Construction of reliable protein-protein interaction networks with a new interaction generality measure

MOTIVATION: Recent screening techniques have made large amounts of protein-protein interaction data available, from which biologically important information such as the function of uncharacterized proteins, the existence of novel protein complexes, and novel signal-transduction pathways can be discovered. However, experimental data on protein interactions contain many false positives, making these discoveries difficult. Therefore computational methods of assessing the reliability of each candidate protein-protein interaction are urgently needed. RESULTS: We developed a new 'interaction generality' measure (IG2) to assess the reliability of protein-protein interactions using only the topological properties of their interaction-network structure. Using yeast protein-protein interaction data, we showed that reliable protein-protein interactions had significantly lower IG2 values than less-reliable interactions, suggesting that IG2 values can be used to evaluate and filter interaction data to enable the construction of reliable protein-protein interaction networks.     

Delineating protein-protein interactions via biomolecular interaction analysis-mass spectrometry

The utility of biomolecular interaction analysis-mass spectrometry (BIA/MS) in screening for protein-protein interactions was explored in this work. Experiments were performed in which proteins served as ligands for screening of possible interactions with other proteins from human plasma and urine. The proteins utilized were beta-2-microglobulin, cystatin C (cysC), retinol binding protein (RBP), transthyretin (TTR), alpha-1-microglobulin, C-reactive protein, transferrin and papain. The immobilization of functionally active proteins was confirmed via interactions with antibodies to the corresponding proteins. Various dilutions of human urine and plasma were injected over the protein-derivatized surfaces. It was observed that the urine injections generally yielded smaller SPR responses than those observed after the plasma injections. The BIA/MS experiments did not reveal novel protein-protein interactions, although several established interactions (such as those between RBP and TTR, and cysC and papain) were validated. Few protein ligand deficiencies (such as truncations) leading to false negative and false positive BIA/MS results were also discovered.     

Development of a high-throughput yeast two-hybrid screening system to study protein-protein interactions in plants

We have developed a high-throughput yeast two-hybrid screening system (HTP-YTH) that incorporates yeast gap-repair cloning, multiple positive ( ADE2, HIS3, lacZ) and negative ( URA3-based) selection schemes to reduce the incidence of negative and false positive clones, and automation of laboratory procedures to increase throughput. This HTP-YTH system has been applied to the study of protein-protein interactions that are involved in rice defense signal transduction pathways. More than 100 genes involved in plant defense responses were selected from DuPont's rice expressed sequence tag (EST) databases as baits for HTP-YTH screening. Results from YTH screening of eight of these rice genes are presented in this paper. Not only have we identified known protein-protein interactions, but we have also discovered novel interactions, which may ultimately reveal the regulatory network of host defense signal transduction pathways. We have demonstrated that our HTP-YTH method can be used to map protein-protein interaction networks and signal transduction pathways in any system. In combination with other approaches, such efficient YTH screens can help us systemically to study the functions of known and unknown genes in the genomics era.     

Identification of VCP/p97, carboxyl terminus of Hsp70-interacting protein (CHIP), and amphiphysin II interaction partners using membrane-based human proteome arrays

Proteins mediate their biological function through interactions with other proteins. Therefore, the systematic identification and characterization of protein-protein interactions have become a powerful proteomic strategy to understand protein function and comprehensive cellular regulatory networks. For the screening of valosin-containing protein, carboxyl terminus of Hsp70-interacting protein (CHIP), and amphiphysin II interaction partners, we utilized a membrane-based array technology that allows the identification of human protein-protein interactions with crude bacterial cell extracts. Many novel interaction pairs such as valosin-containing protein/autocrine motility factor receptor, CHIP/caytaxin, or amphiphysin II/DLP4 were identified and subsequently confirmed by pull-down, two-hybrid and co-immunoprecipitation experiments. In addition, assays were performed to validate the interactions functionally. CHIP e.g. was found to efficiently polyubiquitinate caytaxin in vitro, suggesting that it might influence caytaxin degradation in vivo. Using peptide arrays, we also identified the binding motifs in the proteins DLP4, XRCC4, and fructose-1,6-bisphosphatase, which are crucial for the association with the Src homology 3 domain of amphiphysin II. Together these studies indicate that our human proteome array technology permits the identification of protein-protein interactions that are functionally involved in neurodegenerative disease processes, the degradation of protein substrates, and the transport of membrane vesicles.     

Methods for the detection and analysis of protein-protein interactions

A large number of methods have been developed over the years to study protein-protein interactions. Many of these techniques are now available to the nonspecialist researcher thanks to new affordable instruments and/or resource centres. A typical protein-protein interaction study usually starts with an initial screen for novel binding partners. We start this review by describing three techniques that can be used for this purpose: (i) affinity-tagged proteins (ii) the two-hybrid system and (iii) some quantitative proteomic techniques that can be used in combination with, e.g., affinity chromatography and coimmunoprecipitation for screening of protein-protein interactions. We then describe some public protein-protein interaction databases that can be searched to identify previously reported interactions for a given bait protein. Four strategies for validation of protein-protein interactions are presented: confocal microscopy for intracellular colocalization of proteins, coimmunoprecipitation, surface plasmon resonance (SPR) and spectroscopic studies. Throughout the review we focus particularly on the advantages and limitations of each method.     

Functional phosphosite screening for targeted protein-protein interactions by combining phosphoproteomics strategies and mammalian two-hybrid assays

An effective new platform for phosphosite mapping and subsequent functional screening was developed to analyze the targeted protein-protein interactions of p300 and CBP with β-catenin. Two novel functional phosphosites, Ser12 of p300 and Ser92 of CBP, were revealed to modulate p300/β-catenin and CBP/β-catenin interactions, respectively.     

Highly sensitive assays for SUMOylation and small ubiquitin-like modifier-dependent protein-protein interactions

Small ubiquitin-like proteins (SUMO) are recently discovered post-translational modifiers that regulate protein functions and intracellular trafficking. In this study, we are describing two chemoluminescence-based assays, one for SUMOylation and another one for SUMO-mediated protein-protein interactions. These assays can be used to characterize the activity and kinetics of the enzymes that catalyze SUMOylation, and in high-throughput screening for inhibitors of SUMOylation and SUMO-dependent protein-protein interactions. These novel assays represent the most sensitive assays for ubiquitin-like systems published to date. Similar strategies can be used to develop assays for other ubiquitin-like modification systems.     

Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods

Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.     

Gγ recruitment system incorporating a novel signal amplification circuit to screen transient protein-protein interactions

Weak and transient protein-protein interactions are associated with biological processes, but many are still undefined because of the difficulties in their identification. Here, we describe a redesigned method to screen transient protein-protein interactions by using a novel signal amplification circuit, which is incorporated into yeast to artificially magnify the signal responding to the interactions. This refined method is based on the previously established Gγ recruitment system, which utilizes yeast G-protein signaling and mating growth selection to screen interacting protein pairs. In the current study, to test the capability of our method, we chose mutants of the Z-domain derived from Staphylococcus aureus protein A as candidate proteins, and the Fc region of human IgG as the counterpart. By introduction of an artificial signal amplifier into the previous Gγ recruitment system, the signal transduction responding to transient interactions between Z-domain mutants and the Fc region with significantly low affinity (8.0 × 10(3) M(-1)) was successfully amplified in recombinant haploid yeast cells. As a result of zygosis with the opposite mating type of wild-type haploid cells, diploid colonies were vigorously and selectively generated on the screening plates, whereas our previous system rarely produced positive colonies. This new approach will be useful for exploring the numerous transient interactions that remain undefined because of the lack of powerful screening tools for their identification.     

Protein-protein interactions: principles, techniques, and their potential role in new drug development

A vast network of genes is inter-linked through protein-protein interactions and is critical component of almost every biological process under physiological conditions. Any disruption of the biologically essential network leads to pathological conditions resulting into related diseases. Therefore, proper understanding of biological functions warrants a comprehensive knowledge of protein-protein interactions and the molecular mechanisms that govern such processes. The importance of protein-protein interaction process is highlighted by the fact that a number of powerful techniques/methods have been developed to understand how such interactions take place under various physiological and pathological conditions. Many of the key protein-protein interactions are known to participate in disease-associated signaling pathways, and represent novel targets for therapeutic intervention. Thus, controlling protein-protein interactions offers a rich dividend for the discovery of new drug targets. Availability of various tools to study and the knowledge of human genome have put us in a unique position to understand highly complex biological network, and the mechanisms involved therein. In this review article, we have summarized protein-protein interaction networks, techniques/methods of their binding/kinetic parameters, and the role of these interactions in the development of potential tools for drug designing.     

PEPPI: Whole-proteome Protein-protein Interaction Prediction through Structure and Sequence Similarity,Functional Association,and Machine Learning

Proteome-wide identification of protein-protein interactions is a formidable task which has yet to be sufficiently addressed by experimental methodologies. Many computational methods have been developed to predict proteome-wide interaction networks, but few leverage both the sensitivity of structural information and the wide availability of sequence data. We present PEPPI, a pipeline which integrates structural similarity, sequence similarity, functional association data, and machine learning-based classification through a naïve Bayesian classifier model to accurately predict protein-protein interactions at a proteomic scale. Through benchmarking against a set of 798 ground truth interactions and an equal number of non-interactions, we have found that PEPPI attains 4.5% higher AUROC than the best of other state-of-the-art methods. As a proteomic-scale application, PEPPI was applied to model the interactions which occur between SARS-CoV-2 and human host cells during coronavirus infection, where 403 high-confidence interactions were identified with predictions covering 73% of a gold standard dataset from PSICQUIC and demonstrating significant complementarity with the most recent high-throughput experiments. PEPPI is available both as a webserver and in a standalone version and should be a powerful and generally applicable tool for computational screening of protein-protein interactions.     

Detection and identification of plasma proteins that bind GlialCAM using ProteinChip arrays, SELDI-TOF MS, and nano-LC MS/MS

In order to fully understand biological processes it is essential to identify interactions in protein complexes. There are several techniques available to study this type of interactions, such as yeast two-hybrid screens, affinity chromatography, and coimmunoprecipitation. We propose a novel strategy to identify protein-protein interactions, comprised of first detecting the interactions using ProteinChips and SELDI-TOF MS, followed by the isolation of the interacting proteins through affinity beads and RP-HPLC and finally identifying the proteins using nano-LC MS/MS. The advantages of this new strategy are that the primary high-throughput screening of samples can be performed with small amounts of sample, no specific antibody is needed and the proteins represented on the SELDI-TOF MS spectra can be identified with high confidence. Furthermore, the method is faster and less labor-intensive than other current approaches. Using this novel method, we isolated and identified the interactions of two mouse plasma proteins, mannose binding lectin C and properdin, with GlialCAM, a type 1 transmembrane glycoprotein that belongs to the Ig superfamily.     

Prediction of protein-protein interactions: the CAPRI experiment, its evaluation and implications

Given the increasing interest in protein-protein interactions, the prediction of these interactions from sequence and structural information has become a booming activity. CAPRI, the community-wide experiment for assessing blind predictions of protein-protein interactions, is playing an important role in fostering progress in docking procedures. At the same time, novel methods are being derived for predicting regions of a protein that are likely to interact and for characterizing putative intermolecular contacts from sequence and structural data. Together with docking procedures, these methods provide an integrated computational approach that should be a valuable complement to genome-scale experimental studies of protein-protein interactions.     

Protein-Protein Interactions: Principles,Techniques, and their Potential Role in New Drug Development

Abstract

A vast network of genes is inter-linked through protein-protein interactions and is critical component of almost every biological process under physiological conditions. Any disruption of the biologically essential network leads to pathological conditions resulting into related diseases. Therefore, proper understanding of biological functions warrants a comprehensive knowledge of protein-protein interactions and the molecular mechanisms that govern such processes. The importance of protein-protein interaction process is highlighted by the fact that a number of powerful techniques/methods have been developed to understand how such interactions take place under various physiological and pathological conditions. Many of the key protein-protein interactions are known to participate in disease-associated signaling pathways, and represent novel targets for therapeutic intervention. Thus, controlling protein-protein interactions offers a rich dividend for the discovery of new drug targets. Availability of various tools to study and the knowledge of human genome have put us in a unique position to understand highly complex biological network, and the mechanisms involved therein. In this review article, we have summarized protein-protein interaction networks, techniques/methods of their binding/kinetic parameters, and the role of these interactions in the development of potential tools for drug designing.     

ProteoChip: a highly sensitive protein microarray prepared by a novel method of protein immobilization for application of protein-protein interaction studies

We have developed a highly sensitive microarray protein chip, ProteoChip, coated with ProLinker, novel calixcrown derivatives with a bifunctional coupling property that permits efficient immobilization of capture proteins on solid matrixes and makes high-throughput analysis of protein-protein interactions possible. The analysis of quartz crystal microbalance showed that both monoclonal antibody (mAb) and antigen (Ag) bound to the gold film of the sensor surface coated with ProLinker B and that it is useful for studies of Ab-Ag interactions. ProteoChip, aminated glass slide coated with ProLinker A, was also demonstrated to be useful for preparation of high-density array spots by using a microarrayer and for analysis of analyte Ags either by direct or sandwich methods of fluorescence immunoassay. The detection sensitivity of ProteoChip was as low as 1-10 femtogram/mL of analyte protein, useful for detection of tumor markers. ProteoChip was also useful for studies of direct protein-protein interactions as demonstrated by analysis of integrin-extracellular matrix protein interaction. These experimental results suggest that ProteoChip is a powerful tool for development of chip-based lead screening microarrays to monitor protein-protein interactions (i.e. drug target) as well as for biomarker assays which require high detection sensitivity.     

Improving yeast two-hybrid screening systems.

Yeast two-hybrid (Y2H) screening methods are an effective means for the detection of protein-protein interactions. Optimisation and automation has increased the throughput of the method to an extent that allows the systematic mapping of protein-protein interactions on a proteome-wide scale. Since two-hybrid screens fail to detect a great number of interactions, parallel high-throughput approaches are needed for proteome-wide interaction screens. In this review, we discuss and compare different approaches for adaptation of Y2H screening to high-throughput, the limits of the method and possible alternative approaches to complement the mapping of organism-wide protein-protein interactions.     

Genetic approaches to the identification of interactions between membrane proteins in yeast

The recent sequencing of entire eukaryotic genomes has renewed the interest in identifying and characterizing all gene products that are expressed in a given organism. The characterization of unknown gene products is facilitated by the knowledge of its binding partners. Thus, a novel protein may be classified by identifying previously characterized proteins that interact with it. If such an approach is carried out on a large scale, it may allow the rapid characterization of the thousands of predicted open reading frames identified by recent sequencing projects. Currently, the yeast two-hybrid system is the most widely used genetic assay for the detection of protein-protein interactions. The yeast two-hybrid system has become popular because it requires little individual optimization and because, as compared to conventional biochemical methods, the identification and characterization of protein-protein interactions can be completed in a relatively short time span. In this review, we briefly discuss the yeast two-hybrid system and its application to large scale screening studies that aim at deciphering all protein-protein interactions taking place in a given cell type or organism. We then focus on a class of proteins that is unsuitable for conventional yeast two-hybrid systems, namely integral membrane proteins and membrane-associated proteins, and describe several novel genetic systems that combine the advantages of the yeast two-hybrid system with the potential to identify interaction partners of membrane-associated proteins in their natural setting.     

A high efficiency strategy for binding property characterization of peptide-binding domains

A large proportion of protein-protein interactions is mediated by families of peptide-binding domains. Comprehensive characterization of each of these domains is critical for understanding the mechanisms and networks of protein interaction at the domain level. However, existing methods are all based on large scale screenings for each domain that are inefficient to deal with hundreds of members in major domain families. We developed a systematic strategy for efficient binding property characterization of peptide-binding domains based on high throughput validation screening of a specialized candidate ligand library using yeast two-hybrid mating array. Its outstanding feature is that the overall efficiency is dramatically improved compared with that of traditional screening, and it will be higher as the system cycles. PDZ domain family was first used to test the strategy. Five PDZ domains were rapidly characterized. Broader binding properties were identified compared with other methods, including novel recognition specificities that provided the basis for major revision of conventional PDZ classification. Several novel interactions were discovered, serving as significant clues for further functional investigation. This strategy can be easily extended to a variety of peptide-binding domains as a powerful tool for comprehensive analysis of domain binding property in proteomic scale.