The pregnane X receptor (PXR; NR1I2) is an important nuclear receptor whose main function is to regulate enzymes within drug metabolism. The main drug metabolizing enzyme regulated by PXR, cytochrome P450 (CYP) 3A4, accounts for the metabolism of nearly 50% of all marketed drugs. Recently, PXR has also been identified as playing a role in energy homeostasis, immune response, and cancer. Due to its interaction with these important roles, alongside its drug-drug interaction function, it is imperative to identify compounds which can modulate PXR. In this study, we screened the Tox21 10,000 compound collection to identify hPXR agonists using a stable hPXR-Luc HepG2 cell line. A pharmacological study in the presence of a PXR antagonist was performed to confirm the activity of the chosen potential hPXR agonists in the same cells. Finally, metabolically competent cell lines - HepaRG and HepaRG-PXR-Knockout (KO) - were used to further confirm the potential PXR activators. We identified a group of structural clusters and singleton compounds which included potentially novel hPXR agonists. Of the 21 selected compounds, 11 potential PXR activators significantly induced CYP3A4 mRNA expression in HepaRG cells. All 11 of these compounds lost their induction when treating HepaRG-PXR-KO cells, confirming their PXR activation. Etomidoline presented as a potentially selective agonist of PXR. In conclusion, the current study has identified 11 compounds as potentially novel or not well-characterized PXR activators. These compounds should further be studied for their potential effects on drug metabolism and drug-drug interactions due to the immense implications of being a PXR agonist.

The mechanisms leading to organ level toxicities are poorly understood. In this study, we applied an integrated approach to deduce the molecular targets and biological pathways involved in chemically induced toxicity for eight common human organ level toxicity end points (carcinogenicity, cardiotoxicity, developmental toxicity, hepatotoxicity, nephrotoxicity, neurotoxicity, reproductive toxicity, and skin toxicity). Integrated analysis of in vitro assay data, molecular targets and pathway annotations from the literature, and toxicity-molecular target associations derived from text mining, combined with machine learning techniques, were used to generate molecular targets for each of the organ level toxicity end points. A total of 1516 toxicity-related genes were identified and subsequently analyzed for biological pathway coverage, resulting in 206 significant pathways (p-value <0.05), ranging from 3 (e.g., developmental toxicity) to 101 (e.g., skin toxicity) for each toxicity end point. This study presents a systematic and comprehensive analysis of molecular targets and pathways related to various in vivo toxicity end points. These molecular targets and pathways could aid in understanding the biological mechanisms of toxicity and serve as a guide for the design of suitable in vitro assays for more efficient toxicity testing. In addition, these results are complementary to the existing adverse outcome pathway (AOP) framework and can be used to aid in the development of novel AOPs. Our results provide abundant testable hypotheses for further experimental validation.

Since 2009, the Tox21 project has screened ∼8500 chemicals in more than 70 high-throughput assays, generating upward of 100 million data points, with all data publicly available through partner websites at the United States Environmental Protection Agency (EPA), National Center for Advancing Translational Sciences (NCATS), and National Toxicology Program (NTP). Underpinning this public effort is the largest compound library ever constructed specifically for improving understanding of the chemical basis of toxicity across research and regulatory domains. Each Tox21 federal partner brought specialized resources and capabilities to the partnership, including three approximately equal-sized compound libraries. All Tox21 data generated to date have resulted from a confluence of ideas, technologies, and expertise used to design, screen, and analyze the Tox21 10K library. The different programmatic objectives of the partners led to three distinct, overlapping compound libraries that, when combined, not only covered a diversity of chemical structures, use-categories, and properties but also incorporated many types of compound replicates. The history of development of the Tox21 "10K" chemical library and data workflows implemented to ensure quality chemical annotations and allow for various reproducibility assessments are described. Cheminformatics profiling demonstrates how the three partner libraries complement one another to expand the reach of each individual library, as reflected in coverage of regulatory lists, predicted toxicity end points, and physicochemical properties. ToxPrint chemotypes (CTs) and enrichment approaches further demonstrate how the combined partner libraries amplify structure-activity patterns that would otherwise not be detected. Finally, CT enrichments are used to probe global patterns of activity in combined ToxCast and Tox21 activity data sets relative to test-set size and chemical versus biological end point diversity, illustrating the power of CT approaches to discern patterns in chemical-activity data sets. These results support a central premise of the Tox21 program: A collaborative merging of programmatically distinct compound libraries would yield greater rewards than could be achieved separately.

Many flaviviruses including the Dengue virus (DENV), Zika virus (ZIKV), West Nile virus, Yellow Fever virus, and Japanese encephalitis virus are significant human pathogens, unfortunately without any specific therapy. Here, we demonstrate that methylene blue, an FDA-approved drug, is a broad-spectrum and potent antiviral against Zika virus and Dengue virus both in vitro and in vivo. We found that methylene blue can considerably inhibit the interactions between viral protease NS3 and its NS2B co-factor, inhibit viral protease activity, inhibit viral growth, protect 3D mini-brain organoids from ZIKV infection, and reduce viremia in a mouse model. Mechanistic studies confirmed that methylene blue works in both entry and post entry steps, reduces virus production in replicon cells and inhibited production of processed NS3 protein. Overall, we have shown that methylene blue is a potent antiviral for management of flavivirus infections, particularly for Zika virus. As an FDA-approved drug, methylene blue is well-tolerated for human use. Therefore, methylene blue represents a promising and easily developed therapy for management of infections by ZIKV and other flaviviruses.

Assessing skin irritation potential is critical for the safety evaluation of topical drugs and other consumer products such as cosmetics. The use of advanced cellular models, as an alternative to replace animal testing in the safety evaluation for both consumer products and ingredients, is already mandated by law in the European Union (EU) and other countries. However, there has not yet been a large-scale comparison of the effects of topical-use compounds in different cellular skin models. This study assesses the irritation potential of topical-use compounds in different cellular models of the skin that are compatible with high throughput screening (HTS) platforms. A set of 451 topical-use compounds were first tested for cytotoxic effects using two-dimensional (2D) monolayer models of primary neonatal keratinocytes and immortalized human keratinocytes. Forty-six toxic compounds identified from the initial screen with the monolayer culture systems were further tested for skin irritation potential on reconstructed human epidermis (RhE) and full thickness skin (FTS) three-dimensional (3D) tissue model constructs. Skin irritation potential of the compounds was assessed by measuring tissue viability, trans-epithelial electrical resistance (TEER), and secretion of cytokines interleukin 1 alpha (IL-1α) and interleukin 18 (IL-18). Among known irritants, high concentrations of methyl violet and methylrosaniline decreased viability, lowered TEER, and increased IL-1α secretion in both RhE and FTS models, consistent with irritant properties. However, at low concentrations, these two compounds increased IL-18 secretion without affecting levels of secreted IL-1α, and did not reduce tissue viability and TEER, in either RhE or FTS models. This result suggests that at low concentrations, methyl violet and methylrosaniline have an allergic potential without causing irritation. Using both HTS-compatible 2D cellular and 3D tissue skin models, together with irritation relevant activity endpoints, we obtained data to help assess the irritation effects of topical-use compounds and identify potential dermal hazards.

To clarify how smoking leads to heart attack and stroke, we developed an endothelial cell model (iECs) generated from human induced Pluripotent Stem Cells (iPSC) and evaluated its responses to tobacco smoke. These iECs exhibited a uniform endothelial morphology, and expressed markers PECAM1/CD31, VWF/ von Willebrand Factor, and CDH5/VE-Cadherin. The iECs also exhibited tube formation and acetyl-LDL uptake comparable to primary endothelial cells (EC). RNA sequencing (RNA-Seq) revealed a robust correlation coefficient between iECs and EC (R = 0.76), whereas gene responses to smoke were qualitatively nearly identical between iECs and primary ECs (R = 0.86). Further analysis of transcriptional responses implicated 18 transcription factors in regulating responses to smoke treatment, and identified gene sets regulated by each transcription factor, including pathways for oxidative stress, DNA damage/repair, ER stress, apoptosis, and cell cycle arrest. Assays for 42 cytokines in HUVEC cells and iECs identified 23 cytokines that responded dynamically to cigarette smoke. These cytokines and cellular stress response pathways describe endothelial responses for lymphocyte attachment, activation of coagulation and complement, lymphocyte growth factors, and inflammation and fibrosis; EC-initiated events that collectively lead to atherosclerosis. Thus, these studies validate the iEC model and identify transcriptional response networks by which ECs respond to tobacco smoke. Our results systematically trace how ECs use these response networks to regulate genes and pathways, and finally cytokine signals to other cells, to initiate the diverse processes that lead to atherosclerosis and cardiovascular disease.

Traditional toxicity testing reliant on animal models is costly and low throughput, posing a significant challenge with the increasing numbers of chemicals that humans are exposed to in the environment. The purpose of this investigation was to build optimal prediction models for various human in vivo/organ-level toxicity end points (extracted from ChemIDPlus) using chemical structure and Tox21 in vitro quantitative high-throughput screening (qHTS) bioactivity assay data. Several supervised machine learning algorithms were applied to model 14 human toxicity end points pertaining to vascular, kidney, ureter and bladder, and liver organ systems. Three metrics were used to evaluate model performance: area under the receiver operating characteristic curve (AUC-ROC), balanced accuracy (BA), and Matthews correlation coefficient (MCC). The top four models, with AUC-ROC values >0.8, were derived for endocrine (0.90 ± 0.00), musculoskeletal (0.88 ± 0.02), peripheral nerve and sensation (0.85 ± 0.01), and brain and coverings (0.83 ± 0.02) toxicities, whereas the best model AUC-ROC values were >0.7 for the remaining 10 toxicities. Model performance was found to be dependent on the specific data set, model type, and feature selection method used. In addition, chemical structure and assay data showed different levels of contribution to the prediction of different toxicity end points. Although in vitro assay data, when combined with chemical structure, slightly improved the predictive accuracy for most end points (11 out of 14), a noteworthy finding was the near equal success of the structure-only models, which do not require Tox21 qHTS screening data, and the relatively poor performance of assay-only models. Thus, the top-performing structure-only models from this study could be applied for hazard screening of large sets of chemicals for potential human toxicity, whereas the largest assay contributions to models (i.e., cellular targets) could be used, along with the top-contributing structural features, to provide insight into toxicity mechanisms.

BACKGROUND: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling. OBJECTIVES: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP). METHODS: The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast™ metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast™/Tox21 HTS in vitro assays. RESULTS: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set. DISCUSSION: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of ∼875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment. https://doi.org/10.1289/EHP5580.

The transforming growth factor beta (TGFβ) superfamily of secreted signaling molecules and their cognate receptors regulate cell fate and behaviors relevant to many developmental and disease processes. Disruption of TGFβ signaling during embryonic development can, for example, affect morphogenesis and differentiation through complex pathways that may be SMAD (Small Mothers Against Decapentaplegic) dependent or SMAD independent. In the present study, the SMAD Binding Element (SBE)-beta lactamase (bla) HEK 293T cell line, which responds to the activation of the SMAD2/3/4 complex, was used in a quantitative high-throughput screening (qHTS) assay to identify potential TGFβ disruptors in the Tox21 10K compound library. From the primary screening we identified several kinase inhibitors, organometallic compounds, and dithiocarbamates (DTCs) that inhibited TGFβ1-induced SMAD signaling of reporter gene activation independent of cytotoxicity. Counterscreen of SBE antagonists on human embryonic neural stem cells demonstrated cytotoxicity, providing additional evidence to support evaluation of these compounds for developmental toxicity. We profiled the inhibitory patterns of putative SBE antagonists toward other developmental signaling pathways, including wingless-related integration site (WNT), retinoic acid α receptor (RAR), and sonic hedgehog (SHH). The profiling results from SBE-bla assay identify chemicals that disrupt TGFβ/SMAD signaling as part of an integrated qHTS approach for prioritizing putative developmental toxicants.

The National Center for Advancing Translational Sciences (NCATS) Pharmaceutical Collection (NPC), a comprehensive collection of clinically approved drugs, was made a public resource in 2011. Over the past decade, the NPC has been systematically profiled for activity across an array of pathways and disease models, generating an unparalleled amount of data. These data have not only enabled the identification of new repurposing candidates with several in clinical trials, but also uncovered new biological insights into drug targets and disease mechanisms. This retrospective provides an update on the NPC in terms of both successes and lessons learned. We also report our efforts in bringing the NPC up-to-date with drugs approved in recent years.