Applications of Protein Fragment Complementation Assays for Analyzing Biomolecular Interactions and Biochemical Networks in Living Cells.

Protein-protein interactions (PPIs) are indispensable for the dynamic assembly of multiprotein complexes that are central players of nearly all of the intracellular biological processes, such as signaling pathways, metabolic pathways, formation of intracellular organelles, establishment of cytoplasmic skeletons, etc. Numerous approaches have been invented to study PPIs both in vivo and in vitro, including the protein-fragment complementation assay (PCA), which is a widely applied technology to study PPIs and biomolecular interactions. PCA is a technology based on the expression of the bait and prey proteins in fusion with two complementary reporter protein fragments, respectively, that will reassemble when in close proximity. The reporter protein can be the enzymes or fluorescent proteins. Recovery of the enzymatic activity or fluorescent signal can be the indicator of PPI between the bait and prey proteins. Significant effort has been invested in developing many derivatives of PCA, along with various applications, in order to address specific questions. Therefore, a prompt review of these applications is important. In this review, we will categorize these applications according to the scenarios that the PCAs were applied and expect to provide a reference guideline for the future selection of PCA methods in solving a specific problem.

A decade of Nucleic Acid Programmable Protein Arrays (NAPPA) availability: News, actors, progress, prospects and access.

Understanding the dynamic of the proteome is a critical challenge because it requires high sensitive methodologies in high-throughput formats in order to decipher its modifications and complexity. While molecular biology provides relevant information about cell physiology that may be reflected in post-translational changes, High-Throughput (HT) experimental proteomic techniques are essential to provide valuable functional information of the proteins, peptides and the interconnections between them. Hence, many methodological developments and innovations have been reported during the last decade. To study more dynamic protein networks and fine interactions, Nucleic Acid Programmable Protein Arrays (NAPPA) was introduced a decade ago. The tool is rapidly maturing and serving as a gateway to characterize biological systems and diseases thanks primarily to its accuracy, reproducibility, throughput and flexibility. Currently, NAPPA technology has proved successful in several research areas adding valuable information towards innovative diagnostic and therapeutic applications. Here, the basic and latest advances within this modern technology in basic, translational research are reviewed, in addition to presenting its exciting new directions. Our final goal is to encourage more scientists/researchers to incorporate this method, which can help to remove bottlenecks in their particular research or biomedical projects. SIGNIFICANCE: Nucleic Acid Programmable Protein Arrays (NAPPA) is becoming an essential tool for functional proteomics and protein-protein interaction studies. The technology impacts decisively on projects aiming massive screenings and the latest innovations like the multiplexing capability or printing consistency make this a promising method to be integrated in novel and combinatorial proteomic approaches.

Cross-Linking/Mass Spectrometry for Studying Protein Structures and Protein-Protein Interactions: Where Are We Now and Where Should We Go from Here?

Structural mass spectrometry (MS) is gaining increasing importance for deriving valuable three-dimensional structural information on proteins and protein complexes, and it complements existing techniques, such as NMR spectroscopy and X-ray crystallography. Structural MS unites different MS-based techniques, such as hydrogen/deuterium exchange, native MS, ion-mobility MS, protein footprinting, and chemical cross-linking/MS, and it allows fundamental questions in structural biology to be addressed. In this Minireview, I will focus on the cross-linking/MS strategy. This method not only delivers tertiary structural information on proteins, but is also increasingly being used to decipher protein interaction networks, both in vitro and in vivo. Cross-linking/MS is currently one of the most promising MS-based approaches to derive structural information on very large and transient protein assemblies and intrinsically disordered proteins.

Protein-protein interaction predictions using text mining methods.

It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools.

Current innovations and future challenges of network motif detection.

Network motif detection is the search for statistically overrepresented subgraphs present in a larger target network. They are thought to represent key structure and control mechanisms. Although the problem is exponential in nature, several algorithms and tools have been developed for efficiently detecting network motifs. This work analyzes 11 network motif detection tools and algorithms. Detailed comparisons and insightful directions for using these tools and algorithms are discussed. Key aspects of network motif detection are investigated. Network motif types and common network motifs as well as their biological functions are discussed. Applications of network motifs are also presented. Finally, the challenges, future improvements and future research directions for network motif detection are also discussed.

Signal transduction: From the atomic age to the post-genomic era.

We have come a long way in the 55 years since Edmond Fischer and the late Edwin Krebs discovered that the activity of glycogen phosphorylase is regulated by reversible protein phosphorylation. Many of the fundamental molecular mechanisms that operate in biological signaling have since been characterized and the vast web of interconnected pathways that make up the cellular signaling network has been mapped in considerable detail. Nonetheless, it is important to consider how fast this field is still moving and the issues at the current boundaries of our understanding. One must also appreciate what experimental strategies have allowed us to attain our present level of knowledge. We summarize here some key issues (both conceptual and methodological), raise unresolved questions, discuss potential pitfalls, and highlight areas in which our understanding is still rudimentary. We hope these wide-ranging ruminations will be useful to investigators who carry studies of signal transduction forward during the rest of the 21st century.

Split-luciferase complementary assay: applications, recent developments, and future perspectives.

Bioluminescent systems are considered as potent reporter systems for bioanalysis since they have specific characteristics, such as relatively high quantum yields and photon emission over a wide range of colors from green to red. Biochemical events are mostly accomplished through large protein machines. These molecular complexes are built from a few to many proteins organized through their interactions. These protein-protein interactions are vital to facilitate the biological activity of cells. The split-luciferase complementation assay makes the study of two or more interacting proteins possible. In this technique, each of the two domains of luciferase is attached to each partner of two interacting proteins. On interaction of those proteins, luciferase fragments are placed close to each other and form a complemented luciferase, which produces a luminescent signal. Split luciferase is an effective tool for assaying biochemical metabolites, where a domain or an intact protein is inserted into an internally fragmented luciferase, resulting in ligand binding, which causes a change in the emitted signals. We review the various applications of this novel luminescent biosensor in studying protein-protein interactions and assaying metabolites involved in analytical biochemistry, cell communication and cell signaling, molecular biology, and the fate of the whole cell, and show that luciferase-based biosensors are powerful tools that can be applied for diagnostic and therapeutic purposes.

Coverage of protein domain families with structural protein-protein interactions: current progress and future trends.

Protein interactions have evolved into highly precise and regulated networks adding an immense layer of complexity to cellular systems. The most accurate atomistic description of protein binding sites can be obtained directly from structures of protein complexes. The availability of structurally characterized protein interfaces significantly improves our understanding of interactomes, and the progress in structural characterization of protein-protein interactions (PPIs) can be measured by calculating the structural coverage of protein domain families. We analyze the coverage of protein domain families (defined according to CDD and Pfam databases) by structures, structural protein-protein complexes and unique protein binding sites. Structural PPI coverage of currently available protein families is about 30% without any signs of saturation in coverage growth dynamics. Given the current growth rates of domain databases and structural PPI deposition, complete domain coverage with PPIs is not expected in the near future. As a result of this study we identify families without any protein-protein interaction evidence (listed on a supporting website http://www.ncbi.nlm.nih.gov/Structure/ibis/coverage/) and propose them as potential targets for structural studies with a focus on protein interactions.

[Recent advances in the techniques of protein-protein interaction study].

Protein-protein interactions play key roles in the development of organisms and the response to biotic and abiotic stresses. Several wet-lab methods have been developed to study this challenging area,including yeast two-hybrid system, tandem affinity purification, Co-immunoprecipitation, GST Pull-down, bimolecular fluorescence complementation, fluorescence resonance energy transfer and surface plasmon resonance analysis. In this review, we discuss theoretical principles and relative advantages and disvantages of these techniques,with an emphasis on recent advances to compensate for limitations.

Bimolecular fluorescence complementation (BiFC): a 5-year update and future perspectives.

Over the past decade, bimolecular fluorescence complementation (BiFC) has emerged as a key technique to visualize protein-protein interactions in a variety of model organisms. The BiFC assay is based on reconstitution of an intact fluorescent protein when two complementary non-fluorescent fragments are brought together by a pair of interacting proteins. While the originally reported BiFC method has enabled the study of many protein-protein interactions, increasing demands to visualize protein-protein interactions under various physiological conditions have not only prompted a series of recent BiFC technology improvements, but also stimulated interest in developing completely new approaches. Here we review current BiFC technology, focusing on the development and improvement of BiFC systems, the understanding of split sites in fluorescent proteins, and enhancements in the signal-to-noise ratio. In addition, we provide perspectives on possible future improvements of the technique.

Searching for the Holy Grail; protein-protein interaction analysis and modulation.

The first EMBO workshop on 'Protein-Protein Interaction Analysis & Modulation' took place in June 2012 in Roscoff, France. It brought together researchers to discuss the growing field of protein network analysis and the modulation of protein-protein interactions, as well as outstanding related issues including the daunting challenge of integrating interactomes in systems biology and in the modelling of signalling networks.

Protein-protein docking and hot-spot prediction for drug discovery.

Most processes in living organisms occur through an intricate network of protein-protein interactions, in which any malfunctioning can lead to pathological situations. Therefore, current research in biomedicine is starting to focus on protein interaction networks. A detailed structural knowledge of these interactions at molecular level will be necessary for drug discovery targeting protein-protein interactions. The challenge from a structural biology point of view is determining the structure of the specific complex formed upon interaction of two or several proteins, and/or locating the surface residues involved in the interaction and identify which of them are the most important ones for binding (hot-spots). In this line, an increasing number of computer tools are available to complement experimental efforts. Docking algorithms can achieve successful predictive rates in many complexes, as shown in the community assessment experiment CAPRI, and have already been applied to a variety of cases of biomedical interest. On the other side, many methods for interface and hotspot prediction have been reported, based on a variety of evolutionary, geometrical and physico-chemical parameters. Computer predictions are reaching a significant level of maturity, and can be very useful to guide experiments and suggest mutations, or to provide a mechanistic framework to the experimental results on a given interaction. We will review here existing computer approaches for proteinprotein docking, interface prediction and hot-spot identification, with focus to drug discovery targeting protein-protein interactions.

Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches.

The recognition process between a protein and a partner represents a significant theoretical challenge. In silico structure-based drug design carried out with nothing more than the three-dimensional structure of the protein has led to the introduction of many compounds into clinical trials and numerous drug approvals. Central to guiding the discovery process is to recognize active among non-active compounds. While large-scale computer simulations of compounds taken from a library (virtual screening) or designed de novo are highly desirable in the post-genomic area, many technical problems remain to be adequately addressed. This article presents an overview and discusses the limits of current computational methods for predicting the correct binding pose and accurate binding affinity. It also presents the performances of the most popular algorithms for exploring binary and multi-body protein interactions.

Isoenergetic microarrays to study the structure and interactions of DsrA and OxyS RNAs in two- and three-component complexes.

Information on the secondary structure and interactions of RNA is important to understand the biological function of RNA as well as in applying RNA as a tool for therapeutic purposes. Recently, the isoenergetic microarray mapping method was developed to improve the prediction of RNA secondary structure. Herein, for the first time, isoenergetic microarrays were used to study the binding of RNA to protein or other RNAs as well as the interactions of two different RNAs and protein in a three-component complex. The RNAs used as models were the regulatory DsrA and OxyS RNAs from Escherichia coli, the fragments of their target mRNAs (fhlA and rpoS), and their complexes with Hfq protein. The collected results showed the advantages and some limitations of microarray mapping.

Interaction of tumor suppressor p53 with DNA and proteins.

p53, a tumor suppressor and a transcription factor, binds DNA in a sequence-specific manner. In more than half of human cancers, p53 has been found to be mutated with the loss of DNA-binding ability. In this review, we focus on the sensitive detection of interaction of tumor suppressor p53 with double-stranded DNA bearing the consensus sequence and proteins, such as monoclonal antibodies recognizing the p53 protein and metalloprotein. Relying on the specific binding of p53 to DNA and antibodies, quantitative determination of wild-type and mutant p53 proteins in normal and cancer cell lysates has been achieved.

Present and future challenges and limitations in protein-protein docking.

The study of protein-protein interactions that are involved in essential life processes can largely benefit from the recent upraising of computational docking approaches. Predicting the structure of a protein-protein complex from their separate components is still a highly challenging task, but the field is rapidly improving. Recent advances in sampling algorithms and rigid-body scoring functions allow to produce, at least for some cases, high quality docking models that are perfectly suitable for biological and functional annotations, as it has been shown in the CAPRI blind tests. However, important challenges still remain in docking prediction. For example, in cases with significant mobility, such as multidomain proteins, fully unrestricted rigid-body docking approaches are clearly insufficient so they need to be combined with restraints derived from domain-domain linker residues, evolutionary information, or binding site predictions. Other challenging cases are weak or transient interactions, such as those between proteins involved in electron transfer, where the existence of alternative bound orientations and encounter complexes complicates the binding energy landscape. Docking methods also struggle when using in silico structural models for the interacting subunits. Bringing these challenges to a practical point of view, we have studied here the limitations of our docking and energy-based scoring approach, and have analyzed different parameters to overcome the limitations and improve the docking performance. For that, we have used the standard benchmark and some practical cases from CAPRI. Based on these results, we have devised a protocol to estimate the success of a given docking run.

Native electrophoretic techniques to identify protein-protein interactions.

Permanent protein-protein interactions are commonly identified by co-purification of two or more protein components using techniques like co-immunoprecipitation, tandem affinity purification and native electrophoresis. Here we focus on blue-native electrophoresis, clear-native electrophoresis, high-resolution clear-native electrophoresis and associated techniques to identify stable membrane protein complexes and detergent-labile physiological supercomplexes. Hints for dynamic protein-protein interactions can be obtained using two-hybrid techniques but not from native electrophoresis and other protein isolation techniques except after covalent cross-linking of interacting proteins in vivo prior to protein separation.