is freely accessible at http://udock.fr.

Solution Structure of the IIAChitobiose-HPr Complex of the N,N′-Diacetylchitobiose Branch of the Escherichia coli Phosphotransferase System

The solution structure of the complex of enzyme IIA of the N,N'-diacetylchitobiose (Chb) transporter with the histidine phosphocarrier protein HPr has been solved by NMR. The IIA(Chb)-HPr complex completes the structure elucidation of representative cytoplasmic complexes for all four sugar branches of the bacterial phosphoryl transfer system (PTS). The active site His-89 of IIA(Chb) was mutated to Glu to mimic the phosphorylated state. IIA(Chb)(H89E) and HPr form a weak complex with a K(D) of ~0.7 mM. The interacting binding surfaces, concave for IIA(Chb) and convex for HPr, complement each other in terms of shape, residue type, and charge distribution, with predominantly hydrophobic residues, interspersed by some uncharged polar residues, located centrally, and polar and charged residues at the periphery. The active site histidine of HPr, His-15, is buried within the active site cleft of IIA(Chb) formed at the interface of two adjacent subunits of the IIA(Chb) trimer, thereby coming into close proximity with the active site residue, H89E, of IIA(Chb). A His89-P-His-15 pentacoordinate phosphoryl transition state can readily be modeled without necessitating any significant conformational changes, thereby facilitating rapid phosphoryl transfer. Comparison of the IIA(Chb)-HPr complex with the IIA(Chb)-IIB(Chb) complex, as well as with other cytoplasmic complexes of the PTS, highlights a unifying mechanism for recognition of structurally diverse partners. This involves generating similar binding surfaces from entirely different underlying structural elements, large interaction surfaces coupled with extensive redundancy, and side chain conformational plasticity to optimize diverse sets of intermolecular interactions.

Multiplex assay for condition-dependent changes in protein–protein interactions

Changes in protein-protein interactions that occur in response to environmental cues are difficult to uncover and have been poorly characterized to date. Here we describe a yeast-based assay that allows many binary protein interactions to be assessed in parallel and under various conditions. This method combines molecular bar-coding and tag array technology with the murine dihydrofolate reductase-based protein-fragment complementation assay. A total of 238 protein-fragment complementation assay strains, each representing a unique binary protein complex, were tagged with molecular barcodes, pooled, and then interrogated against a panel of 80 diverse small molecules. Our method successfully identified specific disruption of the Hom3:Fpr1 interaction by the immunosuppressant FK506, illustrating the assay's capacity to identify chemical inhibitors of protein-protein interactions. Among the additional findings was specific cellular depletion of the Dst1:Rbp9 complex by the anthracycline drug doxorubicin, but not by the related drug idarubicin. The assay also revealed chemical-induced accumulation of several binary multidrug transporter complexes that largely paralleled increases in transcript levels. Further assessment of two such interactions (Tpo1:Pdr5 and Snq2:Pdr5) in the presence of 1,246 unique chemical compounds revealed a positive correlation between drug lipophilicity and the drug response in yeast.

Arbitrary protein−protein docking targets biologically relevant interfaces

BackgroundProtein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations.ResultsIn this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking using PEBP (Phosphatidylethanolamine binding protein), a kinase inhibitor with multiple partners.ConclusionsAn approach using arbitrary docking, and based solely on physical properties, can successfully identify biologically pertinent protein interfaces.

Beauty Is in the Eye of the Beholder: Proteins Can Recognize Binding Sites of Homologous Proteins in More than One Way

Understanding the mechanisms of protein–protein interaction is a fundamental problem with many practical applications. The fact that different proteins can bind similar partners suggests that convergently evolved binding interfaces are reused in different complexes. A set of protein complexes composed of non-homologous domains interacting with homologous partners at equivalent binding sites was collected in 2006, offering an opportunity to investigate this point. We considered 433 pairs of protein–protein complexes from the ABAC database (AB and AC binary protein complexes sharing a homologous partner A) and analyzed the extent of physico-chemical similarity at the atomic and residue level at the protein–protein interface. Homologous partners of the complexes were superimposed using Multiprot, and similar atoms at the interface were quantified using a five class grouping scheme and a distance cut-off. We found that the number of interfacial atoms with similar properties is systematically lower in the non-homologous proteins than in the homologous ones. We assessed the significance of the similarity by bootstrapping the atomic properties at the interfaces. We found that the similarity of binding sites is very significant between homologous proteins, as expected, but generally insignificant between the non-homologous proteins that bind to homologous partners. Furthermore, evolutionarily conserved residues are not colocalized within the binding sites of non-homologous proteins. We could only identify a limited number of cases of structural mimicry at the interface, suggesting that this property is less generic than previously thought. Our results support the hypothesis that different proteins can interact with similar partners using alternate strategies, but do not support convergent evolution.

Solution Structure of an Archaeal RNase P Binary Protein Complex: Formation of the 30-kDa Complex between Pyrococcus furiosus RPP21 and RPP29 Is Accompanied by Coupled Protein Folding and Highlights Critical Features for Protein–Protein and Protein–RNA Interactions

Ribonuclease P (RNase P) is a ribonucleoprotein (RNP) enzyme that catalyzes the Mg 2+-dependent 5′ maturation of precursor tRNAs. In all domains of life, it is a ribozyme: the RNase P RNA (RPR) component has been demonstrated to be responsible for catalysis. However, the number of RNase P protein subunits (RPPs) varies from 1 in bacteria to 9 or 10 in eukarya. The archaeal RPR is associated with at least 4 RPPs, which function in pairs (RPP21–RPP29 and RPP30–POP5). We used solution NMR spectroscopy to determine the three-dimensional structure of the protein–protein complex comprising Pyrococcus furiosus RPP21 and RPP29. We found that the protein–protein interaction is characterized by coupled folding of secondary structural elements that participate in interface formation. In addition to detailing the intermolecular contacts that stabilize this 30-kDa binary complex, the structure identifies surfaces rich in conserved basic residues likely vital for recognition of the RPR and/or precursor tRNA. Furthermore, enzymatic footprinting experiments allowed us to localize the RPP21–RPP29 complex to the specificity domain of the RPR. These findings provide valuable new insights into mechanisms of RNP assembly and serve as important steps towards a three-dimensional model of this ancient RNP enzyme.

Tracking transcription factor complexes on DNA using total internal reflectance fluorescence protein binding microarrays

We have developed a high-throughput protein binding microarray (PBM) assay to systematically investigate transcription regulatory protein complexes binding to DNA with varied specificity and affinity. Our approach is based on the novel coupling of total internal reflectance fluorescence (TIRF) spectroscopy, swellable hydrogel double-stranded DNA microarrays and dye-labeled regulatory proteins, making it possible to determine both equilibrium binding specificities and kinetic rates for multiple protein:DNA interactions in a single experiment. DNA specificities and affinities for the general transcription factors TBP, TFIIA and IIB determined by TIRF–PBM are similar to those determined by traditional methods, while simultaneous measurement of the factors in binary and ternary protein complexes reveals preferred binding combinations. TIRF–PBM provides a novel and extendible platform for multi-protein transcription factor investigation.

Simulations of Multi-protein Complexes: Structure, Binding Affinity, and Dynamics of Vps27/hse1 Bound to Membrane-tethered Ubiquitin

Protein-protein interactions play an essential role in many cellular functions. While biophysical and structural characterizations have traditionally focused on strong binary complexes, the biological importance of weakly bound multi-protein complexes is increasingly recognized. Such complexes typically contain various proteins, with different folded domains held together in part by flexible linkers. Further increasing the complexity, many multi-protein complexes assemble at or near membranes. We develop coarse-grained models and effective energy functions for simulating such large multi-protein complexes with low to intermediate binding affinities (Kd > 1 μM). The models are validated against structure and binding-affinity data for a broad range of binary protein complexes. Using replica exchange Monte Carlo simulation techniques, we apply our model to study the assembly, energetics, and dynamics of the complex between Vps27/Hse1 and membrane-tethered ubiquitin. The yeast Vps27/Hse1 complex and the homologous mammalian Hrs/STAM complex deliver ubiquitinated transmembrane proteins to the ESCRT endosomal protein-sorting pathway that is important in many biological processes. Vps27 and Hse1 contain several folded domains and flexible linkers. We find that the membrane-tethered ubiquitin binds preferentially to the UIM domains of Vps27. However, the simulations also show that ubiquitin interacts with other domains. The observed multiple specific and non-specific ubiquitin-Vps27 interactions greatly enhance the overall binding affinity. In the complex, the structure of Vps27/Hse1 is highly dynamic and flexible, reflecting the ability of Vps27/Hse1 to bind to a diverse set of ubiquitinated protein targets. The models developed here can easily incorporate additional experimental information (e.g., from fluorescence, scattering, electron microscopy), and hold promise for simulations of other large multi-protein complexes.