A Quantitative Systems Pharmacology Platform Reveals NAFLD Pathophysiological States and Targeting Strategies

Non-alcoholic fatty liver disease (NAFLD) has a high global prevalence with a heterogeneous and complex pathophysiology that presents barriers to traditional targeted therapeutic approaches. We describe an integrated quantitative systems pharmacology (QSP) platform that comprehensively and unbiasedly defines disease states, in contrast to just individual genes or pathways, that promote NAFLD progression. The QSP platform can be used to predict drugs that normalize these disease states and experimentally test predictions in a human liver acinus microphysiology system (LAMPS) that recapitulates key aspects of NAFLD. Analysis of a 182 patient-derived hepatic RNA-sequencing dataset generated 12 gene signatures mirroring these states. Screening against the LINCS L1000 database led to the identification of drugs predicted to revert these signatures and corresponding disease states. A proof-of-concept study in LAMPS demonstrated mitigation of steatosis, inflammation, and fibrosis, especially with drug combinations. Mechanistically, several structurally diverse drugs were predicted to interact with a subnetwork of nuclear receptors, including pregnane X receptor (PXR; NR1I2), that has evolved to respond to both xenobiotic and endogenous ligands and is intrinsic to NAFLD-associated transcription dysregulation. In conjunction with iPSC-derived cells, this platform has the potential for developing personalized NAFLD therapeutic strategies, informing disease mechanisms, and defining optimal cohorts of patients for clinical trials.

Quantifying the progression of non-alcoholic fatty liver disease in human biomimetic liver microphysiology systems with fluorescent protein biosensors

Metabolic syndrome is a complex disease that involves multiple organ systems including a critical role for the liver. Non-alcoholic fatty liver disease (NAFLD) is a key component of the metabolic syndrome and fatty liver is linked to a range of metabolic dysfunctions that occur in approximately 25% of the population. A panel of experts recently agreed that the acronym, NAFLD, did not properly characterize this heterogeneous disease given the associated metabolic abnormalities such as type 2 diabetes mellitus (T2D), obesity, and hypertension. Therefore, metabolic dysfunction-associated fatty liver disease (MAFLD) has been proposed as the new term to cover the heterogeneity identified in the NAFLD patient population. Although many rodent models of NAFLD/NASH have been developed, they do not recapitulate the full disease spectrum in patients. Therefore, a platform has evolved initially focused on human biomimetic liver microphysiology systems that integrates fluorescent protein biosensors along with other key metrics, the microphysiology systems database, and quantitative systems pharmacology. Quantitative systems pharmacology is being applied to investigate the mechanisms of NAFLD/MAFLD progression to select molecular targets for fluorescent protein biosensors, to integrate computational and experimental methods to predict drugs for repurposing, and to facilitate novel drug development. Fluorescent protein biosensors are critical components of the platform since they enable monitoring of the pathophysiology of disease progression by defining and quantifying the temporal and spatial dynamics of protein functions in the biosensor cells, and serve as minimally invasive biomarkers of the physiological state of the microphysiology system experimental disease models. Here, we summarize the progress in developing human microphysiology system disease models of NAFLD/MAFLD from several laboratories, developing fluorescent protein biosensors to monitor and to measure NAFLD/MAFLD disease progression and implementation of quantitative systems pharmacology with the goal of repurposing drugs and guiding the creation of novel therapeutics.

Development and Optimization of a High-Content Analysis Platform to Identify Suppressors of Lamin B1 Overexpression as a Therapeutic Strategy for Autosomal Dominant Leukodystrophy

Autosomal dominant leukodystrophy (ADLD) is a fatal, progressive adult-onset disease characterized by widespread central nervous system (CNS) demyelination and significant morbidity. The late age of onset together with the relatively slow disease progression provides a large therapeutic window for the disorder. However, no treatment exists for ADLD, representing an urgent and unmet clinical need. We have previously shown that ADLD is caused by duplications of the lamin B1 gene causing increased expression of the lamin B1 protein, a major constituent of the nuclear lamina, and demonstrated that transgenic mice with oligodendrocyte-specific overexpression of lamin B1 exhibit temporal and histopathological features reminiscent of the human disease. As increased levels of lamin B1 are the causative event triggering ADLD, approaches aimed at reducing lamin B1 levels and associated functional consequences represent a promising strategy for discovery of small-molecule ADLD therapeutics. To this end, we have created an inducible cell culture model of lamin B1 overexpression and developed high-content analysis in connection with multivariate analysis to define, analyze, and quantify lamin B1 expression and its associated abnormal nuclear phenotype in mouse embryonic fibroblasts (MEFs). The assay has been optimized to meet high-throughput screening (HTS) criteria in multiday variability studies. To control for batch-to-batch variation in the primary MEFs, we have implemented a screening strategy that employs sentinel cells to avoid costly losses during HTS. We posit the assay will identify bona fide suppressors of lamin B1 pathophysiology as candidates for development into potential therapies for ADLD.

Applications of the microphysiology systems database for experimental ADME-Tox and disease models

To accelerate the development and application of Microphysiological Systems (MPS) in biomedical research and drug discovery/development, a centralized resource is required to provide the detailed design, application, and performance data that enables industry and research scientists to select, optimize, and/or develop new MPS solutions, as well as to harness data from MPS models. We have previously implemented an open source Microphysiology Systems Database (MPS-Db), with a simple icon driven interface, as a resource for MPS researchers and drug discovery/development scientists (https://mps.csb.pitt.edu). The MPS-Db captures and aggregates data from MPS, ranging from static microplate models to integrated, multi-organ microfluidic models, and associates those data with reference data from chemical, biochemical, pre-clinical, clinical and post-marketing sources to support the design, development, validation, application and interpretation of the models. The MPS-Db enables users to manage their multifactor, multichip studies, then upload, analyze, review, computationally model and share data. Here we discuss how the sharing of MPS study data in the MS-Db is under user control and can be kept private to the individual user, shared with a select group of collaborators, or be made accessible to the general scientific community. We also present a test case using our liver acinus MPS model (LAMPS) as an example and discuss the use of the MPS-Db in managing, designing, and analyzing MPS study data, assessing the reproducibility of MPS models, and evaluating the concordance of MPS model results with clinical findings. We introduce the Disease Portal module with links to resources for the design of MPS disease models and studies and discuss the integration of computational models for the prediction of PK/PD and disease pathways using data generated from MPS models.

A High-Throughput Assay for DNA Replication Inhibitors Based upon Multivariate Analysis of Yeast Growth Kinetics

Mcm2-7 is the molecular motor of eukaryotic replicative helicase, and the regulation of this complex is a major focus of cellular S-phase regulation. Despite its cellular importance, few small-molecule inhibitors of this complex are known. Based upon our genetic analysis of synthetic growth defects between mcm alleles and a range of other alleles, we have developed a high-throughput screening (HTS) assay using a well-characterized mcm mutant (containing the mcm2DENQ allele) to identify small molecules that replicate such synthetic growth defects. During assay development, we found that aphidicolin (inhibitor of DNA polymerase alpha) and XL413 (inhibitor of the DNA replication-dependent kinase CDC7) preferentially inhibited growth of the mcm2DENQ strain relative to the wild-type parental strain. However, as both strains demonstrated some degree of growth inhibition with these compounds, small and variable assay windows can result. To increase assay sensitivity and reproducibility, we developed a strategy combining the analysis of cell growth kinetics with linear discriminant analysis (LDA). We found that LDA greatly improved assay performance and captured a greater range of synthetic growth inhibition phenotypes, yielding a versatile analysis platform conforming to HTS requirements.

Clinically Observed Estrogen Receptor Alpha Mutations within the Ligand-Binding Domain Confer Distinguishable Phenotypes

OBJECTIVE

Twenty to fifty percent of estrogen receptor-positive (ER+) metastatic breast cancers express mutations within the ER ligand-binding domain. While most studies focused on the constitutive ER signaling activity commonly engendered by these mutations selected during estrogen deprivation therapy, our study was aimed at investigating distinctive phenotypes conferred by different mutations within this class.

METHODS

We examined the two most prevalent mutations, D538G and Y537S, employing corroborative genome-edited and lentiviral-transduced ER+ T47D cell models. We used a luciferase-based reporter and endogenous phospho-ER immunoblot analysis to characterize the estrogen response of ER mutants and determined their resistance to known ER antagonists.

RESULTS

Consistent with their selection during estrogen deprivation therapy, these mutants conferred constitutive ER activity. While Y537S mutants showed no estrogen dependence, D538G mutants demonstrated an enhanced estrogen-dependent response. Both mutations conferred resistance to ER antagonists that was overcome at higher doses acting specifically through their ER target.

CONCLUSIONS

These observations provide a tenable hypothesis for how D538G ESR1-expressing clones can contribute to shorter progression-free survival observed in the exemestane arm of the BOLERO-2 study. Thus, in those patients with dominant D538G-expressing clones, longitudinal analysis for this mutation in circulating free DNA may prove beneficial for informing more optimal therapeutic regimens.

HCS campaign to identify selective inhibitors of IL-6-induced STAT3 pathway activation in head and neck cancer cell lines

Signal transducer and activator of transcription factor 3 (STAT3) is hyperactivated in head and neck squamous cell carcinomas (HNSCC). Cumulative evidence indicates that IL-6 production by HNSCC cells and/or stromal cells in the tumor microenvironment activates STAT3 and contributes to tumor progression and drug resistance. A library of 94,491 compounds from the Molecular Library Screening Center Network (MLSCN) was screened for the ability to inhibit interleukin-6 (IL-6)-induced pSTAT3 activation. For contractual reasons, the primary high-content screening (HCS) campaign was conducted over several months in 3 distinct phases; 1,068 (1.1%) primary HCS actives remained after cytotoxic or fluorescent outliers were eliminated. One thousand one hundred eighty-seven compounds were cherry-picked for confirmation; actives identified in the primary HCS and compounds selected by a structural similarity search of the remaining MLSCN library using hits identified in phases I and II of the screen. Actives were confirmed in pSTAT3 IC50 assays, and an IFNγ-induced pSTAT1 activation assay was used to prioritize selective inhibitors of STAT3 activation that would not inhibit STAT1 tumor suppressor functions. Two hundred three concentration-dependent inhibitors of IL-6-induced pSTAT3 activation were identified and 89 of these also produced IC50s against IFN-γ-induced pSTAT1 activation. Forty-nine compounds met our hit criteria: they reproducibly inhibited IL-6-induced pSTAT3 activation by ≥70% at 20 μM; their pSTAT3 activation IC50s were ≤25 μM; they were ≥2-fold selective for pSTAT3 inhibition over pSTAT1 inhibition; a cross target query of PubChem indicated that they were not biologically promiscuous; and they were ≥90% pure. Twenty-six chemically tractable hits that passed filters for nuisance compounds and had acceptable drug-like and ADME-Tox properties by computational evaluation were purchased for characterization. The hit structures were distributed among 5 clusters and 8 singletons. Twenty-four compounds inhibited IL-6-induced pSTAT3 activation with IC50s ≤20 μM and 13 were ≥3-fold selective versus inhibition of pSTAT1 activation. Eighteen hits inhibited the growth of HNSCC cell lines with average IC50s ≤ 20 μM. Four chemical series were progressed into lead optimization: the guanidinoquinazolines, the triazolothiadiazines, the amino alcohols, and an oxazole-piperazine singleton.

The Microphysiology Systems Database for Analyzing and Modeling Compound Interactions with Human and Animal Organ Models

Microfluidic human organ models, microphysiology systems (MPS), are currently being developed as predictive models of drug safety and efficacy in humans. To design and validate MPS as predictive of human safety liabilities requires safety data for a reference set of compounds, combined with in vitro data from the human organ models. To address this need, we have developed an internet database, the MPS database (MPS-Db), as a powerful platform for experimental design, data management, and analysis, and to combine experimental data with reference data, to enable computational modeling. The present study demonstrates the capability of the MPS-Db in early safety testing using a human liver MPS to relate the effects of tolcapone and entacapone in the in vitro model to human in vivo effects. These two compounds were chosen to be evaluated as a representative pair of marketed drugs because they are structurally similar, have the same target, and were found safe or had an acceptable risk in preclinical and clinical trials, yet tolcapone induced unacceptable levels of hepatotoxicity while entacapone was found to be safe. Results demonstrate the utility of the MPS-Db as an essential resource for relating in vitro organ model data to the multiple biochemical, preclinical, and clinical data sources on in vivo drug effects.

A metric and workflow for quality control in the analysis of heterogeneity in phenotypic profiles and screens

Heterogeneity is well recognized as a common property of cellular systems that impacts biomedical research and the development of therapeutics and diagnostics. Several studies have shown that analysis of heterogeneity: gives insight into mechanisms of action of perturbagens; can be used to predict optimal combination therapies; and can be applied to tumors where heterogeneity is believed to be associated with adaptation and resistance. Cytometry methods including high content screening (HCS), high throughput microscopy, flow cytometry, mass spec imaging and digital pathology capture cell level data for populations of cells. However it is often assumed that the population response is normally distributed and therefore that the average adequately describes the results. A deeper understanding of the results of the measurements and more effective comparison of perturbagen effects requires analysis that takes into account the distribution of the measurements, i.e. the heterogeneity. However, the reproducibility of heterogeneous data collected on different days, and in different plates/slides has not previously been evaluated. Here we show that conventional assay quality metrics alone are not adequate for quality control of the heterogeneity in the data. To address this need, we demonstrate the use of the Kolmogorov-Smirnov statistic as a metric for monitoring the reproducibility of heterogeneity in an SAR screen, describe a workflow for quality control in heterogeneity analysis. One major challenge in high throughput biology is the evaluation and interpretation of heterogeneity in thousands of samples, such as compounds in a cell-based screen. In this study we also demonstrate that three heterogeneity indices previously reported, capture the shapes of the distributions and provide a means to filter and browse big data sets of cellular distributions in order to compare and identify distributions of interest. These metrics and methods are presented as a workflow for analysis of heterogeneity in large scale biology projects.

A human liver microphysiology platform for investigating physiology, drug safety, and disease models

This paper describes the development and characterization of a microphysiology platform for drug safety and efficacy in liver models of disease that includes a human, 3D, microfluidic, four-cell, sequentially layered, self-assembly liver model (SQL-SAL); fluorescent protein biosensors for mechanistic readouts; as well as a microphysiology system database (MPS-Db) to manage, analyze, and model data. The goal of our approach is to create the simplest design in terms of cells, matrix materials, and microfluidic device parameters that will support a physiologically relevant liver model that is robust and reproducible for at least 28 days for stand-alone liver studies and microfluidic integration with other organs-on-chips. The current SQL-SAL uses primary human hepatocytes along with human endothelial (EA.hy926), immune (U937) and stellate (LX-2) cells in physiological ratios and is viable for at least 28 days under continuous flow. Approximately, 20% of primary hepatocytes and/or stellate cells contain fluorescent protein biosensors (called sentinel cells) to measure apoptosis, reactive oxygen species (ROS) and/or cell location by high content analysis (HCA). In addition, drugs, drug metabolites, albumin, urea and lactate dehydrogenase (LDH) are monitored in the efflux media. Exposure to 180 μM troglitazone or 210 μM nimesulide produced acute toxicity within 2-4 days, whereas 28 μM troglitazone produced a gradual and much delayed toxic response over 21 days, concordant with known mechanisms of toxicity, while 600 µM caffeine had no effect. Immune-mediated toxicity was demonstrated with trovafloxacin with lipopolysaccharide (LPS), but not levofloxacin with LPS. The SQL-SAL exhibited early fibrotic activation in response to 30 nM methotrexate, indicated by increased stellate cell migration, expression of alpha-smooth muscle actin and collagen, type 1, alpha 2. Data collected from the in vitro model can be integrated into a database with access to related chemical, bioactivity, preclinical and clinical information uploaded from external databases for constructing predictive models.

High-content positional biosensor screening assay for compounds to prevent or disrupt androgen receptor and transcriptional intermediary factor 2 protein-protein interactions

The androgen receptor-transcriptional intermediary factor 2 (AR-TIF2) positional protein-protein interaction (PPI) biosensor assay described herein combines physiologically relevant cell-based assays with the specificity of binding assays by incorporating structural information of AR and TIF2 functional domains along with intracellular targeting sequences and fluorescent reporters. Expression of the AR-red fluorescent protein (RFP) "prey" and TIF2-green fluorescent protein (GFP) "bait" components of the biosensor was directed by recombinant adenovirus constructs that expressed the ligand binding and activation function 2 surface domains of AR fused to RFP with nuclear localization and nuclear export sequences, and three α-helical LXXLL motifs from TIF2 fused to GFP and an HIV Rev nucleolar targeting sequence. In unstimulated cells, AR-RFP was localized predominantly to the cytoplasm and TIF2-GFP was localized to nucleoli. Dihydrotestosterone (DHT) treatment induced AR-RFP translocation into the nucleus where the PPIs between AR and TIF2 resulted in the colocalization of both biosensors within the nucleolus. We adapted the translocation enhanced image analysis module to quantify the colocalization of the AR-RFP and TIF2-GFP biosensors in images acquired on the ImageXpress platform. DHT induced a concentration-dependent AR-TIF2 colocalization and produced a characteristic condensed punctate AR-RFP PPI nucleolar distribution pattern. The heat-shock protein 90 inhibitor 17-N-allylamino-17-demethoxygeldanamycin (17-AAG) and antiandrogens flutamide and bicalutamide inhibited DHT-induced AR-TIF2 PPI formation with 50% inhibition concentrations (IC50s) of 88.5±12.5 nM, 7.6±2.4 μM, and 1.6±0.4 μM, respectively. Images of the AR-RFP distribution phenotype allowed us to distinguish between 17-AAG and flutamide, which prevented AR translocation, and bicalutamide, which blocked AR-TIF2 PPIs. We screened the Library of Pharmacologically Active Compounds (LOPAC) set for compounds that inhibited AR-TIF2 PPI formation or disrupted preexisting complexes. Eleven modulators of steroid family nuclear receptors (NRs) and 6 non-NR ligands inhibited AR-TIF2 PPI formation, and 10 disrupted preexisting complexes. The hits appear to be either AR antagonists or nonspecific inhibitors of NR activation and trafficking. Given that the LOPAC set represents such a small and restricted biological and chemical diversity, it is anticipated that screening a much larger and more diverse compound library will be required to find AR-TIF2 PPI inhibitors/disruptors. The AR-TIF2 protein-protein interaction biosensor (PPIB) approach offers significant promise for identifying molecules with potential to modulate AR transcriptional activity in a cell-specific manner that is distinct from the existing antiandrogen drugs that target AR binding or production. Small molecules that disrupt AR signaling at the level of AR-TIF2 PPIs may also overcome the development of resistance and progression to castration-resistant prostate cancer.

Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology.

In vitro platforms for evaluating liver toxicity

The liver is a heterogeneous organ with many vital functions, including metabolism of pharmaceutical drugs and is highly susceptible to injury from these substances. The etiology of drug-induced liver disease is still debated although generally regarded as a continuum between an activated immune response and hepatocyte metabolic dysfunction, most often resulting from an intermediate reactive metabolite. This debate stems from the fact that current animal and in vitro models provide limited physiologically relevant information, and their shortcomings have resulted in "silent" hepatotoxic drugs being introduced into clinical trials, garnering huge financial losses for drug companies through withdrawals and late stage clinical failures. As we advance our understanding into the molecular processes leading to liver injury, it is increasingly clear that (a) the pathologic lesion is not only due to liver parenchyma but is also due to the interactions between the hepatocytes and the resident liver immune cells, stellate cells, and endothelial cells; and (b) animal models do not reflect the human cell interactions. Therefore, a predictive human, in vitro model must address the interactions between the major human liver cell types and measure key determinants of injury such as the dosage and metabolism of the drug, the stress response, cholestatic effect, and the immune and fibrotic response. In this mini-review, we first discuss the current state of macro-scale in vitro liver culture systems with examples that have been commercialized. We then introduce the paradigm of microfluidic culture systems that aim to mimic the liver with physiologically relevant dimensions, cellular structure, perfusion, and mass transport by taking advantage of micro and nanofabrication technologies. We review the most prominent liver-on-a-chip platforms in terms of their physiological relevance and drug response. We conclude with a commentary on other critical advances such as the deployment of fluorescence-based biosensors to identify relevant toxicity pathways, as well as computational models to create a predictive tool.

High-content pSTAT3/1 imaging assays to screen for selective inhibitors of STAT3 pathway activation in head and neck cancer cell lines

The oncogenic transcription factor signal transducer and activator of transcription 3 (STAT3) is hyperactivated in most cancers and represents a plausible therapeutic target. In the absence of STAT3-selective small-molecule inhibitors, we sought to develop pSTAT3/1 high-content imaging (HCS) assays to screen for selective inhibitors of STAT3 pathway activation in head and neck squamous cell carcinomas (HNSCC) tumor cell lines. Based on the expression of the interleukin-6 (IL-6)Rα and gp130 subunits of the IL-6 receptor complex and STAT3, we selected the Cal33 HNSCC cell line as our model. After developing image acquisition and analysis procedures, we rigorously investigated the cytokine activation responses to optimize the dynamic ranges of both assays and demonstrated that the pan-Janus kinase inhibitor pyridone 6 nonselectively inhibited pSTAT3 and pSTAT1 activation with 50% inhibition concentrations of 7.19 ± 4.08 and 16.38 ± 8.45 nM, respectively. The optimized pSTAT3 HCS assay performed very well in a pilot screen of 1,726 compounds from the Library of Pharmacologically Active Compounds and the National Institutes of Health clinical collection sets, and we identified 51 inhibitors of IL-6-induced pSTAT3 activation. However, only three of the primary HCS actives selectively inhibited STAT3 compared with STAT1. Our follow-up studies indicated that the nonselective inhibition of cytokine induced pSTAT3 and pSTAT1 activation by G-alpha stimulatory subunit-coupled G-protein-coupled receptor agonists, and forskolin was likely due to cyclic adenosine monophosphate-mediated up-regulation of suppressors of cytokine signaling 3. Azelastine, an H1 receptor antagonist approved for the treatment of seasonal allergic rhinitis, nonallergic vasomotor rhinitis, and ocular conjunctivitis, was subsequently confirmed as a selective inhibitor of IL-6-induced pSTAT3 activation that also reduced the growth of HNSCC cell lines. These data illustrate the power of a chemical biology approach to lead generation that utilizes fully developed and optimized HCS assays as phenotypic screens to interrogate specific signaling pathways.

Towards a three-dimensional microfluidic liver platform for predicting drug efficacy and toxicity in humans

Although the process of drug development requires efficacy and toxicity testing in animals prior to human testing, animal models have limited ability to accurately predict human responses to xenobiotics and other insults. Societal pressures are also focusing on reduction of and, ultimately, replacement of animal testing. However, a variety of in vitro models, explored over the last decade, have not been powerful enough to replace animal models. New initiatives sponsored by several US federal agencies seek to address this problem by funding the development of physiologically relevant human organ models on microscopic chips. The eventual goal is to simulate a human-on-a-chip, by interconnecting the organ models, thereby replacing animal testing in drug discovery and development. As part of this initiative, we aim to build a three-dimensional human liver chip that mimics the acinus, the smallest functional unit of the liver, including its oxygen gradient. Our liver-on-a-chip platform will deliver a microfluidic three-dimensional co-culture environment with stable synthetic and enzymatic function for at least 4 weeks. Sentinel cells that contain fluorescent biosensors will be integrated into the chip to provide multiplexed, real-time readouts of key liver functions and pathology. We are also developing a database to manage experimental data and harness external information to interpret the multimodal data and create a predictive platform.

Alkylation sensitivity screens reveal a conserved cross-species functionome

To identify genes that contribute to chemotherapy resistance in glioblastoma, we conducted a synthetic lethal screen in a chemotherapy-resistant glioblastoma-derived cell line with the clinical alkylator temozolomide (TMZ) and an siRNA library tailored toward "druggable" targets. Select DNA repair genes in the screen were validated independently, confirming the DNA glycosylases uracil-DNA glycosylase (UNG) and A/G-specific adenine DNA glycosylase (MYH) as well as methylpurine-DNA glycosylase (MPG) to be involved in the response to high dose TMZ. The involvement of UNG and MYH is likely the result of a TMZ-induced burst of reactive oxygen species. We then compared the human TMZ sensitizing genes identified in our screen with those previously identified from alkylator screens conducted in Escherichia coli and Saccharomyces cerevisiae. The conserved biologic processes across all three species compose an alkylation functionome that includes many novel proteins not previously thought to impact alkylator resistance. This high-throughput screen, validation and cross-species analysis was then followed by a mechanistic analysis of two essential nodes: base excision repair (BER) DNA glycosylases (UNG, human and mag1, S. cerevisiae) and protein modification systems, including UBE3B and ICMT in human cells or pby1, lip22, stp22 and aim22 in S. cerevisiae. The conserved processes of BER and protein modification were dual targeted and yielded additive sensitization to alkylators in S. cerevisiae. In contrast, dual targeting of BER and protein modification genes in human cells did not increase sensitivity, suggesting an epistatic relationship. Importantly, these studies provide potential new targets to overcome alkylating agent resistance.

Development and validation of a high-content screening assay to identify inhibitors of cytoplasmic dynein-mediated transport of glucocorticoid receptor to the nucleus

Rapid ligand-induced trafficking of glucocorticoid nuclear hormone receptor (GR) from the cytoplasm to the nucleus is an extensively studied model for intracellular retrograde cargo transport employed in constructive morphogenesis and many other cellular functions. Unfortunately, potent and selective small-molecule disruptors of this process are lacking, which has restricted pharmacological investigations. We describe here the development and validation of a 384-well high-content screening (HCS) assay to identify inhibitors of the rapid ligand-induced retrograde translocation of cytoplasmic glucocorticoid nuclear hormone receptor green fluorescent fusion protein (GR-GFP) into the nuclei of 3617.4 mouse mammary adenocarcinoma cells. We selected 3617.4 cells, because they express GR-GFP under the control of a tetracycline (Tet)-repressible promoter and are exceptionally amenable to image acquisition and analysis procedures. Initially, we investigated the time-dependent expression of GR-GFP in 3617.4 cells under Tet-on and Tet-off control to determine the optimal conditions to measure dexamethasone (Dex)-induced GR-GFP nuclear translocation on the ArrayScan-VTI automated imaging platform. We then miniaturized the assay into a 384-well format and validated the performance of the GR-GFP nuclear translocation HCS assay in our 3-day assay signal window and dimethylsulfoxide validation tests. The molecular chaperone heat shock protein 90 (Hsp90) plays an essential role in the regulation of GR steroid binding affinity and ligand-induced retrograde trafficking to the nucleus. We verified that the GR-GFP HCS assay captured the concentration-dependent inhibition of GR-GFP nuclear translocation by 17-AAG, a benzoquinone ansamycin that selectively blocks the binding and hydrolysis of ATP by Hsp90. We screened the 1280 compound library of pharmacologically active compounds set in the Dex-induced GR-GFP nuclear translocation assay and used the multi-parameter HCS data to eliminate cytotoxic compounds and fluorescent outliers. We identified five qualified hits that inhibited the rapid retrograde trafficking of GR-GFP in a concentration-dependent manner: Bay 11-7085, 4-phenyl-3-furoxancarbonitrile, parthenolide, apomorphine, and 6-nitroso-1,2-benzopyrone. The data presented here demonstrate that the GR-GFP HCS assay provides an effective phenotypic screen and support the proposition that screening a larger library of diversity compounds will yield novel small-molecule probes that will enable the further exploration of intracellular retrograde transport of cargo along microtubules, a process which is essential to the morphogenesis and function of all cells.

Discovery of diverse small molecule chemotypes with cell-based PKD1 inhibitory activity

Protein kinase D (PKD) is a novel family of serine/threonine kinases regulated by diacylglycerol, which is involved in multiple cellular processes and various pathological conditions. The limited number of cell-active, selective inhibitors has historically restricted biochemical and pharmacological studies of PKD. We now markedly expand the PKD1 inhibitory chemotype inventory with eleven additional novel small molecule PKD1 inhibitors derived from our high throughput screening campaigns. The in vitro IC(50)s for these eleven compounds ranged in potency from 0.4 to 6.1 µM with all of the evaluated compounds being competitive with ATP. Three of the inhibitors (CID 1893668, (1Z)-1-(3-ethyl-5-methoxy-1,3-benzothiazol-2-ylidene)propan-2-one; CID 2011756, 5-(3-chlorophenyl)-N-[4-(morpholin-4-ylmethyl)phenyl]furan-2-carboxamide; CID 5389142, (6Z)-6-[4-(3-aminopropylamino)-6-methyl-1H-pyrimidin-2-ylidene]cyclohexa-2,4-dien-1-one) inhibited phorbol ester-induced endogenous PKD1 activation in LNCaP prostate cancer cells in a concentration-dependent manner. The specificity of these compounds for PKD1 inhibitory activity was supported by kinase assay counter screens as well as by bioinformatics searches. Moreover, computational analyses of these novel cell-active PKD1 inhibitors indicated that they were structurally distinct from the previously described cell-active PKD1 inhibitors while computational docking of the new cell-active compounds in a highly conserved ATP-binding cleft suggests opportunities for structural modification. In summary, we have discovered novel PKD1 inhibitors with in vitro and cell-based inhibitory activity, thus successfully expanding the structural diversity of small molecule inhibitors available for this important pharmacological target.

Identification of chemosensitivity nodes for vinblastine through small interfering RNA high-throughput screens

Discovering chemosensitivity pathways or nodes is an attractive strategy for formulating new drug combinations for cancer. Microtubules are among the most successful anticancer drug targets. Therefore, we implemented a small interfering RNA (siRNA) synthetic lethal screen targeting 5520 unique druggable genes to identify novel chemosensitivity nodes for vinblastine, a microtubule-destabilizing agent used clinically. We transiently transfected human glioblastoma cells with siRNAs for 48 h and then treated cells with a sublethal concentration of vinblastine. Forty-eight hours later, we analyzed cell viability and, using a series of statistical methods, identified 65 gene products that, when suppressed, sensitized glioblastoma cells to vinblastine. After completion of the secondary assays, we focused on one siRNA, B-cell lymphoma extra large (BCL-xL), because of its role in the intrinsic apoptosis signaling pathway as well as the availability of pharmacological inhibitors. We found that nontoxic concentrations of 4-[4-[[2-(4-chlorophenyl)-5,5-dimethylcyclohexen-1-yl]methyl]piperazin-1-yl]-N-[4-[[(2R)-4-morpholin-4-yl-1-phenylsulfanylbutan-2-yl]amino]-3-(trifluoromethylsulfonyl)phenyl]sulfonylbenzamide (ABT-263), an inhibitor of the BCL-2 family members (BCL-2, BCL-xL, and BCL-w), sensitized glioblastoma and non-small-cell lung cancer cells to vinblastine and induced apoptosis through the intrinsic cell death pathway. These results illustrate the usefulness of unbiased siRNA screens as a method for identifying potential novel anticancer therapeutic combinations.

Characterization and optimization of a novel protein-protein interaction biosensor high-content screening assay to identify disruptors of the interactions between p53 and hDM2

We present here the characterization and optimization of a novel imaging-based positional biosensor high-content screening (HCS) assay to identify disruptors of p53-hDM2 protein-protein interactions (PPIs). The chimeric proteins of the biosensor incorporated the N-terminal PPI domains of p53 and hDM2, protein targeting sequences (nuclear localization and nuclear export sequence), and fluorescent reporters, which when expressed in cells could be used to monitor p53-hDM2 PPIs through changes in the subcellular localization of the hDM2 component of the biosensor. Coinfection with the recombinant adenovirus biosensors was used to express the NH-terminal domains of p53 and hDM2, fused to green fluorescent protein and red fluorescent protein, respectively, in U-2 OS cells. We validated the p53-hDM2 PPI biosensor (PPIB) HCS assay with Nutlin-3, a compound that occupies the hydrophobic pocket on the surface of the N-terminus of hDM2 and blocks the binding interactions with the N-terminus of p53. Nutlin-3 disrupted the p53-hDM2 PPIB in a concentration-dependent manner and provided a robust, reproducible, and stable assay signal window that was compatible with HCS. The p53-hDM2 PPIB assay was readily implemented in HCS and we identified four (4) compounds in the 1,280-compound Library of Pharmacologically Active Compounds that activated the p53 signaling pathway and elicited biosensor signals that were clearly distinct from the responses of inactive compounds. Anthracycline (topoisomerase II inhibitors such as mitoxantrone and ellipticine) and camptothecin (topoisomerase I inhibitor) derivatives including topotecan induce DNA double strand breaks, which activate the p53 pathway through the ataxia telangiectasia mutated-checkpoint kinase 2 (ATM-CHK2) DNA damage response pathway. Although mitoxantrone, ellipticine, camptothecin, and topotecan all exhibited concentration-dependent disruption of the p53-hDM2 PPIB, they were much less potent than Nutlin-3. Further, their corresponding cellular images and quantitative HCS data did not completely match the Nutlin-3 phenotypic profile.

Identifying actives from HTS data sets: practical approaches for the selection of an appropriate HTS data-processing method and quality control review

High-throughput screening (HTS) has achieved a dominant role in drug discovery over the past 2 decades. The goal of HTS is to identify active compounds (hits) by screening large numbers of diverse chemical compounds against selected targets and/or cellular phenotypes. The HTS process consists of multiple automated steps involving compound handling, liquid transfers, and assay signal capture, all of which unavoidably contribute to systematic variation in the screening data. The challenge is to distinguish biologically active compounds from assay variability. Traditional plate controls-based and non-controls-based statistical methods have been widely used for HTS data processing and active identification by both the pharmaceutical industry and academic sectors. More recently, improved robust statistical methods have been introduced, reducing the impact of systematic row/column effects in HTS data. To apply such robust methods effectively and properly, we need to understand their necessity and functionality. Data from 6 HTS case histories are presented to illustrate that robust statistical methods may sometimes be misleading and can result in more, rather than less, false positives or false negatives. In practice, no single method is the best hit detection method for every HTS data set. However, to aid the selection of the most appropriate HTS data-processing and active identification methods, the authors developed a 3-step statistical decision methodology. Step 1 is to determine the most appropriate HTS data-processing method and establish criteria for quality control review and active identification from 3-day assay signal window and DMSO validation tests. Step 2 is to perform a multilevel statistical and graphical review of the screening data to exclude data that fall outside the quality control criteria. Step 3 is to apply the established active criterion to the quality-assured data to identify the active compounds.

Automated high-content live animal drug screening using C. elegans expressing the aggregation prone serpin α1-antitrypsin Z

The development of preclinical models amenable to live animal bioactive compound screening is an attractive approach to discovering effective pharmacological therapies for disorders caused by misfolded and aggregation-prone proteins. In general, however, live animal drug screening is labor and resource intensive, and has been hampered by the lack of robust assay designs and high throughput work-flows. Based on their small size, tissue transparency and ease of cultivation, the use of C. elegans should obviate many of the technical impediments associated with live animal drug screening. Moreover, their genetic tractability and accomplished record for providing insights into the molecular and cellular basis of human disease, should make C. elegans an ideal model system for in vivo drug discovery campaigns. The goal of this study was to determine whether C. elegans could be adapted to high-throughput and high-content drug screening strategies analogous to those developed for cell-based systems. Using transgenic animals expressing fluorescently-tagged proteins, we first developed a high-quality, high-throughput work-flow utilizing an automated fluorescence microscopy platform with integrated image acquisition and data analysis modules to qualitatively assess different biological processes including, growth, tissue development, cell viability and autophagy. We next adapted this technology to conduct a small molecule screen and identified compounds that altered the intracellular accumulation of the human aggregation prone mutant that causes liver disease in α1-antitrypsin deficiency. This study provides powerful validation for advancement in preclinical drug discovery campaigns by screening live C. elegans modeling α1-antitrypsin deficiency and other complex disease phenotypes on high-content imaging platforms.

Implementation of a 220,000-compound HCS campaign to identify disruptors of the interaction between p53 and hDM2 and characterization of the confirmed hits

In recent years, advances in structure-based drug design and the development of an impressive variety of high-throughput screening (HTS) assay formats have yielded an expanding list of protein-protein interaction inhibitors. Despite these advances, protein-protein interaction targets are still widely considered difficult to disrupt with small molecules. The authors present here the results from screening 220,017 compounds from the National Institute of Health's small-molecule library in a novel p53-hDM2 protein-protein interaction biosensor (PPIB) assay. The p53-hDM2 positional biosensor performed robustly and reproducibly throughout the high-content screening (HCS) campaign, and analysis of the multiparameter data from images of the 3 fluorescent channels enabled the authors to identify and eliminate compounds that were cytotoxic or fluorescent artifacts. The HCS campaign yielded 3 structurally related methylbenzo-naphthyridin-5-amine (MBNA) hits with IC(50)s between 30 and 50 microM in the p53-hDM2 PPIB. In HCT116 cells with wild-type (WT) p53, the MBNAs enhanced p53 protein levels, increased the expression of p53 target genes, caused a cell cycle arrest in G1, induced apoptosis, and inhibited cell proliferation with an IC(50) ~4 microM. The prototype disruptor of p53-hDM2 interactions Nutlin-3 was more potent than the MBNAs in the p53-hDM2 PPIB assay but produced equivalent biological results in HCT116 cells WT for p53. Unlike Nutlin-3, however, MBNAs also increased the percentage of apoptosis in p53 null cells and exhibited similar potencies for growth inhibition in isogenic cell lines null for p53 or p21. Neither the MBNAs nor Nutin-3 caused cell cycle arrest in p53 null HCT116 cells. Despite the relatively modest size of the screening library, the combination of a novel p53-hDM2 PPIB assay together with an automated imaging HCS platform and image analysis methods enabled the discovery of a novel chemotype series that disrupts p53-hDM2 interactions in cells.

Profiling the NIH Small Molecule Repository for compounds that generate H2O2 by redox cycling in reducing environments

We have screened the Library of Pharmacologically Active Compounds (LOPAC) and the National Institutes of Health (NIH) Small Molecule Repository (SMR) libraries in a horseradish peroxidase-phenol red (HRP-PR) H2O2 detection assay to identify redox cycling compounds (RCCs) capable of generating H2O2 in buffers containing dithiothreitol (DTT). Two RCCs were identified in the LOPAC set, the ortho-naphthoquinone beta-lapachone and the para-naphthoquinone NSC 95397. Thirty-seven (0.02%) concentration-dependent RCCs were identified from 195,826 compounds in the NIH SMR library; 3 singleton structures, 9 ortho-quinones, 2 para-quinones, 4 pyrimidotriazinediones, 15 arylsulfonamides, 2 nitrothiophene-2-carboxylates, and 2 tolyl hydrazides. Sixty percent of the ortho-quinones and 80% of the pyrimidotriazinediones in the library were confirmed as RCCs. In contrast, only 3.9% of the para-quinones were confirmed as RCCs. Fifteen of the 251 arylsulfonamides in the library were confirmed as RCCs, and since we screened 17,868 compounds with a sulfonamide functional group we conclude that the redox cycling activity of the arylsulfonamide RCCs is due to peripheral reactive enone, aromatic, or heterocyclic functions. Cross-target queries of the University of Pittsburgh Drug Discovery Institute (UPDDI) and PubChem databases revealed that the RCCs exhibited promiscuous bioactivity profiles and have populated both screening databases with significantly higher numbers of active flags than non-RCCs. RCCs were promiscuously active against protein targets known to be susceptible to oxidation, but were also active in cell growth inhibition assays, and against other targets thought to be insensitive to oxidation. Profiling compound libraries or the hits from screening campaigns in the HRP-PR H(2)O(2) detection assay significantly reduce the timelines and resources required to identify and eliminate promiscuous nuisance RCCs from the candidates for lead optimization.

Functional genomic analysis of glioblastoma multiforme through short interfering RNA screening: a paradigm for therapeutic development

Glioblastoma multiforme (GBM) is a high-grade brain malignancy arising from astrocytes. Despite aggressive surgical approaches, optimized radiation therapy regimens, and the application of cytotoxic chemotherapies, the median survival of patients with GBM from time of diagnosis remains less than 15 months, having changed little in decades. Approaches that target genes and biological pathways responsible for tumorigenesis or potentiate the activity of current therapeutic modalities could improve treatment efficacy. In this regard, several genomic and proteomic strategies promise to impact significantly on the drug discovery process. High-throughput genome-wide screening with short interfering RNA (siRNA) is one strategy for systematically exploring possible therapeutically relevant targets in GBM. Statistical methods and protein-protein interaction network databases can also be applied to the screening data to explore the genes and pathways that underlie the pathological basis and development of GBM. In this study, we highlight several genome-wide siRNA screens and implement these experimental concepts in the T98G GBM cell line to uncover the genes and pathways that regulate GBM cell death and survival. These studies will ultimately influence the development of a new avenue of neurosurgical therapy by placing the drug discovery process in the context of the entire biological system.

Cdc25B dual-specificity phosphatase inhibitors identified in a high-throughput screen of the NIH compound library

The University of Pittsburgh Molecular Library Screening Center (Pittsburgh, PA) conducted a screen with the National Institutes of Health compound library for inhibitors of in vitro cell division cycle 25 protein (Cdc25) B activity during the pilot phase of the Molecular Library Screening Center Network. Seventy-nine (0.12%) of the 65,239 compounds screened at 10 muM met the active criterion of > or =50% inhibition of Cdc25B activity, and 25 (31.6%) of these were confirmed as Cdc25B inhibitors with 50% inhibitory concentration (IC(50)) values <50 microM. Thirteen of the Cdc25B inhibitors were represented by singleton chemical structures, and 12 were divided among four clusters of related structures. Thirteen (52%) of the Cdc25B inhibitor hits were quinone-based structures. The Cdc25B inhibitors were further characterized in a series of in vitro secondary assays to confirm their activity, to determine their phosphatase selectivity against two other dual-specificity phosphatases, mitogen-activated protein kinase phosphatase (MKP)-1 and MKP-3, and to examine if the mechanism of Cdc25B inhibition involved oxidation and inactivation. Nine Cdc25B inhibitors did not appear to affect Cdc25B through a mechanism involving oxidation because they did not generate detectable amounts of H(2)O(2) in the presence of dithiothreitol, and their Cdc25B IC(50) values were not significantly affected by exchanging the dithiothreitol for beta-mercaptoethanol or reduced glutathione or by adding catalase to the assay. Six of the nonoxidative hits were selective for Cdc25B inhibition versus MKP-1 and MKP-3, but only the two bisfuran-containing hits, PubChem substance identifiers 4258795 and 4260465, significantly inhibited the growth of human MBA-MD-435 breast and PC-3 prostate cancer cell lines. To confirm the structure and biological activity of 4260465, the compound was resynthesized along with two analogs. Neither of the substitutions to the two analogs was tolerated, and only the resynthesized hit 26683752 inhibited Cdc25B activity in vitro (IC(50) = 13.83 +/- 1.0 microM) and significantly inhibited the growth of the MBA-MD-435 breast and PC-3 prostate cancer cell lines (IC(50) = 20.16 +/- 2.0 microM and 24.87 +/- 2.25 microM, respectively). The two bis-furan-containing hits identified in the screen represent novel nonoxidative Cdc25B inhibitor chemotypes that block tumor cell proliferation. The availability of non-redox active Cdc25B inhibitors should provide valuable tools to explore the inhibition of the Cdc25 phosphatases as potential mono- or combination therapies for cancer.

Designing, optimizing, and implementing high-throughput siRNA genomic screening with glioma cells for the discovery of survival genes and novel drug targets

A major challenge for the treatment of cancers, such as glioblastoma multiforme (GBM), has been resistance to radiation and cancer chemotherapeutics. Short interfering RNA (siRNA) based screening may facilitate the identification of genes and pathways essential for cancer cell survival and could enable a more targeted therapeutic approach for the treatment of GBM. Although the commercial availability of siRNA libraries has expanded greatly, detailed methods for the implementation and analysis of genome-scale screens are largely lacking. To annotate the essential genes and pathways for glioma cell survival, we designed, optimized, and implemented a high-throughput siRNA screen in the highly drug and radiation resistant T98G glioma cell line. We developed a rapid, readily available, and simple strategy to optimize siRNA transfection assays in a 384-well plate format based on immunofluorescence studies and inhibition of the non-essential, endogenous gene lamin A/C. We used these transfection conditions to successfully screen a library of 1056 siRNAs targeting 352 unique human genes in a cell-based one gene per well format to identify the genes essential for glioma cell survival and assess the quality of the screening conditions prior to large-scale screening. After developing and applying a median-based outlier detection algorithm for post-screen analysis, we identified the Ras oncogene family member RAN as an essential gene for glioma cell survival. Successful implementation and analysis of this siRNA screen validates our transfection optimization approach and provides guidance for the rapid development of high-throughput siRNA screens in human glioma cells.

Identification of survival genes in human glioblastoma cells by small interfering RNA screening

Target identification and validation remain difficult steps in the drug discovery process, and uncovering the core genes and pathways that are fundamental for cancer cell survival may facilitate this process. Glioblastoma represents a challenging form of cancer for chemotherapy. Therefore, we assayed 16,560 short interfering RNA (siRNA) aimed at identifying which of the 5520 unique therapeutically targetable gene products were important for the survival of human glioblastoma. We analyzed the viability of T98G glioma cells 96 h after siRNA transfection with two orthogonal statistical methods and identified 55 survival genes that encoded proteases, kinases, and transferases. It is noteworthy that 22% (12/55) of the survival genes were constituents of the 20S and 26S proteasome subunits. An expression survey of a panel of glioma cell lines demonstrated expression of the proteasome component PSMB4, and the validity of the proteasome complex as a target for survival inhibition was confirmed in a series of glioma and nonglioma cell lines by pharmacological inhibition and RNA interference. Biological networks were built with the other survival genes using a protein-protein interaction network, which identified clusters of cellular processes, including protein ubiquitination, purine and pyrimidine metabolism, nucleotide excision repair, and NF-kappaB signaling. The results of this study should broaden our understanding of the core genes and pathways that regulate cell survival; through either small molecule inhibition or RNA interference, we highlight the potential significance of proteasome inhibition.

Development of a 384-well colorimetric assay to quantify hydrogen peroxide generated by the redox cycling of compounds in the presence of reducing agents

We report here the development and optimization of a simple 384-well colorimetric assay to measure H(2)O(2) generated by the redox cycling of compounds incubated with reducing agents in high-throughput screening (HTS) assay buffers. The phenol red-horseradish peroxidase (HRP) assay readily detected H(2)O(2) either added exogenously or generated by the redox cycling of compounds in dithiothreitol (DTT). The generation of H(2)O(2) was dependent on the concentration of both the compound and DTT and was abolished by catalase. Although both DTT and tris(2-carboxyethyl) phosphine sustain the redox cycling generation of H(2)O(2) by a model quinolinedione, 6-chloro-7-(2-morpholin-4-yl-ethylamino)-quinoline-5,8-dione (NSC 663284; DA3003-1), other reducing agents such as beta-mercaptoethanol, glutathione, and cysteine do not. The assay is compatible with HTS. Once terminated, the assay signal was stable for at least 5 h, allowing for a reasonable throughput. The assay tolerated up to 20% dimethyl sulfoxide, allowing a wide range of compound concentrations to be tested. The assay signal window was robust and reproducible with average Z-factors of > or =0.8, and the redox cycling generation of H(2)O(2) by DA3003-1 in DTT exhibited an average 50% effective concentration of 0.830 +/- 0.068 microM. Five of the mitogen-activated protein kinase phosphatase (MKP) 1 inhibitors identified in an HTS were shown to generate H(2)O(2) in the presence of DTT, and their inhibition of MKP-1 activity was shown to be time dependent and was abolished or significantly reduced by either 100 U of catalase or by higher DTT levels. A cross-target query of the PubChem database with three structurally related pyrimidotriazinediones revealed active flags in 36-39% of the primary screening assays. Activity was confirmed against a number of targets containing active site cysteines, including protein tyrosine phosphatases, cathepsins, and caspases, as well as a number of cellular cytotoxicity assays. Rather than utilize resources to conduct a hit characterization effort involving several secondary assays, the phenol red-HRP assay provides a simple, rapid, sensitive, and inexpensive method to identify compounds that redox cycle in DTT or tris(2-carboxyethyl)phosphine to produce H(2)O(2) that may indirectly modulate target activity and represent promiscuous false-positives from a primary screen.

HTS identifies novel and specific uncompetitive inhibitors of the two-component NS2B-NS3 proteinase of West Nile virus

West Nile virus (WNV), a member of the Flavividae family, is a mosquito-borne, emerging pathogen. In addition to WNV, the family includes dengue, yellow fever, and Japanese encephalitis viruses, which affect millions of individuals worldwide. Because countermeasures are currently unavailable, flaviviral therapy is urgently required. The flaviviral two-component nonstructural NS2B-NS3 proteinase (protease [pro]) is essential for viral life cycle and, consequently, is a promising drug target. We report here the results of the miniaturization of an NS2B-NS3pro activity assay, followed by high-throughput screening of the National Institutes of Health's 65,000 compound library and identification of novel, uncompetitive inhibitors of WNV NS2B-NS3pro that appear to interfere with the productive interactions of the NS2B cofactor with the NS3pro domain. We anticipate that following structure optimization, the identified probes could form the foundation for the design of novel and specific therapeutics for WNV infection. We also provide the structural basis for additional species-selective allosteric inhibitors of flaviviruses.

Development and implementation of a miniaturized high-throughput time-resolved fluorescence energy transfer assay to identify small molecule inhibitors of polo-like kinase 1

Polo-like kinase (Plk) 1 is a key enzyme involved in regulating the mammalian cell cycle that is also a validated anticancer drug target. Nonetheless, there are relatively few readily available potent and selective small molecule inhibitors of Plk1. To increase the availability of pharmacologically valuable Plk1 inhibitors, we describe herein the development, variability assessment, validation, and implementation of a 384-well automated, miniaturized high-throughput time-resolved fluorescence energy transfer screening assay designed to identify Plk1 kinase inhibitors. Using a small molecule library of pharmaceutically active compounds to gauge high-throughput assay robustness and reproducibility, we found nine general kinase inhibitors, including H-89, which was selected as the minimum control. We then interrogated a 97,101 compound library from the National Institutes of Health repository for small molecule inhibitors of Plk1 kinase activity. The initial primary hit rate in a single 10 microM concentration format was 0.21%. Hit compounds were subjected to concentration-response confirmation and interference assays. Identified in the screen were seven compounds with 50% inhibitory concentration (IC50) values below 1 microM, 20 compounds with IC50 values between 1 microM and 5 microM, and eight compounds with IC50 values between 5 and 10 microM, which could be assigned to seven distinct chemotype classes. Hit compounds were also examined for their ability to inhibit other kinases such as protein kinase D, focal adhesion kinase, rho-associated coiled coil protein kinase 2, c-jun NH2-terminal kinase 3, and protein kinase A via experimentation or data-mining. These compounds should be useful as probes for the biological activity of Plk1 and as leads for the development of new selective inhibitors of Plk1.

Development and Implementation of a 384-Well Homogeneous Fluorescence Intensity High-Throughput Screening Assay to Identify Mitogen-Activated Protein Kinase Phosphatase-1 Dual-Specificity Protein Phosphatase Inhibitors

We report here the miniaturization, development, and implementation of a homogeneous 384-well fluorescence intensity high-throughput screening (HTS) assay for identifying mitogen-activated protein kinase (MAPK) phosphatase-1 (MKP-1) dual-specificity phosphatase inhibitors. As part of the National Institutes of Health (NIH) Molecular Libraries Screening Center Network (MLSCN), the MKP-1 assay was utilized to screen an NIH diversity library of 65,239 compounds for inhibitors of MKP-1 activity at 10 microM and was also used to confirm the concentration dependence of active agents identified in the primary screen. We observed 100 (0.15%) compounds that inhibited MKP-1 in vitro by > or =50% at 10 microM in the primary assay, and 46 of the 100 compounds were confirmed as concentration-dependent inhibitors of MKP-1 with 50% inhibitory concentration (IC(50)) values of <50 microM; four exhibited IC(50) values <1.0 microM, six produced IC(50) values in the 1-10 microM range, and 36 produced IC(50) values in the 10-50 microM range. A clustering and classification analysis of the compound structures of the 46 confirmed MKP-1 inhibitors produced 29 singleton structures and seven clusters of related structures. Some MKP-1 inhibitors were members of structural classes or contained substructure pharmacophores that previously were reported to inhibit either MKP-1 or other protein tyrosine phosphatases, validating the HTS assay. Importantly, we have identified several attractive and novel MKP-1 inhibitor structures that warrant further investigation as potential probes to study the biology of MKP-1 and its role in controlling the amplitude and/or duration of MAPK signaling, cell survival, and tumor progression.

Development and optimization of high-throughput in vitro protein phosphatase screening assays

We describe here detailed protocols to design, optimize and validate in vitro phosphatase assays that we have utilized to conduct high-throughput screens for inhibitors of dual-specificity phosphatases: CDC25B, mitogen-activated protein kinase phosphatase (MKP)-1 and MKP-3. We provide details of the critical steps that are needed to effectively miniaturize the assay into a 384-well, high-throughput format that is both reproducible and cost effective. In vitro phosphatase assays that are optimized according to these protocols should satisfy the assay performance criteria required for a robust high-throughput assay with Z-factors >0.5, and with low intra-plate, inter-plate and day-to-day variability (CV <20%). Assuming the availability of sufficient active phosphatase enzyme and access to appropriate liquid handling automation and detection instruments, a single investigator should be able to develop a 384-well format high-throughput assay in a period of 3-4 weeks.