Baculovirus display for discovery of low-affinity extracellular receptor–ligand interactions using protein microarrays

When used in conjunction with multivalent protein probes, protein microarrays offer a robust technology for discovery of low-affinity extracellular protein–protein interactions. Probes for receptor-matching screens generally consist of purified extracellular domains fused to affinity tags. Given that approximately two-thirds of extracellular proteins are transmembrane domain-containing proteins, it would be desirable to develop a system to express and display probe receptors in a native-like membrane environment. Toward this end, we evaluated baculovirus display as a platform for generating multivalent probes for protein microarray screens. Virion particles were generated displaying single-transmembrane domain receptors BTLA, CD200, and EFNB2, representing a range of affinities for their interacting partners. Virions directly labeled with Cy5 fluorophore were screened against a microarray containing more than 600 extracellular proteins, and the results were compared with data derived from soluble Fc protein or probe-coated protein A microbeads. An optimized protocol employing a blocking step with a nonrelated probe-expressing control baculovirus allowed identification of the expected interactions with a signal-to-noise ratio similar to or higher than those obtained with the other formats. Our results demonstrate that baculovirus display is suitable for detection of high- and low-affinity extracellular protein–protein interactions on protein microarrays. This platform eliminates the need for protein purification and provides a native-like lipid environment for membrane-associated receptors.     

Systems for the detection and analysis of protein–protein interactions

The analysis of protein–protein interactions is important for developing a better understanding of the functional annotations of proteins that are involved in various biochemical reactions in vivo. The discovery that a protein with an unknown function binds to a protein with a known function could provide a significant clue to the cellular pathway concerning the unknown protein. Therefore, information on protein–protein interactions obtained by the comprehensive analysis of all gene products is available for the construction of interactive networks consisting of individual protein–protein interactions, which, in turn, permit elaborate biological phenomena to be understood. Systems for detecting protein–protein interactions in vitro and in vivo have been developed, and have been modified to compensate for limitations. Using these novel approaches, comprehensive and reliable information on protein–protein interactions can be determined. Systems that permit this to be achieved are described in this review.K. Kuroda, M. Kato and J. Mima contributed equally to this work.     

Mapping protein–ligand interactions using whole genome phage display libraries

The function of many genes cannot be deduced from sequence similarity, and biochemical methods are usually required. Whole genome sequences can be thought of as not only a set of genes but also collections of functional domains. These domains can be studied by affinity methods whereby identification of the ligand can provide information on biochemical function. To take advantage of this method, one must express all functional domains in a form suitable for affinity studies. Phage display technology provides a means for accomplishing this. The pJuFo phage display system, based on the interaction between the leucine zippers Jun and Fos, has been modified and used to create a genomic phage display library from Escherichia coli MG1655. The system has been tested by using the library to map the dominant binding epitopes for an anti-RecA protein polyclonal antibody sera. This methodology provides a general biochemical approach to functional analysis of protein–ligand interactions on a genome-wide basis.     

Advantages of mRNA display selections over other selection techniques for investigation of protein–protein interactions

mRNA display is a genotype–phenotype conjugation method that allows for amplification-based, iterative rounds of in vitro selection to be applied to peptides and proteins. mRNA display can be used to display both long natural protein and short synthetic peptide libraries with unusually high diversities for the investigation of protein–protein interactions. Here, we summarize the advantages of mRNA display by comparing it with other widely used peptide or protein-selection techniques, and discuss various applications of this technique in studying protein–protein interactions.     

Helix-mediated protein–protein interactions as targets for intervention using foldamers

Protein–protein interactions (PPIs) play a central role in virtually all biological processes and have been the focus of intense investigation from structural molecular biology to cell biology for the majority of the last two decades and, more recently, are emerging as important targets for pharmaceutical intervention. A common motif found at the interface of PPIs is the α-helix, suggesting that, in the same way as the “lock and key” model has evolved for competitive inhibition of enzymes, it should be possible to elaborate “rule-based” approaches for inhibition of helix-mediated PPIs. This review will describe the biological function and structural features of a series of representative helix-mediated PPIs and discuss approaches that are being developed to target these interactions with small molecules that employ non-natural amino acids.     

Two-hybrid-based analysis of protein–protein interactions of the yeast multidrug resistance protein, Pdr5p

The ATP-binding cassette (ABC) transporters are a large family of proteins responsible for the translocation of a variety of compounds across the membranes of both prokaryotes and eukaryotes. The inter-protein and intra-protein interactions in these traffic ATPases are still only poorly understood. In the present study we describe, for the first time, an extensive yeast two-hybrid (Y2H)-based analysis of the interactions of the cytoplasmic loops of the yeast pleiotropic drug resistance (Pdr) protein, Pdr5p, an ABC transporter of Saccharomyces cerevisiae. Four of the major cytosolic loops that have been predicted for this protein [including the two nucleotide-binding domain (NBD)-containing loops and the cytosolic C-terminal region] were subjected to an extensive inter-domain interaction study in addition to being used as baits to identify potential interacting proteins within the cell using the Y2H system. Results of these studies have revealed that the first cytosolic loop (CL1) – containing the first NBD domain – and also the C-terminal region of Pdr5p interact with several candidate proteins. The possibility of an interaction between the CL1 loops of two neighboring Pdr5p molecules was also indicated, which could possibly have implications for dimerization of this protein. Electronic Publication     

Scoring functions for protein–protein interactions

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Hot spot-based design of small-molecule inhibitors for protein–protein interactions

Protein–protein interactions (PPIs) are important targets for the development of chemical probes and therapeutic agents. From the initial discovery of the existence of hot spots at PPI interfaces, it has been proposed that hot spots might provide the key for developing small-molecule PPI inhibitors. However, there has been no review on the ways in which the knowledge of hot spots can be used to achieve inhibitor design, nor critical examination of successful examples. This Digest discusses the characteristics of hot spots and the identification of druggable hot spot pockets. An analysis of four examples of hot spot-based design reveals the importance of this strategy in discovering potent and selective PPI inhibitors. A general procedure for hot spot-based design of PPI inhibitors is outlined.     

Predicting protein–protein interactions from protein sequences using meta predictor

A novel method is proposed for predicting protein–protein interactions (PPIs) based on the meta approach, which predicts PPIs using support vector machine that combines results by six independent state-of-the-art predictors. Significant improvement in prediction performance is observed, when performed on Saccharomyces cerevisiae and Helicobacter pylori datasets. In addition, we used the final prediction model trained on the PPIs dataset of S. cerevisiae to predict interactions in other species. The results reveal that our meta model is also capable of performing cross-species predictions. The source code and the datasets are available at     

Identification of antisense RNA stem–loops that inhibit RNA–protein interactions using a bacterial reporter system

Many well-characterized examples of antisense RNAs from prokaryotic systems involve hybridization of the looped regions of stem–loop RNAs, presumably due to the high thermodynamic stability of the resulting loop–loop and loop–linear interactions. In this study, the identification of RNA stem–loops that inhibit U1A protein binding to the hpII RNA through RNA–RNA interactions was attempted using a bacterial reporter system based on phage λ N-mediated antitermination. As a result, loop sequences possessing 7–8 base complementarity to the 5′ region of the boxA element important for functional antitermination complex formation, but not the U1 hpII loop, were identified. In vitro and in vivo mutational analysis strongly suggested that the selected loop sequences were binding to the boxA region, and that the structure of the antisense stem–loop was important for optimal inhibitory activity. Next, in an attempt to demonstrate the ability to inhibit the interaction between the U1A protein and the hpII RNA, the rational design of an RNA stem–loop that inhibits U1A-binding to a modified hpII was carried out. Moderate inhibitory activity was observed, showing that it is possible to design and select antisense RNA stem–loops that disrupt various types of RNA–protein interactions.     

Current trends in endotoxin detection and analysis of endotoxin–protein interactions

Endotoxin is a type of pyrogen that can be found in Gram-negative bacteria. Endotoxin can form a stable interaction with other biomolecules thus making its removal difficult especially during the production of biopharmaceutical drugs. The prevention of endotoxins from contaminating biopharmaceutical products is paramount as endotoxin contamination, even in small quantities, can result in fever, inflammation, sepsis, tissue damage and even lead to death. Highly sensitive and accurate detection of endotoxins are keys in the development of biopharmaceutical products derived from Gram-negative bacteria. It will facilitate the study of the intermolecular interaction of an endotoxin with other biomolecules, hence the selection of appropriate endotoxin removal strategies. Currently, most researchers rely on the conventional LAL-based endotoxin detection method. However, new methods have been and are being developed to overcome the problems associated with the LAL-based method. This review paper highlights the current research trends in endotoxin detection from conventional methods to newly developed biosensors. Additionally, it also provides an overview of the use of electron microscopy, dynamic light scattering (DLS), fluorescence resonance energy transfer (FRET) and docking programs in the endotoxin–protein analysis.     

Peptide-based covalent inhibitors of protein–protein interactions

Protein–protein interactions (PPI) are involved in all cellular processes and many represent attractive therapeutic targets. However, the frequently rather flat and large interaction areas render the identification of small molecular PPI inhibitors very challenging. As an alternative, peptide interaction motifs derived from a PPI interface can serve as starting points for the development of inhibitors. However, certain proteins remain challenging targets when applying inhibitors with a competitive mode of action. For that reason, peptide-based ligands with an irreversible binding mode have gained attention in recent years. This review summarizes examples of covalent inhibitors that employ peptidic binders and have been tested in a biological context.