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.

Advances in the development of high-throughput screening and automated chemistry have rapidly accelerated the production of chemical and biological data, much of them freely accessible through literature aggregator services such as ChEMBL and PubChem. Here, we explore how to use this comprehensive mapping of chemical biology space to support the development of large-scale quantitative structure-activity relationship (QSAR) models. We propose a new deep learning consensus architecture (DLCA) that combines consensus and multitask deep learning approaches together to generate large-scale QSAR models. This method improves knowledge transfer across different target/assays while also integrating contributions from models based on different descriptors. The proposed approach was validated and compared with proteochemometrics, multitask deep learning, and Random Forest methods paired with various descriptors types. DLCA models demonstrated improved prediction accuracy for both regression and classification tasks. The best models together with their modeling sets are provided through publicly available web services at https://predictor.ncats.io .

Chemical genomics aims to comprehensively define, and ultimately predict, the effects of small molecule compounds on biological systems. Chemical activity profiling approaches must consider chemical effects on all pathways operative in mammalian cells. To enable a strategic and maximally efficient chemical profiling of pathway space, we have created the NCATS BioPlanet, a comprehensive integrated pathway resource that incorporates the universe of 1,658 human pathways sourced from publicly available, manually curated sources, which have been subjected to thorough redundancy and consistency cross-evaluation. BioPlanet supports interactive browsing, retrieval, and analysis of pathways, exploration of pathway connections, and pathway search by gene targets, category, and availability of corresponding bioactivity assay, as well as visualization of pathways on a 3-dimensional globe, in which the distance between any two pathways is proportional to their degree of gene component overlap. Using this resource, we propose a strategy to identify a minimal set of 362 biological assays that can interrogate the universe of human pathways. The NCATS BioPlanet is a public resource, which will be continually expanded and updated, for systems biology, toxicology, and chemical genomics, available at http://tripod.nih.gov/bioplanet/.

Natural products and their derivatives continue to be wellsprings of nascent therapeutic potential. However, many laboratories have limited resources for biological evaluation, leaving their previously isolated or synthesized compounds largely or completely untested. To address this issue, the Canvass library of natural products was assembled, in collaboration with academic and industry researchers, for quantitative high-throughput screening (qHTS) across a diverse set of cell-based and biochemical assays. Characterization of the library in terms of physicochemical properties, structural diversity, and similarity to compounds in publicly available libraries indicates that the Canvass library contains many structural elements in common with approved drugs. The assay data generated were analyzed using a variety of quality control metrics, and the resultant assay profiles were explored using statistical methods, such as clustering and compound promiscuity analyses. Individual compounds were then sorted by structural class and activity profiles. Differential behavior based on these classifications, as well as noteworthy activities, are outlined herein. One such highlight is the activity of (-)-2(S)-cathafoline, which was found to stabilize calcium levels in the endoplasmic reticulum. The workflow described here illustrates a pilot effort to broadly survey the biological potential of natural products by utilizing the power of automation and high-throughput screening.

The inhibition of acetylcholinesterase (AChE) has pharmaceutical applications as well as potential neurotoxic effects. The in vivo metabolites of some chemicals including organophosphorus pesticides can become more potent AChE inhibitors compared to their parental compounds. To account for the effects of biotransformation, we have developed and characterized a high-throughput screening method for identifying AChE inhibitors that become active or more potent following xenobiotic metabolism. In this study, an enzyme-based assay was developed in 1536-well plates using recombinant human AChE combined with human or rat liver microsomes. The AChE activity was measured by two methods with different readouts: colorimetric and fluorescent. The assay exhibited exceptional performance characteristics including large assay signal window, low well-to-well variability and high reproducibility. The performance of the assays with microsomes was characterized by testing a group of known AChE inhibitors including parent compounds and their metabolites. Large potency differences between the parent compounds and the metabolites were observed in the assay with microsome addition. Both assay readouts were required for maximal sensitivity. These results demonstrate that this platform is a promising method to profile large numbers of chemicals that require metabolic activation for inhibiting AChE activity.

Toxicogenomics (TGx) has contributed significantly to toxicology and now has great potential to support moves towards animal-free approaches in regulatory decision making. Here, we discuss in vitro TGx systems and their potential impact on risk assessment. We raise awareness of the rapid advancement of genomics technologies, which generates novel genomics features essential for enhanced risk assessment. We specifically emphasize the importance of reproducibility in utilizing TGx in the regulatory setting. We also highlight the role of machine learning (particularly deep learning) in developing TGx-based predictive models. Lastly, we touch on the topics of how TGx approaches could facilitate adverse outcome pathways (AOP) development and enhance read-across strategies to further regulatory application. Finally, we summarize current efforts to develop TGx for risk assessment and set out remaining challenges.

Heterogeneous response to chemotherapy is a major issue for the treatment of cancer. For most gynecologic cancers including ovarian, cervical, and placental, the list of available small molecule therapies is relatively small compared to options for other cancers. While overall cancer mortality rates have decreased in the United States as early diagnoses and cancer therapies have become more effective, ovarian cancer still has low survival rates due to the lack of effective treatment options, drug resistance, and late diagnosis. To understand chemotherapeutic diversity in gynecologic cancers, we have screened 7914 approved drugs and bioactive compounds in 11 gynecologic cancer cell lines to profile their chemotherapeutic sensitivity. We identified two HDAC inhibitors, mocetinostat and entinostat, as pan-gynecologic cancer suppressors with IC50 values within an order of magnitude of their human plasma concentrations. In addition, many active compounds identified, including the non-anticancer drugs and other compounds, diversely inhibited the growth of three gynecologic cancer cell groups and individual cancer cell lines. These newly identified compounds are valuable for further studies of new therapeutics development, synergistic drug combinations, and new target identification for gynecologic cancers. The results also provide a rationale for the personalized chemotherapeutic testing of anticancer drugs in treatment of gynecologic cancer.

Malaria is a disease with diverse symptoms depending on host immune status and pathogenicity of Plasmodium parasites. The continuous parasite growth within a host suggests mechanisms of immune evasion by the parasite and/or immune inhibition in response to infection. To identify pathways commonly inhibited after malaria infection, we infected C57BL/6 mice with four Plasmodium yoelii strains causing different disease phenotypes and 24 progeny of a genetic cross. mRNAs from mouse spleens day 1 and/or day 4 post infection (p.i.) were hybridized to a mouse microarray to identify activated or inhibited pathways, upstream regulators, and host genes playing an important role in malaria infection. Strong interferon responses were observed after infection with the N67 strain, whereas initial inhibition and later activation of hematopoietic pathways were found after infection with 17XNL parasite, showing unique responses to individual parasite strains. Inhibitions of pathways such as Th1 activation, dendritic cell (DC) maturation, and NFAT immune regulation were observed in mice infected with all the parasite strains day 4 p.i., suggesting universally inhibited immune pathways. As a proof of principle, treatment of N67-infected mice with antibodies against T cell receptors OX40 or CD28 to activate the inhibited pathways enhanced host survival. Controlled activation of these pathways may provide important strategies for better disease management and for developing an effective vaccine.

The constitutive androstane receptor (CAR; NR1I3) is a nuclear receptor involved in all phases of drug metabolism and disposition. However, recently it's been implicated in energy metabolism, tumor progression, and cancer therapy as well. It is, therefore, important to identify compounds that induce hCAR activation to predict drug-drug interactions and potential therapeutic usage. In this study, we screen the Tox21 10,000 compound collection to characterize hCAR activators. A novel structural cluster of compounds was identified, which included nitazoxanide and tenonitrozole, while known structural clusters, such as flavones and prazoles, were also detected. Four compounds, neticonazole, diphenamid, phenothrin, and rimcazole, have been identified as novel hCAR activators, one of which, rimcazole, shows potential selectivity towards hCAR over its sister receptor, the pregnane X receptor (PXR). All four compounds translocated hCAR from the cytoplasm into the nucleus demonstrating the first step to CAR activation. Profiling these compounds as hCAR activators would enable an estimation of drug-drug interactions, as well as identify prospective therapeutically beneficial drugs.

BACKGROUND: A central challenge in toxicity testing is the large number of chemicals in commerce that lack toxicological assessment. In response, the Tox21 program is re-focusing toxicity testing from animal studies to less expensive and higher throughput in vitro methods using target/pathway-specific, mechanism-driven assays. OBJECTIVES: Our objective was to use an in-depth mechanistic study approach to prioritize and characterize the chemicals affecting mitochondrial function. METHODS: We used a tiered testing approach to prioritize for more extensive testing 622 compounds identified from a primary, quantitative high-throughput screen of 8,300 unique small molecules, including drugs and industrial chemicals, as potential mitochondrial toxicants by their ability to significantly decrease the mitochondrial membrane potential (MMP). Based on results from secondary MMP assays in HepG2 cells and rat hepatocytes, 34 compounds were selected for testing in tertiary assays that included formation of reactive oxygen species (ROS), upregulation of p53 and nuclear erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE), mitochondrial oxygen consumption, cellular Parkin translocation, and larval development and ATP status in the nematode Caenorhabditis elegans. RESULTS: A group of known mitochondrial complex inhibitors (e.g., rotenone) and uncouplers (e.g., chlorfenapyr), as well as potential novel complex inhibitors and uncouplers, were detected. From this study, we identified four not well-characterized potential mitochondrial toxicants (lasalocid, picoxystrobin, pinacyanol, and triclocarban) that merit additional in vivo characterization. CONCLUSIONS: The tier-based approach for identifying and mechanistically characterizing mitochondrial toxicants can potentially reduce animal use in toxicological testing. https://doi.org/10.1289/EHP2589.