In vitro, high-throughput screening (HTS) assays are seeing increasing use in toxicity testing. HTS assays can simultaneously test many chemicals, but have seen limited use in the regulatory arena, in part because of the need to undergo rigorous, time-consuming formal validation. Here we discuss streamlining the validation process, specifically for prioritization applications in which HTS assays are used to identify a high-concern subset of a collection of chemicals. The high-concern chemicals could then be tested sooner rather than later in standard guideline bioassays. The streamlined validation process would continue to ensure the reliability and relevance of assays for this application. We discuss the following practical guidelines: (1) follow current validation practice to the extent possible and practical; (2) make increased use of reference compounds to better demonstrate assay reliability and relevance; (3) deemphasize the need for cross-laboratory testing, and; (4) implement a web-based, transparent and expedited peer review process.
Validation; in vitro; high-throughput screening
The constitutive androstane receptor (CAR, NR1I3) is a xenobiotic sensor governing the transcription of numerous hepatic genes associated with drug metabolism and clearance. Recent evidence suggests that CAR also modulates energy homeostasis and cancer development. Thus, identification of novel human (h) CAR activators is of both clinical importance and scientific interest.
Docking and ligand-based structure-activity models were used for virtual screening of a database containing over 2000 FDA-approved drugs. Identified lead compounds were evaluated in cell-based reporter assays to determine hCAR activation. Potential activators were further tested in human primary hepatocytes (HPHs) for the expression of the prototypical hCAR target gene CYP2B6.
Nineteen lead compounds with optimal modeling parameters were selected for biological evaluation. Seven of the 19 leads exhibited moderate to potent activation of hCAR. Five out of the seven compounds translocated hCAR from the cytoplasm to the nucleus of HPHs in a concentration-dependent manner. These compounds also induce the expression of CYP2B6 in HPHs with rank-order of efficacies closely resembling that of hCAR activation.
These results indicate that our strategically integrated approaches are effective in the identification of novel hCAR modulators, which may function as valuable research tools or potential therapeutic molecules.
CAR; Pharmacophore; CYP2B6; Induction; Hepatocytes
Chordoma is a rare primary bone malignancy that arises in the skull base, spine and sacrum and originates from remnants of the notochord. These tumors are typically resistant to conventional chemotherapy, and to date there are no FDA-approved agents to treat chordoma. The lack of in vivo models of chordoma has impeded the development of new therapies for this tumor. Primary tumor from a sacral chordoma was xenografted into NOD/SCID/IL-2R γ-null mice. The xenograft is serially transplantable and was characterized by both gene expression analysis and whole genome SNP genotyping. The NIH Chemical Genomics Center performed high-throughput screening of 2,816 compounds using two established chordoma cell lines, U-CH1 and U-CH2B. The screen yielded several compounds that showed activity and two, sunitinib and bortezomib, were tested in the xenograft. Both agents slowed the growth of the xenograft tumor. Sensitivity to an inhibitor of IκB, as well as inhibition of an NF-κB gene expression signature demonstrated the importance of NF-κB signaling for chordoma growth. This serially transplantable chordoma xenograft is thus a practical model to study chordomas and perform in vivo preclinical drug testing.
The human cytochrome P450 (CYP) enzyme family is involved in the biotransformation of many xenobiotics. As part of the U.S. Tox21 Phase I effort, we profiled the CYP activity of approximately three thousand compounds, primarily those of environmental concern, against human CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4 isoforms in a quantitative high throughput screening (qHTS) format. In order to evaluate the extent to which computational models built from a drug-like library screened in these five CYP assays under the same conditions can accurately predict the outcome of an environmental compound library, five support vector machines (SVM) models built from over 17,000 drug-like compounds were challenged to predict the CYP activities of the Tox21 compound collection. Although a large fraction of the test compounds fall outside of the applicability domain (AD) of the models, as measured by k-nearest neighbor (k-NN) similarities, the predictions were largely accurate for CYP1A2, CYP2C9, and CYP3A4 ioszymes with area under the receiver operator characteristic curves (AUC-ROC) ranging between 0.82 and 0.84. The lower predictive power of the CYP2C19 model (AUC-ROC = 0.76) is caused by experimental errors and that of the CYP2D6 model (AUC-ROC = 0.76) can be rescued by rebalancing the training data. Our results demonstrate that decomposing molecules into atom types enhanced the coverage of the AD and that computational models built from drug-like molecules can be used to predict the ability of non-drug like compounds to interact with these CYPs.
Human CYPs; QSAR models; Predictive Capacity; SVM; Predictive Toxicology
Drug-induced phospholipidosis (PLD), characterized by an intracellular accumulation of phospholipids and formation of concentric lamellar bodies, has raised concerns in the drug discovery community, due to its potential adverse effects. To evaluate the PLD induction potential, 4,161 non-redundant drug-like molecules from the National Institutes of Health Chemical Genomics Center (NCGC) Pharmaceutical Collection (NPC), the Library of Pharmacologically Active Compounds (LOPAC) and the Tocris Biosciences collection were screened in a quantitative high-throughput screening (qHTS) format. The potential of drug-lipid complex formation can be linked directly to the structures of drug molecules, and many PLD inducing drugs were found to share common structural features. Support vector machine (SVM) models were constructed by using customized atom types or Molecular Operating Environment (MOE) 2D descriptors as structural descriptors. Either the compounds from LOPAC or randomly selected from the entire dataset were used as the training set. The impact of training data with biased structural features and the impact of molecule descriptors emphasizing whole-molecule properties or detailed functional groups at the atom level on model performance were analyzed and discussed. Rebalancing strategies were applied to improve the predictive power of the SVM models. Using the under-sampling method, the consensus model using one third of the compounds randomly selected from the data set as the training set achieved high accuracy of 0.90 in predicting the remaining two thirds of the compounds constituting the test set, as measured by the area under the receiver operator characteristic curve (AUC-ROC).
phospholipidosis; computation toxicology; QSAR; SVM; qHTS
Quinazolin-4-one 1 was identified as an inhibitor of the HIF-1α transcriptional factor from a high-throughput screen. HIF-1α up-regulation is common in many cancer cells. In this paper, we describe an efficient one-pot sequential reaction for the synthesis of quinazolin-4-one 1 analogues. The structure-activity relationship (SAR) study led to the 5-fold more potent analogue, 16.
hypoxia-inducible factor-1α; quinazolin-4-ones; parallel synthesis
Chordoma is a rare, slow growing malignant tumor arising from remnants of the fetal notochord. Surgery is the first choice for chordoma treatment, followed by radiotherapy, although postoperative complications remain significant. Recurrence of the disease occurs frequently due to the anatomy of the tumor location and violation of the tumor margins at the initial surgery. Currently, there are no effective drugs available for patients with chordoma. Due to the rarity of the disease, there is limited opportunity to test agents in clinical trials and no concerted effort to develop agents for chordoma in the pharmaceutical industry. To rapidly and efficiently identify small molecules that inhibit chordoma cell growth, we screened the NCGC Pharmaceutical Collection (NPC) containing approximately 2800 clinically approved and investigational drugs at 15 different concentrations in chordoma cell lines, U-CH1 and U-CH2. We identified a group of drugs including bortezomib, 17-AAG, digitoxin, staurosporine, digoxin, rubitecan, and trimetrexate that inhibited chordoma cell growth, with potencies from 10 to 370 nM in U-CH1 cells, but less potently in U-CH2 cells. Most of these drugs also induced caspase 3/7 activity with a similar rank order as the cytotoxic effect on U-CH1 cells. Cantharidin, digoxin, digitoxin, staurosporine, and bortezomib showed similar inhibitory effect on cell lines and 3 primary chordoma cell cultures. The combination treatment of bortezomib with topoisomerase I and II inhibitors increased the therapeutic potency in U-CH2 and patient-derived primary cultures. Our results provide information useful for repurposing currently approved drugs for chordoma and potential approach of combination therapy.
chordoma; NCGC Pharmaceutical Collection; cell viability; caspase 3/7; U-CH1; U-CH2; qHTS
The limitations of traditional toxicity testing characterized by high-cost animal models with low-throughput readouts, inconsistent responses, ethical issues, and extrapolability to humans call for alternative strategies for chemical risk assessment. A new strategy using in vitro human cell-based assays has been designed to identify key toxicity pathways and molecular mechanisms leading to the prediction of an in vivo response. The emergence of quantitative high-throughput screening (qHTS) technology has proved to be an efficient way to decompose complex toxicological end points to specific pathways of targeted organs. In addition, qHTS has made a significant impact on computational toxicology in two aspects. First, the ease of mechanism of action identification brought about by in vitro assays has enhanced the simplicity and effectiveness of machine learning, and second, the high-throughput nature and high reproducibility of qHTS have greatly improved the data quality and increased the quantity of training datasets available for predictive model construction. In this review, the benefits of qHTS routinely used in the US Tox21 program will be highlighted. Quantitative structure–activity relationships models built on traditional in vivo data and new qHTS data will be compared and analyzed. In conjunction with the transition from the pilot phase to the production phase of the Tox21 program, more qHTS data will be made available that will enrich the data pool for predictive toxicology. It is perceivable that new in silico toxicity models based on high-quality qHTS data will achieve unprecedented reliability and robustness, thus becoming a valuable tool for risk assessment and drug discovery.
computational toxicology; qHTS; risk assessment; Tox21
5-hydroxymethylcytosine (5-hmC), a derivative of 5-methylcytosine (5-mC), is abundant in the brain for unknown reasons. Our goal was to characterize the genomic distribution of 5-hmC and 5-mC in human and mouse tissues. We assayed 5-hmC using glucosylation coupled with restriction enzyme digestion, and interrogation on microarrays. We detected 5-hmC enrichment in genes with synapse-related functions in both human and mouse brain. We also identified substantial tissue-specific differential distributions of these DNA modifications at the exon-intron boundary, in both human and mouse. This boundary change was mainly due to 5-hmC in the brain, but due to 5-mC in non-neural contexts. This pattern was replicated in multiple independent datasets and with single molecule sequencing. Moreover, in human frontal cortex, constitutive exons contained higher levels of 5-hmC, relative to alternatively-spliced exons. Our study suggests a novel role for 5-hmC in RNA splicing and synaptic function in the brain.
A shift in toxicity testing from in vivo to in vitro may efficiently prioritize compounds, reveal new mechanisms, and enable predictive modeling. Quantitative high-throughput screening (qHTS) is a major source of data for computational toxicology, and our goal in this study was to aid in the development of predictive in vitro models of chemical-induced toxicity, anchored on interindividual genetic variability. Eighty-one human lymphoblast cell lines from 27 Centre d’Etude du Polymorphisme Humain trios were exposed to 240 chemical substances (12 concentrations, 0.26nM–46.0μM) and evaluated for cytotoxicity and apoptosis. qHTS screening in the genetically defined population produced robust and reproducible results, which allowed for cross-compound, cross-assay, and cross-individual comparisons. Some compounds were cytotoxic to all cell types at similar concentrations, whereas others exhibited interindividual differences in cytotoxicity. Specifically, the qHTS in a population-based human in vitro model system has several unique aspects that are of utility for toxicity testing, chemical prioritization, and high-throughput risk assessment. First, standardized and high-quality concentration-response profiling, with reproducibility confirmed by comparison with previous experiments, enables prioritization of chemicals for variability in interindividual range in cytotoxicity. Second, genome-wide association analysis of cytotoxicity phenotypes allows exploration of the potential genetic determinants of interindividual variability in toxicity. Furthermore, highly significant associations identified through the analysis of population-level correlations between basal gene expression variability and chemical-induced toxicity suggest plausible mode of action hypotheses for follow-up analyses. We conclude that as the improved resolution of genetic profiling can now be matched with high-quality in vitro screening data, the evaluation of the toxicity pathways and the effects of genetic diversity are now feasible through the use of human lymphoblast cell lines.
chemical cytotoxicity; apoptosis; HapMap; lymphoblasts; qHTS
Hepatotoxicity is a major concern for both drug development and toxicological evaluation of environmental chemicals. The assessment of compound-induced hepatotoxicity has traditionally relied on in vivo testing; however, it is being replaced by human in vitro models due to an emphasis on the reduction of animal testing and species-specific differences. Since most cell lines and hybridomas lack the full complement of enzymes at physiological levels found in the liver, primary hepatocytes are the gold standard to study liver toxicities in vitro due to the retention of most of their in vivo activities. Here, we optimized a cell viability assay using plateable cryopreserved human hepatocytes in a 1536-well-plate format. The assay was validated by deriving inhibitory concentration at 50% values for 12 known compounds, including tamoxifen, staurosporine, and phenylmercuric acetate, with regard to hepatotoxicity and general cytotoxicity using multiple hepatocyte donors. The assay performed well, and the cytotoxicity of these compounds was confirmed in comparison to HepG2 cells. This is the first study to report the reliability of using plateable cryopreserved human hepatocytes for cytotoxicity studies in a 1536-well-plate format. These results suggest that plateable cryopreserved human hepatocytes can be scaled up for screening a large compound library and may be amenable to other hepatocytic assays such as metabolic or drug safety studies.
Chronic inflammatory diseases are characterised by systemically elevated levels of tumour necrosis factor (TNF)-α, a proinflammatory cytokine with pleiotropic downstream effects. We have previously demonstrated increased genotoxicity in peripheral leukocytes and various tissues in models of intestinal inflammation. In the present study, we asked whether TNF-α is sufficient to induce DNA damage systemically, as observed in intestinal inflammation, and whether tumour necrosis factor receptor (TNFR) signalling would be necessary for the resultant genotoxicity. In the wild-type mice, 500 ng per mouse of TNF-α was sufficient to induce DNA damage to multiple cell types and organs 1-h post-administration. Primary splenic T cells manifested TNF-α-induced DNA damage in the absence of other cell types. Furthermore, TNFR1−/−TNFR2−/− mice demonstrated decreased systemic DNA damage in a model of intestinal inflammation and after TNF-α injection versus wild-type mice, indicating the necessity of TNFR signalling. Nuclear factor (NF)-κB inhibitors were also able to decrease damage induced by TNF-α injection in wild-type mice. When TNF-α administration was combined with interleukin (IL)-1β, another proinflammatory cytokine, DNA damage persisted for up to 24 h. When combined with IL-10, an anti-inflammatory cytokine, decreased genotoxicity was observed in vivo and in vitro. TNF-α/TNFR-mediated signalling is therefore sufficient and plays a large role in mediating DNA damage to various cell types, subject to modulation by other cytokines and their mediators.
Background: Over the past 20 years, an increased focus on detecting environmental chemicals that pose a risk of adverse effects due to endocrine disruption has driven the creation of the U.S. Environmental Protection Agency (EPA) Endocrine Disruptor Screening Program (EDSP). Thousands of chemicals are subject to the EDSP; thus, processing these chemicals using current test batteries could require millions of dollars and decades. A need for increased throughput and efficiency motivated the development of methods using in vitro high throughput screening (HTS) assays to prioritize chemicals for EDSP Tier 1 screening (T1S).
Objective: In this study we used U.S. EPA ToxCast HTS assays for estrogen, androgen, steroidogenic, and thyroid-disrupting mechanisms to classify compounds and compare ToxCast results to in vitro and in vivo data from EDSP T1S assays.
Method: We implemented an iterative model that optimized the ability of endocrine-related HTS assays to predict components of EDSP T1S and related results. Balanced accuracy was used as a measure of model performance.
Results: ToxCast estrogen receptor and androgen receptor assays predicted the results of relevant EDSP T1S assays with balanced accuracies of 0.91 (p < 0.001) and 0.92 (p < 0.001), respectively. Uterotrophic and Hershberger assay results were predicted with balanced accuracies of 0.89 (p < 0.001) and 1 (p < 0.001), respectively. Models for steroidogenic and thyroid-related effects could not be developed with the currently published ToxCast data.
Conclusions: Overall, results suggest that current ToxCast assays can accurately identify chemicals with potential to interact with the estrogenic and androgenic pathways, and could help prioritize chemicals for EDSP T1S assays.
androgen; endocrine; estrogen; high throughput; in vitro; ToxCast
The human cytochrome P450 (CYP450) isozymes are the most important enzymes in the body to metabolize many endogenous and exogenous substances including environmental toxins and therapeutic drugs. Any unnecessary interactions between a small molecule and CYP450 isozymes may raise a potential to disarm the integrity of the protection. Accurately predicting the potential interactions between a small molecule and CYP450 isozymes is highly desirable for assessing the metabolic stability and toxicity of the molecule. The National Institutes of Health Chemical Genomics Center (NCGC) has screened a collection of over seventeen thousand compounds against the five major isozymes of CYP450 (1A2, 2C9, 2C19, 2D6 and 3A4) in a quantitative high throughput screening (qHTS) format. In this study, we developed support vector classification (SVC) models for these five isozymes using a set of customized generic atom types. The CYP450 datasets were randomly split into equal-sized training and test sets. The optimized SVC models exhibited high predictive power against the test sets for all five CYP450 isozymes with accuracies of 0.93, 0.89, 0.89, 0.85 and 0.87 for 1A2, 2C9, 2C19, 2D6 and 3A4, respectively, as measured by the area under the receiver operating characteristic (ROC) curves. The important atom types and features extracted from the five models are consistent with the structural preferences for different CYP450 substrates reported in the literature. We also identified novel features with significant discerning power to separate CYP450 actives from inactives. These models can be useful in prioritizing compounds in a drug discovery pipeline, or recognizing the toxic potential of environmental chemicals.
Background: Oxidative stress has been implicated in the pathogenesis of a variety of diseases ranging from cancer to neurodegeneration, highlighting the need to identify chemicals that can induce this effect. The antioxidant response element (ARE) signaling pathway plays an important role in the amelioration of oxidative stress. Thus, assays that detect the up-regulation of this pathway could be useful for identifying chemicals that induce oxidative stress.
Objectives: We used cell-based reporter methods and informatics tools to efficiently screen a large collection of environmental chemicals and identify compounds that induce oxidative stress.
Methods: We utilized two cell-based ARE assay reporters, β-lactamase and luciferase, to screen a U.S. National Toxicology Program 1,408-compound library (NTP 1408, which contains 1,340 unique compounds) for their ability to induce oxidative stress in HepG2 cells using quantitative high throughput screening (qHTS).
Results: Roughly 3% (34 of 1,340) of the unique compounds demonstrated activity across both cell-based assays. Based on biological activity and structure–activity relationship profiles, we selected 50 compounds for retesting in the two ARE assays and in an additional follow-up assay that employed a mutated ARE linked to β-lactamase. Using this strategy, we identified 30 compounds that demonstrated activity in the ARE-bla and ARE-luc assays and were able to determine structural features conferring compound activity across assays.
Conclusions: Our results support the robustness of using two different cell-based approaches for identifying compounds that induce ARE signaling. Together, these methods are useful for prioritizing chemicals for further in-depth mechanism-based toxicity testing.
ARE; Nrf2; oxidative stress; qHTS; toxicity; Tox21
Pleasure-seeking deficits, including lack of libido, are a core feature of depression. Animal and preliminary clinical studies both suggest that phosphodiesterase 4 (PDE4) is a target for developing novel antidepressants. This study examined the potential involvement of PDE4 in the pathology of depression in both animal models and human postmortem brains. In humans, PDE4B and PDE4D levels were elevated in cingulate cortical tissue from individuals with major depressive disorder (MDD) compared to controls. Using the female urine smelling test (FUST), a recently refined method for monitoring sexual pleasure-seeking activity in mice, we found that icv infusion of novel, selective, and potent PDE4 inhibitors enhanced sexual pleasure-seeking activity in male mice that underwent the learned helplessness or serotonin depletion paradigms. The infusion also increased sexual pleasure-seeking activity in naïve male mice. The results suggest that PDE4 may be a plausible contributor to the sexual pleasure-seeking deficits seen in depressed patients; inhibiting PDE4 may restore these deficits.
PDE4; postmortem human brain; depression; pleasure-seeking activity
The human ether-a-go-go-related gene (hERG) channel, a member of a family of voltage-gated potassium (K+) channels, plays a critical role in the repolarization of the cardiac action potential. The reduction of hERG channel activity as a result of adverse drug effects or genetic mutations may cause QT interval prolongation and potentially lead to acquired long QT syndrome. Thus, screening for hERG channel activity is important in drug development. Cardiotoxicity associated with the inhibition of hERG channels by environmental chemicals is also a public health concern. To assess the inhibitory effects of environmental chemicals on hERG channel function, we screened the National Toxicology Program (NTP) collection of 1408 compounds by measuring thallium influx into cells through hERG channels. Seventeen compounds with hERG channel inhibition were identified with IC50 potencies ranging from 0.26 to 22 μM. Twelve of these compounds were confirmed as hERG channel blockers in an automated whole cell patch clamp experiment. In addition, we investigated the structure-activity relationship of seven compounds belonging to the quaternary ammonium compound (QAC) series on hERG channel inhibition. Among four active QAC compounds, tetra-n-octylammonium bromide was the most potent with an IC50 value of 260 nM in the thallium influx assay and 80 nM in the patch clamp assay. The potency of this class of hERG channel inhibitors appears to depend on the number and length of their aliphatic side-chains surrounding the charged nitrogen. Profiling environmental compound libraries for hERG channel inhibition provides information useful in prioritizing these compounds for cardiotoxicity assessment in vivo.
cardiotoxicity; hERG; long QT syndrome; NTP 1408 library; patch clamp; qHTS; tetra-n-octylammonium bromide; thallium influx
Included among the quantitative high throughput screens (qHTS) conducted in support of the U.S. Tox21 program are those being evaluated for the detection of genotoxic compounds. One such screen is based on the induction of increased cytotoxicity in 7 isogenic chicken DT40 cell lines deficient in DNA repair pathways compared to the parental DNA repair-proficient cell line. To characterize the utility of this approach for detecting genotoxic compounds and identifying the type(s) of DNA damage induced, we evaluated nine of 42 compounds identified as positive for differential cytotoxicity in qHTS (actinomycin D, adriamycin, alachlor, benzotrichloride, diglycidyl resorcinol ether, lovastatin, melphalan, trans-1,4-dichloro-2-butene, tris(2,3-epoxypropyl)isocyanurate) and one non-cytotoxic genotoxic compound (2-aminothiamine) for (1) clastogenicity in mutant and wild-type cells; (2) the comparative induction of γH2AX positive foci by melphalan; (3) the extent to which a 72-hr exposure duration increased assay sensitivity or specificity; (4) the use of 10 additional DT40 DNA repair-deficient cell lines to better analyze the type(s) of DNA damage induced; and (5) the involvement of reactive oxygen species in the induction of DNA damage. All compounds but lovastatin and 2-aminothiamine were more clastogenic in at least one DNA repair-deficient cell line than the wild-type cells. The differential responses across the various DNA repair-deficient cell lines provided information on the type(s) of DNA damage induced. The results demonstrate the utility of this DT40 screen for detecting genotoxic compounds, for characterizing the nature of the DNA damage, and potentially for analyzing mechanisms of mutagenesis.
DT40 DNA repair-deficient cell lines; quantitative high throughput screens; cytotoxicity; genotoxicity; chromosomal aberrations; γH2AX positive foci
The U.S. Tox21 collaborative program represents a paradigm shift in toxicity testing of chemical compounds from traditional in vivo tests to less expensive and higher throughput in vitro methods to prioritize compounds for further study, identify mechanisms of action, and ultimately develop predictive models for adverse health effects in humans. The NIH Chemical Genomics Center (NCGC) is an integral component of the Tox21 collaboration due to its quantitative high throughput screening (qHTS) paradigm, in which titration-based screening is used to profile hundreds of thousands of compounds per week. Here, we describe the Tox21 collaboration, qHTS-based compound testing, and the various Tox21 screening assays that have been validated and tested at the NCGC to date.
Tox21; National Research Council; National Toxicology Program; toxicity testing; in vitro assays; NIH Roadmap; NIH Chemical Genomics Center; quantitative high-throughput screening
Opiates are potent analgesics but also drugs of abuse mainly because they produce euphoria. Chronic use of opiates results in the development of tolerance and dependence. Dr Marshall Nirenberg’s group at the National Institutes of Health (NIH) was the first to use a cellular model system of Neuroblastoma×Glioma hybrid cells (NG108-15) to study morphine addiction. They showed that opiates affect adenylyl cyclase (AC) by two opposing mechanisms mediated by the opiate receptor. Although the cellular mechanisms that cause addiction are not yet completely understood, the most observed correlative biochemical adaptation is the upregulation of adenylyl cyclase. This model also provides the opportunity to look for compounds which could dissociate the acute effect of opiates from the delayed response, upregulation of AC, and thus lead to the discovery of non-addictive drugs. To identify small molecule compounds that can inhibit morphine-induced cAMP overshoot, we have validated and optimized a cell-based assay in a high throughput format that measures cellular cAMP production after morphine withdrawal. The assay performed well in the 1536-well plate format. The LOPAC library of 1280 compounds was screened in this assay on a quantitative high throughput screening (qHTS) platform. A group of compounds that can inhibit morphine induced cAMP overshoot were identified. The most potent compounds are eight naloxone related compounds, including levallorphan tartrate, naloxonazine dihydrochloride, naloxone hydrochloride, naltrexone hydrochloride, and naltriben methanesulfonate. The qHTS approach we used in this study will be useful in identifying novel inhibitors of morphine induced addiction from a larger scale screening.
adenylyl cyclase (AC); Adenosine- 3’,5’-monophosphate (cAMP); quantitative high- throughput screening (qHTS); µ opioid receptor (morphine receptor); Human embryonic kidney293- µ opioid receptor cell line (HEK-MOR); Homogeneous Time-Resolved Fluorescence (HTRF)
Background: The large and increasing number of chemicals released into the environment demands more efficient and cost-effective approaches for assessing environmental chemical toxicity. The U.S. Tox21 program has responded to this challenge by proposing alternative strategies for toxicity testing, among which the quantitative high-throughput screening (qHTS) paradigm has been adopted as the primary tool for generating data from screening large chemical libraries using a wide spectrum of assays.
Objectives: The goal of this study was to develop methods to evaluate the data generated from these assays to guide future assay selection and prioritization for the Tox21 program.
Methods: We examined the data from the Tox21 pilot-phase collection of approximately 3,000 environmental chemicals profiled in qHTS format against a panel of 10 human nuclear receptors (AR, ERα, FXR, GR, LXRβ, PPARγ, PPARδ, RXRα, TRβ, and VDR) for reproducibility, concordance of biological activity profiles with sequence homology of the receptor ligand binding domains, and structure–activity relationships.
Results: We determined the assays to be appropriate in terms of biological relevance. We found better concordance for replicate compounds for the agonist-mode than for the antagonist-mode assays, likely due to interference of cytotoxicity in the latter assays. This exercise also enabled us to formulate data-driven strategies for discriminating true signals from artifacts, and to prioritize assays based on data quality.
Conclusions: The results demonstrate the feasibility of qHTS to identify the potential for environmentally relevant chemicals to interact with key toxicity pathways related to human disease induction.
assay performance; chemical genomics; cytotoxicity; nuclear receptors; qHTS; Tox21
Tumor Necrosis Factor-α (TNF-α), a secreted cytokine, plays an important role in inflammatory diseases and immune disorders, and is a potential target for drug development. The traditional assays for detecting TNF-α, enzyme linked immunosorbent assay (ELISA) and radioimmunoassay, are not suitable for the large size compound screens. Both assays suffer from a complicated protocol, multiple plate wash steps and/or excessive radioactive waste. A simple and quick measurement of TNF-α production in a cell based assay is needed for high throughput screening to identify the lead compounds from the compound library. We have developed and optimized two homogeneous TNF-α assays using the HTRF (homogeneous time resolved fluorescence) and AlphaLISA assay formats. We have validated the HTRF based TNF-α assay in a 1536-well plate format by screening a library of 1280 pharmacologically active compounds. The active compounds identified from the screen were confirmed in the AlphaLISA TNF-α assay using a bead-based technology. These compounds were also confirmed in a traditional ELISA assay. From this study, several beta adrenergic agonists have been identified as TNF-α inhibitors. We also identified several novel inhibitors of TNF-α, such as BTO-1, CCG-2046, ellipticine, and PD 169316. The results demonstrated that both homogeneous TNF-α assays are robust and suitable for high throughput screening.
AlphaLISA technology; HTRF technology; inhibition of TNF-α production; qHTS; TNF-α; 1536-well plate.
Nuclear factor-kappa B (NF-κB) is a transcription factor that plays a critical role across many cellular processes including embryonic and neuronal development, cell proliferation, apoptosis, immune responses to infection, and inflammation. Dysregulation of NF-κB signaling is associated with inflammatory diseases and certain cancers. Constitutive activation of NF-κB signaling has been found in some types of tumors including breast, colon, prostate, skin and lymphoid, hence therapeutic blockade of NF-κB signaling in cancer cells provides an attractive strategy for the development of anticancer drugs. To identify small molecule inhibitors of NF-κB signaling, we screened approximately 2,800 clinically approved drugs and bioactive compounds from the NIH Chemical Genomics Center Pharmaceutical Collection (NPC) in a NF-κB mediated β-lactamase reporter gene assay. Each compound was tested at fifteen different concentrations in a quantitative high throughput screening format. We identified nineteen drugs that inhibited NF-κB signaling, with potencies as low as 20 nM. Many of these drugs, including emetine, fluorosalan, sunitinib malate, bithionol, narasin, tribromsalan, and lestaurtinib, inhibited NF-κB signaling via inhibition of IκBα phosphorylation. Others, such as ectinascidin 743, chromomycin A3 and bortezomib utilized other mechanisms. Furthermore, many of these drugs induced caspase 3/7 activity and had an inhibitory effect on cervical cancer cell growth. Our results indicate that many currently approved pharmaceuticals have previously unappreciated effects on NF-κB signaling, which may contribute to anticancer therapeutic effects. Comprehensive profiling of approved drugs provides insight into their molecular mechanisms, thus providing a basis for drug repurposing.
caspase 3/7; cervical cancer; IκBα phosphorylation; NCGC Pharmaceutical Collection; NF-κB signaling
In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation.
modeling; toxicity prediction; structural features; cell viability; caspase-3,7 activation; in vivo toxicity
The NIH Chemical Genomics Center (NCGC) was the inaugural center of the Molecular Libraries and Screening Center Network (MLSCN). Along with the nine other research centers of the MLSCN, the NCGC was established with a primary goal of bringing industrial technology and experience to empower the scientific community with small molecule compounds for use in their research. We intend this review to serve as 1) an introduction to the NCGC standard operating procedures, 2) an overview of several of the lessons learned during the pilot phase and 3) a review of several of the innovative discoveries reported during the pilot phase of the MLSCN.