Measuring Drug Action in the Cellular Context Using Protein-Fragment Complementation Assays

Integrated Proteomics Characterization of NLRP3 Inflammasome Inhibitor MCC950 in Monocytic Cell Line Confirms Direct MCC950 Engagement with Endogenous NLRP3

Inhibition of the NLRP3 inflammasome is a promising strategy for the development of new treatments for inflammatory diseases. MCC950 is a potent and selective small-molecule inhibitor of the NLRP3 pathway and has been validated in numerous species and disease models. Although the capacity of MCC950 to block NLRP3 signaling is well-established, it is still critical to identify the mechanism of action and molecular targets of MCC950 to inform and derisk drug development. Quantitative proteomics performed in disease-relevant systems provides a powerful method to study both direct and indirect pharmacological responses to small molecules to elucidate the mechanism of action and confirm target engagement. A comprehensive target deconvolution campaign requires the use of complementary chemical biology techniques. Here we applied two orthogonal chemical biology techniques: compressed Cellular Thermal Shift Assay (CETSA) and photoaffinity labeling chemoproteomics, performed under biologically relevant conditions with LPS-primed THP-1 cells, thereby deconvoluting, for the first time, the molecular targets of MCC950 using chemical biology techniques. In-cell chemoproteomics with inlysate CETSA confirmed the suspected mechanism as the disruption of inflammasome formation via NLRP3. Further cCETSA (c indicates compressed) in live cells mapped the stabilization of NLRP3 inflammasome pathway proteins, highlighting modulation of the targeted pathway. This is the first evidence of direct MCC950 engagement with endogenous NLRP3 in a human macrophage cellular system using discovery proteomics chemical biology techniques, providing critical information for inflammasome studies.

Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network Approach

Traditional experimental testing to identify endocrine disruptors that enhance estrogenic signaling relies on expensive and labor-intensive experiments. We sought to design a knowledge-based deep neural network (k-DNN) approach to reveal and organize public high-throughput screening data for compounds with nuclear estrogen receptor α and β (ERα and ERβ) binding potentials. The target activity was rodent uterotrophic bioactivity driven by ERα/ERβ activations. After training, the resultant network successfully inferred critical relationships among ERα/ERβ target bioassays, shown as weights of 6521 edges between 1071 neurons. The resultant network uses an adverse outcome pathway (AOP) framework to mimic the signaling pathway initiated by ERα and identify compounds that mimic endogenous estrogens (i.e., estrogen mimetics). The k-DNN can predict estrogen mimetics by activating neurons representing several events in the ERα/ERβ signaling pathway. Therefore, this virtual pathway model, starting from a compound's chemistry initiating ERα activation and ending with rodent uterotrophic bioactivity, can efficiently and accurately prioritize new estrogen mimetics (AUC = 0.864-0.927). This k-DNN method is a potential universal computational toxicology strategy to utilize public high-throughput screening data to characterize hazards and prioritize potentially toxic compounds.

Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches

As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine system and consequently causes adverse health effects in an intact organism, its progeny, or (sub)populations. Traditional experimental testing regimens to identify toxicants that induce endocrine disruption can be expensive and time-consuming. Computational modeling has emerged as a promising and cost-effective alternative method for screening and prioritizing potentially endocrine-active compounds. The efficient identification of suitable chemical descriptors and machine-learning algorithms, including deep learning, is a considerable challenge for computational toxicology studies. Here, we sought to apply classic machine-learning algorithms and deep-learning approaches to a panel of over 7500 compounds tested against 18 Toxicity Forecaster assays related to nuclear estrogen receptor (ERα and ERβ) activity. Three binary fingerprints (Extended Connectivity FingerPrints, Functional Connectivity FingerPrints, and Molecular ACCess System) were used as chemical descriptors in this study. Each descriptor was combined with four machine-learning and two deep- learning (normal and multitask neural networks) approaches to construct models for all 18 ER assays. The resulting model performance was evaluated using the area under the receiver- operating curve (AUC) values obtained from a fivefold cross-validation procedure. The results showed that individual models have AUC values that range from 0.56 to 0.86. External validation was conducted using two additional sets of compounds (n = 592 and n = 966) with established interactions with nuclear ER demonstrated through experimentation. An agonist, antagonist, or binding score was determined for each compound by averaging its predicted probabilities in relevant assay models as an external validation, yielding AUC values ranging from 0.63 to 0.91. The results suggest that multitask neural networks offer advantages when modeling mechanistically related endpoints. Consensus predictions based on the average values of individual models remain the best modeling strategy for computational toxicity evaluations.

High-Throughput Screening to Identify Chemical Cardiotoxic Potential

Cardiovascular (CV) disease is one of the most prevalent public health concerns, and mounting evidence supports the contribution of environmental chemicals to CV disease burden. In this study, we performed cardiotoxicity profiling for the Tox21 chemical library by focusing on high-throughput screening (HTS) assays whose targets are associated with adverse events related to CV failure modes. Our objective was to develop new hypotheses around environmental chemicals of potential interest for adverse CV outcomes using Tox21/ToxCast HTS data. Molecular and cellular events linked to six failure modes of CV toxicity were cross-referenced with 1399 Tox21/ToxCast assays to identify cardio-relevant bioactivity signatures. The resulting 40 targets, measured in 314 assays, were integrated via a ToxPi visualization tool and ranking system to prioritize 1138 chemicals based upon formal integration across multiple domains of information. Filtering was performed based on cytotoxicity and generalized cell stress endpoints to try and isolate chemicals with effects specific to CV biology, and bioactivity- and structure-based clustering identified subgroups of chemicals preferentially affecting targets such as ion channels and vascular tissue biology. Our approach identified drugs with known cardiotoxic effects, such as estrogenic modulators like clomiphene and raloxifene, anti-arrhythmic drugs like amiodarone and haloperidol, and antipsychotic drugs like chlorpromazine. Several classes of environmental chemicals such as organotins, bisphenol-like chemicals, pesticides, and quaternary ammonium compounds demonstrated strong bioactivity against CV targets; these were compared to existing data in the literature (e.g., from cardiomyocytes, animal data, or human epidemiological studies) and prioritized for further testing.

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.

FRETting about the affinity of bimolecular protein-protein interactions

Fluorescence resonance energy transfer (FRET) is a powerful tool to study macromolecular interactions such as protein-protein interactions (PPIs). Fluorescent protein (FP) fusions enable FRET-based PPI analysis of signaling pathways and molecular structure in living cells. Despite FRET's importance in PPI studies, FRET has seen limited use in quantifying the affinities of PPIs in living cells. Here, we have explored the relationship between FRET efficiency and PPI affinity over a wide range when expressed from a single plasmid system in Escherichia coli. Using live-cell microscopy and a set of 20 pairs of small interacting proteins, belonging to different structural folds and interaction affinities, we demonstrate that FRET efficiency can reliably measure the dissociation constant (K_D ) over a range of mM to nM. A 10-fold increase in the interaction affinity results in 0.05 unit increase in FRET efficiency, providing sufficient resolution to quantify large affinity differences (> 10-fold) using live-cell FRET. This approach provides a rapid and simple strategy for assessment of PPI affinities over a wide range and will have utility for high-throughput analysis of protein interactions.

Anti-inflammatory effects of ivy leaves dry extract: influence on transcriptional activity of NFκB

EA 575® is an ivy leaves dry extract (DER 5-7.5:1, 30% ethanol) used against diseases of the lower respiratory tract associated with productive cough. EA 575® improves symptoms associated with chronic inflammatory bronchial conditions. Compared to its bronchospasmolytic and secretolytic properties, the anti-inflammatory effects of EA 575® are mostly untried. Therefore, we addressed the question of whether the anti-inflammatory effect of EA 575® is due to an impact on the NFκB pathway. NFκB nuclear translocation was visualized by immunofluorescence in J774.2 as well as HEK293 cells. In the latter, a luciferase-based reporter was used to monitor NFκB transcriptional activity. Phosphorylation of RelA and its inhibitor IκB was measured by Western blot analysis. Additionally, changes in the stability of NFκB:IκB complex were shown by protein fragment complementation. Decreased transcriptional activity of NFκB under treatment with EA 575® was also shown for a human monocytic as well as a human lung epithelial cell line. EA 575® is able to inhibit NFκB transcriptional activity by partially inhibiting its translocation to the nucleus after stimulation with TNFα. Furthermore, phosphorylation of IκBα is reduced while phosphorylation of RelA is enhanced after pre-incubation with EA 575®, leading to an enhanced stability of NFκB:IκBα complex. EA 575® has an regulatory impact on the NFκB pathway, possibly by switching specificity of IKK from IκBα to RelA, resulting in enhanced stability of NFκB:IκBα complex and reduced RelA translocation into the nucleus.

A selective high affinity MYC-binding compound inhibits MYC:MAX interaction and MYC-dependent tumor cell proliferation

MYC is a key player in tumor development, but unfortunately no specific MYC-targeting drugs are clinically available. MYC is strictly dependent on heterodimerization with MAX for transcription activation. Aiming at targeting this interaction, we identified MYCMI-6 in a cell-based protein interaction screen for small inhibitory molecules. MYCMI-6 exhibits strong selective inhibition of MYC:MAX interaction in cells and in vitro at single-digit micromolar concentrations, as validated by split Gaussia luciferase, in situ proximity ligation, microscale thermophoresis and surface plasmon resonance (SPR) assays. Further, MYCMI-6 blocks MYC-driven transcription and binds selectively to the MYC bHLHZip domain with a KD of 1.6 ± 0.5 μM as demonstrated by SPR. MYCMI-6 inhibits tumor cell growth in a MYC-dependent manner with IC50 concentrations as low as 0.5 μM, while sparing normal cells. The response to MYCMI-6 correlates with MYC expression based on data from 60 human tumor cell lines and is abrogated by MYC depletion. Further, it inhibits MYC:MAX interaction, reduces proliferation and induces massive apoptosis in tumor tissue from a MYC-driven xenograft tumor model without severe side effects. Since MYCMI-6 does not affect MYC expression, it is a unique molecular tool to specifically target MYC:MAX pharmacologically and it has good potential for drug development.

High-Content Reporter Assays

While luminescent reporter gene assays allow for a rapid and relatively interference free assessment of the activation state of a luminescent reporter, fluorescent reporters do not. They suffer from artifacts such as compound fluorescence and cellular debris which makes the assessment of whole well fluorescence signals difficult. However, the use of high-content screening allows for the isolation of individual cells, segmentation and thus enables the screener to utilize fluorescent reporters to assess the activation state of such a high-content reporter on a cell by cell level, thus minimizing artifacts. Here we discuss the use of such a high-content reporter that enables screening for compounds useful for HIV reactivation on Jurkat cells with high-content screening.

Live-Cell High Content Screening in Drug Development

In the past decade, automated microscopy has become an important tool for the drug discovery and development process. The establishment of imaging modalities as screening tools depended on technological breakthroughs in the domain of automated microscopy and automated image analysis. These types of assays are often referred to as high content screening or high content analysis (HCS/HCA). The driving force to adopt imaging for drug development is the quantity and quality of cellular information that can be collected and the enhanced physiological relevance of cellular screening compared to biochemical screening. Most imaging in drug development is performed on fixed cells as this allows uncoupling the preparation of the cells from the acquisition of the images. Live-cell imaging is technically challenging, but is very useful for many aspects of the drug development pipeline such as kinetic studies of compound mode of action or to analyze the motion of cellular components. Most vendors of HCS microscopy systems offer the option of environmental chambers and onboard pipetting on their platforms. This reflects the wish and desire of many customers to have the ability to perform live-cell assays on their HCS automated microscopes. This book chapter summarizes the challenges and advantages of live-cell imaging in drug discovery. Examples of applications are presented and the motivation to perform these assays in kinetic mode is discussed.

Defining estrogenic mechanisms of bisphenol A analogs through high throughput microscopy-based contextual assays

Environmental exposures to chemically heterogeneous endocrine-disrupting chemicals (EDCs) mimic or interfere with hormone actions and negatively affect human health. Despite public interest and the prevalence of EDCs in the environment, methods to mechanistically classify these diverse chemicals in a high throughput (HT) manner have not been actively explored. Here, we describe the use of multiparametric, HT microscopy-based platforms to examine how a prototypical EDC, bisphenol A (BPA), and 18 poorly studied BPA analogs (BPXs), affect estrogen receptor (ER). We show that short exposure to BPA and most BPXs induces ERα and/or ERβ loading to DNA changing target gene transcription. Many BPXs exhibit higher affinity for ERβ and act as ERβ antagonists, while they act largely as agonists or mixed agonists and antagonists on ERα. Finally, despite binding to ERs, some BPXs exhibit lower levels of activity. Our comprehensive view of BPXs activities allows their classification and the evaluation of potential harmful effects. The strategy described here used on a large-scale basis likely offers a faster, more cost-effective way to identify safer BPA alternatives.

Heteromerization of angiotensin receptors changes trafficking and arrestin recruitment profiles

The cardiovascular hormone angiotensin II (AngII) exerts its actions via two G protein-coupled receptor (GPCR) subtypes, AT(1) and AT(2), which often display antagonistic functions. Methodological constraints have so far precluded detailed analyses of the ligand-dependency, cellular localization, and functional relevance of AngII receptor interactions in live cells. In this study, we utilize a protein-fragment complementation assay (PCA) and GPCR-Heteromer Identification Technology (GPCR-HIT) to provide the first detailed investigation of the ligand-dependency and cellular localization of AngII receptor interactions in human embryonic kidney 293 cells. Fluorescent-tagged receptor constructs for PCA and GPCR-HIT displayed normal affinity and selectivity for AngII (AT(1): IC(50)=1.0-1.6nM; AT(2): IC(50)=2.0-3.0nM). Well-characterized angiotensin receptor interactions were used as positive and negative controls to demonstrate the sensitivity and specificity of these fluorescence-based assays. We report that AT(1)-AT(2) receptor heteromers form constitutively, are localized to the plasma membrane and perinuclear compartments, and do not internalize following AngII stimulation despite arrestin being recruited specifically to the heteromer. Our findings using novel fluorescence-based technologies reveal a previously unrecognized mechanism of angiotensin receptor cross-talk involving cross-inhibition of AT(1) receptor internalization through heteromerization with the AT(2) receptor subtype.

Dual-Color Bioluminescence Analysis for Quantitatively Monitoring G-Protein-Coupled Receptor and β-Arrestin Interactions

G protein-coupled receptors (GPCRs) are crucial elements in mammalian signal transduction, and are considered to represent potent drug targets. We have previously developed a GPCR assay system in cultured cells based on complementation of split fragments of click beetle (Pyrearinus termitilluminans) luciferase. The interaction of GPCRs with its target, β-arrestin, resulted in strong emission of bioluminescence upon stimulation with its specific ligand. In this study, we improved precision of the GPCR assay system by using railroad worm (Phrixothrix hirtus) luciferase as an internal control. We generated stable cell lines harboring the railroad worm luciferase and quantitatively evaluate the extent of GPCR-β-arrestin interactions. We showed concentration-dependent bioluminescence responses for four GPCRs: β2-adrenoceptor, endothelin receptor type A, α2-adrenoceptor and human μ-opioid receptor. We also demonstrated that the variation of responses was reduced significantly by normalizing the data with bioluminescence from railroad worm luciferase. This assay system represents a simple and reliable approach for screening drug candidates in a high throughput manner.

Bimolecular Complementation to Visualize Filovirus VP40-Host Complexes in Live Mammalian Cells: Toward the Identification of Budding Inhibitors

Virus-host interactions play key roles in promoting efficient egress of many RNA viruses, including Ebola virus (EBOV or “e”) and Marburg virus (MARV or “m”). Late- (L-) domains conserved in viral matrix proteins recruit specific host proteins, such as Tsg101 and Nedd4, to facilitate the budding process. These interactions serve as attractive targets for the development of broad-spectrum budding inhibitors. A major gap still exists in our understanding of the mechanism of filovirus budding due to the difficulty in detecting virus-host complexes and mapping their trafficking patterns in the natural environment of the cell. To address this gap, we used a bimolecular complementation (BiMC) approach to detect, localize, and follow the trafficking patterns of eVP40-Tsg101 complexes in live mammalian cells. In addition, we used the BiMC approach along with a VLP budding assay to test small molecule inhibitors identified by in silico screening for their ability to block eVP40 PTAP-mediated interactions with Tsg101 and subsequent budding of eVP40 VLPs. We demonstrated the potential broad spectrum activity of a lead candidate inhibitor by demonstrating its ability to block PTAP-dependent binding of HIV-1 Gag to Tsg101 and subsequent egress of HIV-1 Gag VLPs.

Improving drug discovery with contextual assays and cellular systems analysis

Despite rapid growth in our knowledge of potential disease targets following completion of the first drafts of the human genome over 10 years ago, the success rate of new therapeutic discovery has been frustratingly low. In addition to the widely reported costs and single-digit success rate of the entire drug discovery and development process, it has recently been estimated that even the preliminary process of transitioning new targets to preclinical development succeeds in less than 3% of attempts [Vogel (ed.) Drug Discovery and Evaluation: Pharmacological Assays. 3rd ed. Springer, Berlin (2007)]. At these early stages of development, poor understanding of therapeutic mechanisms and lack of compound selectivity are often to blame for failed compounds. It is worth noting than the emerging class of nucleic acid-based therapeutics, including miRNA and RNAi, are likely to be even more prone to unexpected system-wide and off-target activities. For all therapeutic approaches, it is clear that discovery strategies permitting the assessment of drug targets in their native context are required. At the same time, these strategies need to retain the high throughput of current reductionist approaches to enable broad assessment of chemical space for small molecule and genetic therapeutics. We describe here an integrated system based on high-content cellular analysis combined with system-wide pathway interrogation. The platform can be applied to novel therapeutic target and drug candidate identification, and for providing detailed mechanistic and selectivity information at an early stage of development.

Detection and characterization of influenza A virus PA-PB2 interaction through a bimolecular fluorescence complementation assay

The influenza virus polymerase complex, consisting of the PA, PB1, and PB2 subunits, is required for the transcription and replication of the influenza A viral genome. Previous studies have shown that PB1 serves as a core subunit to incorporate PA and PB2 into the polymerase complex by directly interacting with PA and PB2. Despite numerous attempts, largely involving biochemical approaches, a specific interaction between PA and PB2 subunits has yet to be detected. In the current study, we developed and utilized bimolecular fluorescence complementation (BiFC) to study protein-protein interactions in the assembly of the influenza A virus polymerase complex. Proof-of-concept experiments demonstrated that BiFC can specifically detect PA-PB1 interactions in living cells. Strikingly, BiFC demonstrated an interaction between PA and PB2 that has not been reported previously. Deletion-based BiFC experiments indicated that the N-terminal 100 amino acid residues of PA are responsible for the PA-PB2 interaction observed in BiFC. Furthermore, a detailed analysis of subcellular localization patterns and temporal nuclear import of PA-PB2 binary complexes suggested that PA and PB2 subunits interacted in the cytoplasm initially and were subsequently transported as a dimer into the nucleus. Taken together, results of our studies reveal a previously unknown PA-PB2 interaction and provide a framework for further investigation of the biological relevance of the PA-PB2 interaction in the polymerase activity and viral replication of influenza A virus.

Visualization of protein interactions in living cells using bimolecular fluorescence complementation (BiFC) analysis

Protein interactions integrate stimuli from different signaling pathways and developmental programs. Bimolecular fluorescence complementation (BiFC) analysis has been developed for visualization of protein interactions in living cells. This approach is based on complementation between two fragments of a fluorescent protein when they are brought together by an interaction between proteins fused to the fragments, and it enables visualization of the subcellular locations of protein interactions in the normal cellular environment. It can be used for the analysis of many protein interactions and does not require information about the structures of the interaction partners. A multicolor BiFC approach has been developed for simultaneous visualization of interactions with multiple alternative partners in the same cell, based on complementation between fragments of engineered fluorescent proteins that produce bimolecular fluorescent complexes with distinct spectral characteristics. This enables comparison of subcellular distributions of different protein complexes in the same cell and allows analysis of competition between mutually exclusive interaction partners.

Monitoring autophagy in Magnaporthe oryzae

Autophagy is a ubiquitous degradative pathway for the bulk degradation of eukaryotic macromolecules and organelles in eukaryotic cells (Klionsky, 2005; Levine and Klionsky, 2004). Previously, the role of autophagy in turgor generation in plant pathogenic fungi was unknown. Currently, autophagy is confirmed as an important pathway for turgor accumulation in the appressorium (the tips of the invasive hyphae; Liu et al., 2007b) using a technique of targeted gene replacement, deleting the genes that code for Magnaporthe oryzae homologs of yeast autophagy-related (ATG) genes ATG2, ATG4, ATG5, ATG8, ATG9, and ATG18 (Liu et al., 2007a). All of these null mutants fail to breach the cuticle of the host. This chapter will first look at some methodologies to analyze the functions of autophagy-related gene products at the biological, cellular, and molecular level in this model plant pathogenic fungi, and then provide some research evidence of the role of autophagy in the promotion of the formation of the infection structure and pathogenicity to point out some significant areas for further research in this field.

Assessing GPCR activation using protein complementation: a novel technique for HTS

GPCRs (G-protein-coupled receptors) are critical targets in drug discovery. Although most HTS (high-throughput screening) assays are routinely used to identify functional agonism or antagonism, they are suboptimal as methods to screen for modulators of other, novel, aspects of GPCR function. Indeed, it is now evident that GPCRs are highly complex proteins that interact with RAMPs (receptor-activity-modifying partners), β-arrestins, G-proteins, as well as functioning in potential homo- or hetero-meric complexes. Consequently, novel HTS technologies are now required that would facilitate interrogation of GPCRs in terms of their cellular protein–protein interactions. One approach is oligomerization-assisted complementation of monomeric protein fragments and detection of fragment reassembly. Notably, the use of enzymes has advantages in this regard, since complementation results in catalytically competent protein. The assay signal generated in this fashion results in assays of high sensitivity, thereby enabling protocols to be developed in HTS systems that require extremely low fluid volumes. The use of complementing proteins that generate a luminescent signal also provides assays that are markedly free from artefactual interferences.

Beta galactosidase complementation: a cell-based luminescent assay platform for drug discovery

Many cell-based assays interrogating cell pathway activation employ protocols that require microscopic imaging techniques. However, such assays are not in general widely adopted for primary screening. Protein complementation, particularly of enzymes, provides an alternative approach for cell pathway analysis, with a principal advantage that is amenable to high throughput screening using microtiter plate protocols. Notably, alpha complementation of the enzyme beta-galactosidase has been exploited as a technology in this regard, using substrates that generates luminescent signals. This review describes the various uses of this flexible technology to cell-based assay development.

A retrovirus-based protein complementation assay screen reveals functional AKT1-binding partners

We developed a retrovirus-based protein-fragment complementation assay (RePCA) screen to identify protein-protein interactions in mammalian cells. In RePCA, bait protein is fused to one fragment of a rationally dissected fluorescent protein, such as GFP, intensely fluorescent protein, or red fluorescent protein. The second, complementary fragment of the fluorescent protein is fused to an endogenous protein by in-frame exon traps in the enhanced retroviral mutagen vector. An interaction between bait and host protein (prey) places the two parts of the fluorescent molecule in proximity, resulting in reconstitution of fluorescence. By using RePCA, we identified a series of 24 potential interaction partners or substrates of the serine/threonine protein kinase AKT1. We confirm that alpha-actinin 4 (ACTN4) interacts physically and functionally with AKT1. siRNA-mediated ACTN4 silencing down-regulates AKT phosphorylation, blocks AKT translocation to the membrane, increases p27(Kip1) levels, and inhibits cell proliferation. Thus, ACTN4 is a critical regulator of AKT1 localization and function.

Identifying off-target effects and hidden phenotypes of drugs in human cells

We present a strategy for identifying off-target effects and hidden phenotypes of drugs by directly probing biochemical pathways that underlie therapeutic or toxic mechanisms in intact, living cells. High-content protein-fragment complementation assays (PCAs) were constructed with synthetic fragments of a mutant fluorescent protein ('Venus', EYFP or both), allowing us to measure spatial and temporal changes in protein complexes in response to drugs that activate or inhibit particular pathways. One hundred and seven different drugs from six therapeutic areas were screened against 49 different PCA reporters for ten cellular processes. This strategy reproduced known structure-function relationships and also predicted 'hidden,' potent antiproliferative activities for four drugs with novel mechanisms of action, including disruption of mitochondrial membrane potential. A simple algorithm identified a 25-assay panel that was highly predictive of antiproliferative activity, and the predictive power of this approach was confirmed with cross-validation tests. This study suggests a strategy for therapeutic discovery that identifies novel, unpredicted mechanisms of drug action and thereby enhances the productivity of drug-discovery research.

Protein‐Fragment Complementation Assays (PCA) in Small GTPase Research and Drug Discovery

Small GTPases of the Ras and Rho families are among the most studied signaling proteins and represent promising therapeutic targets for human neoplastic disease. Despite the high level of interest in these proteins, direct analysis of most aspects of Ras protein biology in living cells has not been possible, because much of the details of Ras signaling cannot be studied in vitro but requires simple cell-based assays. Here we describe a strategy for directly analyzing Ras signaling pathways in living cells using protein-fragment complementation assays (PCA) based on fragments of intensely fluorescent proteins. The assays allow for spatial and temporal analysis of protein complexes including those that form upstream and downstream from Ras proteins, as well as complexes of Ras proteins with regulator and effector proteins. We describe high-throughput quantitative microscopic methods to follow temporal changes in complex subcellular location and quantity (high-content assays). Spatial and temporal changes in response to perturbations (chemical, siRNA, hormones) allow for delineation of Ras signaling networks and a general and high-throughput approach to identify drugs that act directly or indirectly on Ras pathways.

Deciphering B-ZIP transcription factor interactions in vitro and in vivo

Over the last 15 years, numerous studies have addressed the structural rules that regulate dimerization stability and dimerization specificity of the leucine zipper, a dimeric parallel coiled-coil domain that can either homodimerize or heterodimerize. Initially, these studies were performed with a limited set of B-ZIP proteins, sequence-specific DNA binding proteins that dimerize using the leucine zipper domain to bind DNA. A global analysis of B-ZIP leucine zipper dimerization properties can be rationalized using a limited number of structural rules [J.R. Newman, A.E. Keating, Comprehensive identification of human bZIP interactions with coiled-coil arrays, Science 300 (2003) 2097-2101]. Today, however, access to the genomic sequences of many different organisms has made possible the annotation of all B-ZIP proteins from several species and has generated a bank of data that can be used to refine, and potentially expand, these rules. Already, a comparative analysis of the B-ZIP proteins from Arabidopsis thaliana and Homo sapiens has revealed that the same amino acids are used in different patterns to generate diverse B-ZIP dimerization patterns [C.D. Deppmann, A. Acharya, V. Rishi, B. Wobbes, S. Smeekens, E.J. Taparowsky, C. Vinson, Dimerization specificity of all 67 B-ZIP motifs in Arabidopsis thaliana: a comparison to Homo sapiens B-ZIP motifs, Nucleic Acids Res. 32 (2004) 3435-3445]. The challenge ahead is to investigate the biological significance of different B-ZIP protein-protein interactions. Gaining insight at this level will rely on ongoing investigations to (a) define the role of target DNA on modulating B-ZIP dimerization partners, (b) characterize the B-ZIP transcriptome in various cells and tissues through mRNA microarray analysis, (c) identify the genomic localization of B-ZIP binding at a genomic level using the chromatin immunoprecipitation assay, and (d) develop more sophisticated imaging technologies to visualize dimer dynamics in single cells and whole organisms. Studies of B-ZIP family leucine zipper dimerization and the regulatory mechanisms that control their biological activities could serve as a paradigm for deciphering the biophysical and biological parameters governing other well-characterized protein-protein interaction motifs. This review will focus on the dimerization specificity of coiled-coil proteins, particularly the human B-ZIP transcription family that consists of 53 proteins that use the leucine zipper coiled-coil as a dimerization motif.

Fluorescent protein-based cellular assays analyzed by laser-scanning microplate cytometry in 1536-well plate format

Microtiter plate readers have evolved from photomultiplier and charged-coupled device-based readers, where a population-averaged signal is detected from each well, to microscope-based imaging systems, where cellular characteristics from individual cells are measured. For these systems, speed and ease of data analysis are inversely proportional to the amount of data collected from each well. Microplate laser cytometry is a technology compatible with a 1536-well plate format and capable of population distribution analysis. Microplate cytometers such as the Acumen Explorer can monitor up to four fluorescent signals from single objects in microtiter plates with densities as high as 1536 wells. These instruments can measure changes in fluorescent protein expression, cell shape, or simple cellular redistribution events such as cytoplasmic to nuclear translocation. To develop high-throughput screening applications using laser-scanning microplate cytometry, we used green fluorescent protein- and yellow fluorescent protein-expressing cell lines designed to measure diverse biological functions such as nuclear translocation, epigenetic signaling, and G protein-coupled receptor activation. This chapter illustrates the application of microplate laser cytometry to these assays in a manner that is suitable for screening large compound collections in high throughput.

Visualization of protein interactions in living cells using bimolecular fluorescence complementation (BiFC) analysis

Protein interactions integrate stimuli from different signaling pathways and developmental programs. Bimolecular fluorescence complementation (BiFC) analysis has been developed for visualization of protein interactions in living cells. This approach is based on complementation between two fragments of a fluorescent protein when they are brought together by an interaction between proteins fused to the fragments, and it enables visualization of the subcellular locations of protein interactions in the normal cellular environment. It can be used for the analysis of many protein interactions and does not require information about the structures of the interaction partners. A multicolor BiFC approach has been developed for simultaneous visualization of interactions with multiple alternative partners in the same cell, based on complementation between fragments of engineered fluorescent proteins that produce bimolecular fluorescent complexes with distinct spectral characteristics. This enables comparison of subcellular distributions of different protein complexes in the same cell and allows analysis of competition between mutually exclusive interaction partners.

Translocation Biosensors to Study Signal-Specific Nucleo-Cytoplasmic Transport, Protease Activity and Protein-Protein Interactions

Regulated nucleo-cytoplasmic transport is crucial for cellular homeostasis and relies on protein interaction networks. In addition, the spatial division into the nucleus and the cytoplasm marks two intracellular compartments that can easily be distinguished by microscopy. Consequently, combining the rules for regulated nucleo-cytoplasmic transport with autofluorescent proteins, we developed novel cellular biosensors composed of glutathione S-transferase, mutants of green fluorescent protein and rational combinations of nuclear import and export signals. Addition of regulatory sequences resulted in three classes of biosensors applicable for the identification of signal-specific nuclear export and import inhibitors, small molecules that interfere with protease activity and compounds that prevent specific protein-protein interactions in living cells. As a unique feature, our system exploits nuclear accumulation of the cytoplasmic biosensors as the reliable readout for all assays. Efficacy of the biosensors was systematically investigated and also demonstrated by using a fully automated platform for high throughput screening (HTS) microscopy and assay analysis. The introduced modular biosensors not only have the potential to further dissect nucleo-cytoplasmic transport pathways but also to be employed in numerous screening applications for the early stage evaluation of potential drug candidates.

Emerging classes of protein–protein interaction inhibitors and new tools for their development

Protein-protein interactions play a key role in the signal transduction pathways that regulate cellular function. Three years ago, few descriptions of small molecule protein-protein interaction inhibitors (SMPPIIs) existed in the literature. Today, the number of examples of both the biology and chemistry of such interaction inhibitors is growing rapidly. This growth occurs at the convergence of medicinal chemistry, signaling biology and novel assay technology for profiling emerging compound classes and modes of action. Protein translocation assays provide a unique new tool for identifying, profiling, and optimizing SMPPIIs. This review summarizes recent work in the field, and outlines future developments we can anticipate.