Cation–π, amino–π, π–π, and H‐bond interactions stabilize antigen–antibody interfaces

The identification of immunogenic regions on the surface of antigens, which are able to stimulate an immune response, is a major challenge for the design of new vaccines. Computational immunology aims at predicting such regions—in particular B‐cell epitopes—but is far from being reliably applicable on a large scale. To gain understanding into the factors that contribute to the antigen–antibody affinity and specificity, we perform a detailed analysis of the amino acid composition and secondary structure of antigen and antibody surfaces, and of the interactions that stabilize the complexes, in comparison with the composition and interactions observed in other heterodimeric protein interfaces. We make a distinction between linear and conformational B‐cell epitopes, according to whether they consist of successive residues along the polypeptide chain or not. The antigen–antibody interfaces were shown to differ from other protein–protein interfaces by their smaller size, their secondary structure with less helices and more loops, and the interactions that stabilize them: more H‐bond, cation–π, amino–π, and π–π interactions, and less hydrophobic packing; linear and conformational epitopes can clearly be distinguished. Often, chains of successive interactions, called cation/amino–π and π–π chains, are formed. The amino acid composition differs significantly between the interfaces: antigen–antibody interfaces are less aliphatic and more charged, polar and aromatic than other heterodimeric protein interfaces. Moreover, paratopes and epitopes—albeit to a lesser extent—have amino acid compositions that are distinct from general protein surfaces. This specificity holds promise for improving B‐cell epitope prediction. Proteins 2014; 82:1734–1746. © 2014 Wiley Periodicals, Inc.     

Linkers in the structural biology of protein–protein interactions

Linkers or spacers are short amino acid sequences created in nature to separate multiple domains in a single protein. Most of them are rigid and function to prohibit unwanted interactions between the discrete domains. However, Gly‐rich linkers are flexible, connecting various domains in a single protein without interfering with the function of each domain. The advent of recombinant DNA technology made it possible to fuse two interacting partners with the introduction of artificial linkers. Often, independent proteins may not exist as stable or structured proteins until they interact with their binding partner, following which they gain stability and the essential structural elements. Gly‐rich linkers have been proven useful for these types of unstable interactions, particularly where the interaction is weak and transient, by creating a covalent link between the proteins to form a stable protein–protein complex. Gly‐rich linkers are also employed to form stable covalently linked dimers, and to connect two independent domains that create a ligand‐binding site or recognition sequence. The lengths of linkers vary from 2 to 31 amino acids, optimized for each condition so that the linker does not impose any constraints on the conformation or interactions of the linked partners. Various structures of covalently linked protein complexes have been described using X‐ray crystallography, nuclear magnetic resonance and cryo‐electron microscopy techniques. In this review, we evaluate several structural studies where linkers have been used to improve protein quality, to produce stable protein–protein complexes, and to obtain protein dimers.     

Importance of the interaction protein–protein of the CaM–PDE1A and CaM–MLCK complexes in the development of new anti‐CaM drugs

Protein–protein interactions play central roles in physiological and pathological processes. The bases of the mechanisms of drug action are relevant to the discovery of new therapeutic targets. This work focuses on understanding the interactions in protein–protein–ligands complexes, using proteins calmodulin (CaM), human calcium/calmodulin‐dependent 3′,5′‐cyclic nucleotide phosphodiesterase 1A active human (PDE1A), and myosin light chain kinase (MLCK) and ligands αII–spectrin peptide (αII–spec), and two inhibitors of CaM (chlorpromazine (CPZ) and malbrancheamide (MBC)). The interaction was monitored with a fluorescent biosensor of CaM (hCaM M124C–mBBr). The results showed changes in the affinity of CPZ and MBC depending on the CaM–protein complex under analysis. For the Ca²⁺–CaM, Ca²⁺–CaM–PDE1A, and Ca²⁺–CaM–MLCK complexes, CPZ apparent dissociation constants (K_ds) were 1.11, 0.28, and 0.55 μM, respectively; and for MBC K_ds were 1.43, 1.10, and 0.61 μM, respectively. In competition experiments the addition of calmodulin binding peptide 1 (αII–spec) to Ca²⁺–hCaM M124C–mBBr quenched the fluorescence (K_d = 2.55 ± 1.75 pM) and the later addition of MBC (up to 16 μM) did not affect the fluorescent signal. Instead, the additions of αII–spec to a preformed Ca²⁺–hCaM M124C–mBBr–MBC complex modified the fluorescent signal. However, MBC was able to displace the PDE1A and MLCK from its complex with Ca²⁺–CaM. In addition, docking studies were performed for all complexes with both ligands showing an excellent correlation with experimental data. These experiments may help to explain why in vivo many CaM drugs target prefer only a subset of the Ca²⁺–CaM regulated proteins and adds to the understanding of molecular interactions between protein complexes and small ligands. Copyright © 2013 John Wiley & Sons, Ltd.     

The role of residue stability in transient protein–protein interactions involved in enzymatic phosphate hydrolysis. A computational study

Finding why protein–protein interactions (PPIs) are so specific can provide a valuable tool in a variety of fields. Statistical surveys of so‐called transient complexes (like those relevant for signal transduction mechanisms) have shown a tendency of polar residues to participate in the interaction region. Following this scheme, residues in the unbound partners have to compete between interacting with water or interacting with other residues of the protein. On the other hand, several works have shown that the notion of active site electrostatic preorganization can be used to interpret the high efficiency in enzyme reactions. This preorganization can be related to the instability of the residues important for catalysis. In some enzymes, in addition, conformational changes upon binding to other proteins lead to an increase in the activity of the enzymatic partner. In this article the linear response approximation version of the semimacroscopic protein dipoles Langevin dipoles (PDLD/S‐LRA) model is used to evaluate the stability of several residues in two phosphate hydrolysis enzymes upon complexation with their activating partners. In particular, the residues relevant for PPI and for phosphate hydrolysis in the CDK2/Cyclin A and Ras/GAP complexes are analyzed. We find that the evaluation of the stability of residues in these systems can be used to identify not only active site regions but it can also be used as a guide to locate “hot spots” for PPIs. We also show that conformational changes play a major role in positioning interfacing residues in a proper “energetic” orientation, ready to interact with the residues in the partner protein surface. Thus, we extend the preorganization theory to PPIs, extrapolating the results we obtained from the above‐mentioned complexes to a more general case. We conclude that the correlation between stability of a residue in the surface and the likelihood that it participates in the interaction can be a general fact for transient PPIs. Proteins 2006. © 2005 Wiley‐Liss, Inc.     

Using collections of structural models to predict changes of binding affinity caused by mutations in protein–protein interactions

Protein–protein interactions (PPIs) in all the molecular aspects that take place both inside and outside cells. However, determining experimentally the structure and affinity of PPIs is expensive and time consuming. Therefore, the development of computational tools, as a complement to experimental methods, is fundamental. Here, we present a computational suite: MODPIN, to model and predict the changes of binding affinity of PPIs. In this approach we use homology modeling to derive the structures of PPIs and score them using state‐of‐the‐art scoring functions. We explore the conformational space of PPIs by generating not a single structural model but a collection of structural models with different conformations based on several templates. We apply the approach to predict the changes in free energy upon mutations and splicing variants of large datasets of PPIs to statistically quantify the quality and accuracy of the predictions. As an example, we use MODPIN to study the effect of mutations in the interaction between colicin endonuclease 9 and colicin endonuclease 2 immune protein from Escherichia coli. Finally, we have compared our results with other state‐of‐art methods.     

LuTHy: a double‐readout bioluminescence‐based two‐hybrid technology for quantitative mapping of protein–protein interactions in mammalian cells

Information on protein–protein interactions (PPIs) is of critical importance for studying complex biological systems and developing therapeutic strategies. Here, we present a double‐readout bioluminescence‐based two‐hybrid technology, termed LuTHy, which provides two quantitative scores in one experimental procedure when testing binary interactions. PPIs are first monitored in cells by quantification of bioluminescence resonance energy transfer (BRET) and, following cell lysis, are again quantitatively assessed by luminescence‐based co‐precipitation (LuC). The double‐readout procedure detects interactions with higher sensitivity than traditional single‐readout methods and is broadly applicable, for example, for detecting the effects of small molecules or disease‐causing mutations on PPIs. Applying LuTHy in a focused screen, we identified 42 interactions for the presynaptic chaperone CSPα, causative to adult‐onset neuronal ceroid lipofuscinosis (ANCL), a progressive neurodegenerative disease. Nearly 50% of PPIs were found to be affected when studying the effect of the disease‐causing missense mutations L115R and ?L116 in CSPα with LuTHy. Our study presents a robust, sensitive research tool with high utility for investigating the molecular mechanisms by which disease‐associated mutations impair protein activity in biological systems.     

Lysine methylation modulates the protein–protein interactions of yeast cytochrome C Cyc1p

In recent years, protein methylation has been established as a major intracellular PTM. It has also been proposed to modulate protein‐protein interactions (PPIs) in the interactome. To investigate the effect of PTMs on PPIs, we recently developed the conditional two‐hybrid (C2H) system. With this, we demonstrated that arginine methylation can modulate PPIs in the yeast interactome. Here, we used the C2H system to investigate the effect of lysine methylation. Specifically, we asked whether Ctm1p‐mediated trimethylation of yeast cytochrome c Cyc1p, on lysine 78, modulates its interactions with Erv1p, Ccp1p, Cyc2p and Cyc3p. We show that the interactions between Cyc1p and Erv1p, and between Cyc1p and Cyc3p, are significantly increased upon trimethylation of lysine 78. This increase of interaction helps explain the reported facilitation of Cyc1p import into the mitochondrial intermembrane space upon methylation. This first application of the C2H system to the study of methyllysine‐modulated interactions further confirms its robustness and flexibility.     

Meta‐analysis on blood transcriptomic studies identifies consistently coexpressed protein–protein interaction modules as robust markers of human aging

The bodily decline that occurs with advancing age strongly impacts on the prospects for future health and life expectancy. Despite the profound role of age in disease etiology, knowledge about the molecular mechanisms driving the process of aging in humans is limited. Here, we used an integrative network-based approach for combining multiple large-scale expression studies in blood (2539 individuals) with protein–protein Interaction (PPI) data for the detection of consistently coexpressed PPI modules that may reflect key processes that change throughout the course of normative aging. Module detection followed by a meta-analysis on chronological age identified fifteen consistently coexpressed PPI modules associated with chronological age, including a highly significant module (P = 3.5 × 10⁻³⁸) enriched for ‘T-cell activation’ marking age-associated shifts in lymphocyte blood cell counts (R² = 0.603; P = 1.9 × 10⁻¹⁰). Adjusting the analysis in the compendium for the ‘T-cell activation’ module showed five consistently coexpressed PPI modules that robustly associated with chronological age and included modules enriched for ‘Translational elongation’, ‘Cytolysis’ and ‘DNA metabolic process’. In an independent study of 3535 individuals, four of five modules consistently associated with chronological age, underpinning the robustness of the approach. We found three of five modules to be significantly enriched with aging-related genes, as defined by the GenAge database, and association with prospective survival at high ages for one of the modules including ASF1A. The hereby-detected age-associated and consistently coexpressed PPI modules therefore may provide a molecular basis for future research into mechanisms underlying human aging.     

The structural analysis of protein–protein interactions by NMR spectroscopy

A comprehensive understanding of protein–protein interactions is an important next step in our quest to understand how the information contained in a genome is put into action. Although a number of experimental techniques can report on the existence of a protein– protein interaction, very few can provide detailed structural information. NMR spectroscopy is one of these, and in recent years several complementary NMR approaches, including residual dipolar couplings and the use of paramagnetic effects, have been developed that can provide insight into the structure of protein–protein complexes. In this article, we review these approaches and comment on their strengths and weaknesses.     

Solvated protein–protein docking using Kyte‐Doolittle‐based water preferences

HADDOCK is one of the few docking programs that can explicitly account for water molecules in the docking process. Its solvated docking protocol starts from hydrated molecules and a fraction of the resulting interfacial waters is subsequently removed in a biased Monte Carlo procedure based on water‐mediated contact probabilities. The latter were derived from an analysis of water contact frequencies from high‐resolution crystal structures. Here, we introduce a simple water‐mediated amino acid–amino acid contact probability scale derived from the Kyte‐Doolittle hydrophobicity scale and assess its performance on the largest high‐resolution dataset developed to date for solvated docking. Both scales yield high‐quality docking results. The novel and simple hydrophobicity scale, which should reflect better the physicochemical principles underlying contact propensities, leads to a performance improvement of around 10% in ranking, cluster quality and water recovery at the interface compared with the statistics‐based original solvated docking protocol. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Identification of GABAA Receptor Subunits in Rat Retina: Cloning of the Rat GABAA Receptor ρ2-Subunit cDNA

Abstract: We identified GABA_A receptor subunits in rat retina using PCR. The high degree of conservation among previously described members of ligand-gated anion channels in transmembrane domains was used to design degenerate sense and antisense oligonucleotides. These oligonucleotides were used as primers for PCR, which was applied to the rat retina cDNA. Analysis of clones derived from the PCR amplification identified the GABA_Aα₁, β₁, β₃, and γ₂ subunits and the glycine α₁ subunit. In addition, two clones closely related to the human GABA_Aρ-subunit class were obtained. Molecular cloning revealed one of them as the rat counterpart of the human ρ₂ subunit. Northern blot analysis demonstrated the expression of mRNAs for ρ subunits in retina. These results further support the hypothesis that bicuculline-insensitive GABA channels in rat retina are comprised of ρ subunits.     

Ligand loading at the surface of an optical biosensor and its effect upon the kinetics of protein–protein interactions

Optical biosensors are finding increasing use in the determination of kinetic and equilibrium constants for a variety of biomolecular interactions. Usually these biosensors require one biomolecule, the ligand, to be covalently attached to a hydrogel matrix which itself is bonded to the sensing surface. The ligands partner, the ligate, then binds from solution resulting in a measurable change in response which the instrument records as a function of time. Although in many cases, optical biosensors are used in order to obtain parameters that relate to interactions in solution, it is becoming clear that measurements involving the interaction of ligate with immobilized ligands on surfaces require careful experimental design. Here we report on how the density of ligand loading within the hydogel matrix affects the measured interaction kinetics. It is found that crowding of ligand within this matrix results in a significant reduction in the measured association rate constant, with a corresponding effect in the calculated overall affinity. However, measurements at low ligand loadings show association rate constants that are comparable to those measured in solution. Clearly, where this comparison is required, it is important to perform measurements under such conditions. © 1997 John Wiley & Sons, Ltd.     

A single amino acid in the second transmembrane domain of GABA ρ subunits is a determinant of the response kinetics of GABAC receptors

The ρ subunits that constitute the γ‐aminobutyric acid (GABA)_C receptors of retinal neurons form a unique subclass of ligand‐gated chloride channels that give rise to sustained GABA‐evoked currents that exhibit slow offset (deactivation) kinetics. We exploited this property to examine the molecular mechanisms that govern the disparate response kinetics and pharmacology of perch GABA ρ1B and ρ2A subunits expressed in Xenopus oocytes. Using a combination of domain swapping and site‐directed mutagenesis, we identified the residues at amino acid position 320 in the second transmembrane domain as an important determinant of the receptor kinetics of GABA_C receptors. When the site contains a proline residue, as in wild‐type ρ1 subunits, the receptor deactivates slowly; when serine occupies the site, as in wild‐type ρ2 subunits, the time course of deactivation is more rapid. In addition, we found that the same site also altered the pharmacology of GABA ρ receptors, e.g., when the serine residue of the ρ2A receptor was changed to proline, the response of the mutant receptor to imidazole‐4‐acetic acid (I4AA) mimicked that of the ρ1B receptor. However, despite gross changes in receptor pharmacology, the apparent binding affinity for the drug was not significantly altered. These findings provide further evidence that the second transmembrane domain is involved in the gating mechanism that governs the response properties of the various ρ receptor subunits. It is noteworthy that the proline residue in native ρ1 subunits and the serine residue of ρ2 subunits are well conserved in all species, a good indication that the presence of multiple GABA ρ subunits serves to generate GABA_C receptors that display the wide range of response kinetics observed on various types of retinal neurons. © 1999 John Wiley & Sons, Inc. J Neurobiol 40: 67–76, 1999     

Discovery of binding proteins for a protein target using protein–protein docking‐based virtual screening

Target structure‐based virtual screening, which employs protein‐small molecule docking to identify potential ligands, has been widely used in small‐molecule drug discovery. In the present study, we used a protein–protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all‐to‐all protein–protein docking run on a large dataset was performed. The three‐dimensional rigid docking program SDOCK was used to examine protein–protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z‐score, and convergency of the low‐score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all‐to‐all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor‐α (TNFα), which is a well‐known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top‐ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein–protein docking for the discovery of novel binding proteins for specific protein targets. Proteins 2014; 82:2472–2482. © 2014 Wiley Periodicals, Inc.     

Electron‐deficient p‐benzoyl‐l‐phenylalanine derivatives increase covalent chemical capture yields for protein–protein interactions

The photoactivatable amino acid p‐benzoyl‐l ‐phenylalanine (pBpa) has been used for the covalent capture of protein–protein interactions (PPIs) in vitro and in living cells. However, this technique often suffers from poor photocrosslinking yields due to the low reactivity of the active species. Here we demonstrate that the incorporation of halogenated pBpa analogs into proteins leads to increased crosslinking yields for protein–protein interactions. The analogs can be incorporated into live yeast and upon irradiation capture endogenous PPIs. Halogenated pBpas will extend the scope of PPIs that can be captured and expand the toolbox for mapping PPIs in their native environment.     

Differential protein–protein interactions of LRRK1 and LRRK2 indicate roles in distinct cellular signaling pathways

Genetic studies show that LRRK2, and not its closest paralogue LRRK1, is linked to Parkinson's disease. To gain insight into the molecular and cellular basis of this discrepancy, we searched for LRRK1‐ and LRRK2‐specific cellular processes by identifying their distinct interacting proteins. A protein microarray‐based interaction screen was performed with recombinant 3xFlag‐LRRK1 and 3xFlag‐LRRK2 and, in parallel, co‐immunoprecipitation followed by mass spectrometry was performed from SH‐SY5Y neuroblastoma cell lines stably expressing 3xFlag‐LRRK1 or 3xFlag‐LRRK2. We identified a set of LRRK1‐ and LRRK2‐specific as well as common interactors. One of our most prominent findings was that both screens pointed to epidermal growth factor receptor (EGF‐R) as a LRRK1‐specific interactor, while 14‐3‐3 proteins were LRRK2‐specific. This is consistent with phosphosite mapping of LRRK1, revealing phosphosites outside of 14‐3‐3 consensus binding motifs. To assess the functional relevance of these interactions, SH‐SY5Y‐LRRK1 and ‐LRRK2 cell lines were treated with LRRK2 kinase inhibitors that disrupt 14‐3‐3 binding, or with EGF, an EGF‐R agonist. Redistribution of LRRK2, not LRRK1, from diffuse cytoplasmic to filamentous aggregates was observed after inhibitor treatment. Similarly, EGF induced translocation of LRRK1, but not of LRRK2, to endosomes. Our study confirms that LRRK1 and LRRK2 can carry out distinct functions by interacting with different cellular proteins.

     

Complex structure of cytochrome c–cytochrome c oxidase reveals a novel protein–protein interaction mode

Mitochondrial cytochrome c oxidase (CcO) transfers electrons from cytochrome c (Cyt.c) to O₂ to generate H₂O, a process coupled to proton pumping. To elucidate the mechanism of electron transfer, we determined the structure of the mammalian Cyt.c–CcO complex at 2.0‐Å resolution and identified an electron transfer pathway from Cyt.c to CcO. The specific interaction between Cyt.c and CcO is stabilized by a few electrostatic interactions between side chains within a small contact surface area. Between the two proteins are three water layers with a long inter‐molecular span, one of which lies between the other two layers without significant direct interaction with either protein. Cyt.c undergoes large structural fluctuations, using the interacting regions with CcO as a fulcrum. These features of the protein–protein interaction at the docking interface represent the first known example of a new class of protein–protein interaction, which we term “soft and specific”. This interaction is likely to contribute to the rapid association/dissociation of the Cyt.c–CcO complex, which facilitates the sequential supply of four electrons for the O₂ reduction reaction.     

Exploring the protein–protein interaction landscape in plants

Protein–protein interactions (PPIs) represent an essential aspect of plant systems biology. Identification of key protein players and their interaction networks provide crucial insights into the regulation of plant developmental processes and into interactions of plants with their environment. Despite the great advance in the methods for the discovery and validation of PPIs, still several challenges remain. First, the PPI networks are usually highly dynamic, and the in vivo interactions are often transient and difficult to detect. Therefore, the properties of the PPIs under study need to be considered to select the most suitable technique, because each has its own advantages and limitations. Second, besides knowledge on the interacting partners of a protein of interest, characteristics of the interaction, such as the spatial or temporal dynamics, are highly important. Hence, multiple approaches have to be combined to obtain a comprehensive view on the PPI network present in a cell. Here, we present the progress in commonly used methods to detect and validate PPIs in plants with a special emphasis on the PPI features assessed in each approach and how they were or can be used for the study of plant interactions with their environment.