A novel mammalian display system for the selection of protein-protein interactions by decoy receptor engagement

The emerging field of proteomics has created a need for new high-throughput methodologies for the analysis of gene products. An attractive approach is to develop systems that allow for clonal selection of interacting protein pairs from large molecular libraries. In this study, we have characterized a novel approach for identification and selection of protein-protein interactions, denoted SPIRE (selection of protein interactions by receptor engagement), which is based on a mammalian expression system. We have demonstrated proof of concept by creating a general plasma membrane bound decoy receptor, by displaying a protein or a peptide genetically fused to a trunctated version of the CD40 molecule. When this decoy receptor is engaged by a ligand to the displayed protein/peptide, the receptor expressing cell is rescued from apoptosis. To design a high-throughput system with a highly parallel capacity, we utilized the B cell line WEHI-231, as carrier of the decoy receptor. One specific peptide-displaying cell could be identified and amplified, based on a specific receptor engagement, in a background of 12 500 wild-type cells after four selections. This demonstrates that the approach may serve as a tool in post-genomic research for identifying protein-protein interactions, without prior knowledge of either component.     

Genetic selection for dissociative inhibitors of designated protein-protein interactions

Many biological processes rely on protein-protein interactions. These processes include signal transduction, cell cycle regulation, gene regulation, and viral assembly and replication. Moreover, many proteins and enzymes manifest their function as oligomers. We describe here an efficient means to sift through large combinatorial libraries and identify molecules that block the interaction of target proteins in vivo. The power of this approach is demonstrated by the identification of nine-residue peptides from a combinatorial library that inhibit the intracellular dimerization of HIV-1 protease. Fewer than 1 in 106 peptides do so. In vitro biochemical analyses of one such peptide demonstrate that it acts by dissociating HIV-1 protease into monomers, which are inactive catalysts. Inhibition is enhanced further by dimerizing the peptide. This approach enables the facile identification of new molecules that control cellular processes.     

蛋白质间相互作用研究技术进展

蛋白质组是后基因组时代出现的一个新兴研究领域,而蛋白质间相互作用的研究是蛋白质组研究的一个重要方面。简要介绍了蛋白质间相互作用的研究手段及最新进展。     

Blotting and band-shifting: techniques for studying protein-protein interactions.

The type II cAMP-dependent protein kinase (PKA) is localized in certain cellular compartments through association with specific A-kinase anchoring proteins (AKAPs). A variety of blotting and electrophoresis techniques have been developed to study the protein-protein interactions that occur between the regulatory (R) subunit of PKA and AKAPs. These methods have also been used for a variety of purposes such as detecting calmodulin-binding proteins, comparing wild-type- and mutant-form binding affinities and estimating the molecular weight of multiprotein complexes.     

An in vivo library-versus-library selection of optimized protein-protein interactions.

We describe a rapid and efficient in vivo library-versus-library screening strategy for identifying optimally interacting pairs of heterodimerizing polypeptides. Two leucine zipper libraries, semi-randomized at the positions adjacent to the hydrophobic core, were genetically fused to either one of two designed fragments of the enzyme murine dihydrofolate reductase (mDHFR), and cotransformed into Escherichia coli. Interaction between the library polypeptides reconstituted enzymatic activity of mDHFR, allowing bacterial growth. Analysis of the resulting colonies revealed important biases in the zipper sequences relative to the original libraries, which are consistent with selection for stable, heterodimerizing pairs. Using more weakly associating mDHFR fragments, we increased the stringency of selection. We enriched the best-performing leucine zipper pairs by multiple passaging of the pooled, selected colonies in liquid culture, as the best pairs allowed for better bacterial propagation. This competitive growth allowed small differences among the pairs to be amplified, and different sequence positions were enriched at different rates. We applied these selection processes to a library-versus-library sample of 2.0 x 10(6) combinations and selected a novel leucine zipper pair that may be appropriate for use in further in vivo heterodimerization strategies.     

A phage display system designed to detect and study protein-protein interactions.

Analysing protein-protein interactions is critical in proteomics and drug discovery. The usage of 2-Hybrid (2lambda) systems is limited to an in vivo environment. We describe a bacteriophage 2-Hybrid system for studying protein interactions in vitro. Bait and prey are displayed as fusions to the surface of phage lambda that are marked with different selectable drug-resistant markers. An interaction of phages in vitro through displayed proteins allows bacterial infection by two phages resulting in double drug-resistant bacterial colonies at very low multiplicity of infections. We demonstrate interaction of the protein sorting signal Ubiquitin with the Vps9-CUE, a Ubiquitin binding domain, and by the interaction of (Gly-Glu)(4) and (Gly-Arg)(4) peptides. Interruptions of the phage interactions by non-fused (free) bait or prey molecules show how robust and unique our approach is. We also demonstrate the use of Ubiquitin and CUE display phages to find binding partners in a lambda-display library. The unique usefulness to 2lambda is also described.     

Lipid-assisted protein-protein interactions that support photosynthetic and other cellular activities

Glycoglycerolipids are dominant lipids of photosynthetic organisms, i.e. higher plants and cyanobacteria. X-ray crystallographic localization of glycerolipids revealed that they are present at functionally and structurally important sites of both the PS I and PS II reaction centres. Phosphatidylglycerol (PG) is an indispensible member of glycerolipids, including the formation of functionally active oligomers of the reaction centres both PS I and PS II. Lipids assist in the assembly of protein subunits of the photosynthetic machinery by pasting the individual protein components together. PG is needed to glue CP43 to the reaction centre core. PG and digalactosyldiacylglycerol (DGDG) interact in photosynthetic processes: PG alone controls electron transport at the acceptor site of PS II, and together with DGDG is involved in electron transport at the donor site of PS II. PG is crucial for the formation of division rings and is implicated in the fission of cyanobacteria.     

In vitro selection of Jun-associated proteins using mRNA display

Although yeast two-hybrid assay and biochemical methods combined with mass spectrometry have been successfully employed for the analyses of protein–protein interactions in the field of proteomics, these methods encounter various difficulties arising from the usage of living cells, including inability to analyze toxic proteins and restriction of testable interaction conditions. Totally in vitro display technologies such as ribosome display and mRNA display are expected to circumvent these difficulties. In this study, we applied an mRNA display technique to screening for interactions of a basic leucine zipper domain of Jun protein in a mouse brain cDNA library. By performing iterative affinity selection and sequence analyses, we selected 16 novel Jun-associated protein candidates in addition to four known interactors. By means of real-time PCR and pull-down assay, 10 of the 16 newly discovered candidates were confirmed to be direct interactors with Jun in vitro. Furthermore, interaction of 6 of the 10 proteins with Jun was observed in cultured cells by means of co-immunoprecipitation and observation of subcellular localization. These results demonstrate that this in vitro display technology is effective for the discovery of novel protein–protein interactions and can contribute to the comprehensive mapping of protein–protein interactions.     

Elucidation of protein-protein interactions using chemical cross-linking or label transfer techniques

Understanding the architectures of multiprotein complexes is a central problem in biology. Of the many chemical methods available, label transfer and cross-linking are becoming more popular. Recently, label transfer has been applied to very large protein complexes with great success, and new oxidative methods for protein cross-linking have been developed that are fast and highly efficient. Advances in these techniques should increase the understanding of biological structures and mechanisms.     

Mining literature for protein-protein interactions

MOTIVATION: A central problem in bioinformatics is how to capture information from the vast current scientific literature in a form suitable for analysis by computer. We address the special case of information on protein-protein interactions, and show that the frequencies of words in Medline abstracts can be used to determine whether or not a given paper discusses protein-protein interactions. For those papers determined to discuss this topic, the relevant information can be captured for the Database of Interacting PROTEINS: Furthermore, suitable gene annotations can also be captured. RESULTS: Our Bayesian approach scores Medline abstracts for probability of discussing the topic of interest according to the frequencies of discriminating words found in the abstract. More than 80 discriminating words (e.g. complex, interaction, two-hybrid) were determined from a training set of 260 Medline abstracts corresponding to previously validated entries in the Database of Interacting Proteins. Using these words and a log likelihood scoring function, approximately 2000 Medline abstracts were identified as describing interactions between yeast proteins. This approach now forms the basis for the rapid expansion of the Database of Interacting Proteins.     

Diversity of protein-protein interactions

In this review, we discuss the structural and functional diversity of protein-protein interactions (PPIs) based primarily on protein families for which three-dimensional structural data are available. PPIs play diverse roles in biology and differ based on the composition, affinity and whether the association is permanent or transient. In vivo, the protomer's localization, concentration and local environment can affect the interaction between protomers and are vital to control the composition and oligomeric state of protein complexes. Since a change in quaternary state is often coupled with biological function or activity, transient PPIs are important biological regulators. Structural characteristics of different types of PPIs are discussed and related to their physiological function, specificity and evolution.     

Targeting protein-protein interactions for parasite control

Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs) offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank). EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite) and B. malayi (H. sapiens parasite), which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly applicable.     

A lock-and-key model for protein-protein interactions

MOTIVATION: Protein-protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism's proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs, and also to identify potentially missing or spurious interactions. RESULTS: Our new graph model explains observed interactions between proteins by an underlying interaction of complementary binding domains (lock-and-key model). This leads to a novel graph-theoretical algorithm to identify bipartite subgraphs within protein-protein interaction networks where the underlying data are taken from yeast two-hybrid experimental results. By testing on synthetic data, we demonstrate that under certain modelling assumptions, the algorithm will return correct domain information about each protein in the network. Tests on data from various model organisms show that the local and global patterns predicted by the model are indeed found in experimental data. Using functional and protein structure annotations, we show that bipartite subnetworks can be identified that correspond to biologically relevant interaction motifs. Some of these are novel and we discuss an example involving SH3 domains from the Saccharomyces cerevisiae interactome. AVAILABILITY: The algorithm (in Matlab format) is available (see http://www.maths.strath.ac.uk/~aas96106/lock_key.html).     

Biochemical approaches for discovering protein-protein interactions

Protein–protein interactions or protein complexes are integral in nearly all cellular processes, ranging from metabolism to structure. Elucidating both individual protein associations and complex protein interaction networks, while challenging, is an essential goal of functional genomics. For example, discovering interacting partners for a 'protein of unknown function' can provide insight into actual function far beyond what is possible with sequence-based predictions, and provide a platform for future research. Synthetic genetic approaches such as two-hybrid screening often reveal a perplexing array of potential interacting partners for any given target protein. It is now known, however, that this type of anonymous screening approach can yield high levels of false-positive results, and therefore putative interactors must be confirmed by independent methods. In vitro biochemical strategies for identifying interacting proteins are varied and time-honored, some being as old as the field of protein chemistry itself. Herein we discuss five biochemical approaches for isolating and characterizing protein–protein interactions in vitro : co-immunoprecipitation, blue native gel electrophoresis, in vitro binding assays, protein cross-linking, and rate-zonal centrifugation. A perspective is provided for each method, and where appropriate specific, trial-tested methods are included.     

Rapid antibody selection by mRNA display on a microfluidic chip

In vitro antibody-display technologies are powerful approaches for isolating monoclonal antibodies from recombinant antibody libraries. However, these display techniques require several rounds of affinity selection which is time-consuming. Here, we combined mRNA display with a microfluidic system for in vitro selection and evolution of antibodies and achieved ultrahigh enrichment efficiency of 10⁶- to 10⁸-fold per round. After only one or two rounds of selection, antibodies with high affinity and specificity were obtained from naïve and randomized single-chain Fv libraries of ~10¹² molecules. Furthermore, we confirmed that not only protein–protein (antigen–antibody) interactions, but also protein–DNA and protein–drug interactions were selected with ultrahigh efficiencies. This method will facilitate high-throughput preparation of antibodies and identification of protein interactions in proteomic and therapeutic fields.     

Principles of protein-protein interactions

In the postgenomic era, one of the most interesting and important challenges is to understand protein interactions on a large scale. The physical interactions between protein domains are fundamental to the workings of a cell: in multi-domain polypeptide chains, in multi-subunit proteins and in transient complexes between proteins that also exist independently. Thus experimental investigation of protein-protein interactions has been extensive, including recent large-scale screens using mass spectrometry. The role of computational research on protein-protein interactions encompasses not only prediction, but also understanding the nature of the interactions and their three-dimensional structures. I will discuss properties such as sequence conservation and co-regulation of genes and proteins involved in different types of physical interactions. Given that all proteins consist of their evolutionary units, the domains, all interactions occur between these domains. The interactions between domains belonging to different protein families will be the second topic of my talk.