In response to the current global health emergency posed by the Zika virus (ZIKV) outbreak and its link to microcephaly and other neurological conditions, we performed a drug repurposing screen of ~6,000 compounds that included approved drugs, clinical trial drug candidates and pharmacologically active compounds, and we identified compounds that either inhibit ZIKV infection or suppress infection-induced caspase-3 activity in different neural cells. A pan-caspase inhibitor, Emricasan, inhibited ZIKV-induced increases in caspase-3 activity and protected human cortical neural progenitors in both monolayer and 3-dimensional organoid cultures. Ten structurally unrelated inhibitors of cyclin-dependent kinases inhibited ZIKV replication. Niclosamide, an FDA approved category B anthelmintic drug, also inhibited ZIKV replication. Finally, combination treatments using one compound from each category (neuroprotective and antiviral) further increased protection of human neural progenitors and astrocytes from ZIKV-induced cell death. Our results demonstrate the efficacy of this screening strategy and identify lead compounds for anti-ZIKV drug development.

High-throughput screening (HTS) assays enable the testing of large numbers of chemical substances for activity in diverse areas of biology. The biological responses measured in HTS assays span isolated biochemical systems containing purified receptors or enzymes to signal transduction pathways and complex networks functioning in cellular environments. This Review addresses factors that need to be considered when implementing assays for HTS and is aimed particularly at investigators new to this field. We discuss assay design strategies, the major detection technologies and examples of HTS assays for common target classes, cellular pathways and simple cellular phenotypes. We conclude with special considerations for configuring sensitive, robust, informative and economically feasible HTS assays.

We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation, and ER-dependent cell proliferation. The network model uses activity patterns across the in vitro assays to predict whether a chemical is an ER agonist or antagonist, or is otherwise influencing the assays through a manner dependent on the physics and chemistry of the technology platform ("assay interference"). The method is applied to a library of 1812 commercial and environmental chemicals, including 45 ER positive and negative reference chemicals. Among the reference chemicals, the network model correctly identified the agonists and antagonists with the exception of very weak compounds whose activity was outside the concentration range tested. The model agonist score also correlated with the expected potency class of the active reference chemicals. Of the 1812 chemicals evaluated, 111 (6.1%) were predicted to be strongly ER active in agonist or antagonist mode. This dataset and model were also used to begin a systematic investigation of assay interference. The most prominent cause of false-positive activity (activity in an assay that is likely not due to interaction of the chemical with ER) is cytotoxicity. The model provides the ability to prioritize a large set of important environmental chemicals with human exposure potential for additional in vivo endocrine testing. Finally, this model is generalizable to any molecular pathway for which there are multiple upstream and downstream assays available.

Loss of function mutations in Kelch Like ECH Associated Protein 1 (KEAP1) or gain-of-function mutations in nuclear factor erythroid 2-related factor 2 (NRF2) are common in non-small cell lung cancer (NSCLC) and is associated with therapeutic resistance. To discover novel NRF2 inhibitors for targeted therapy, we conducted a quantitative high-throughput screen using a diverse set of ~400,000 small molecules (Molecular Libraries Small Molecule Repository Library, MLSMR) at the National Center for Advancing Translational Sciences. We identified ML385 as a probe molecule that binds to NRF2 and inhibits its downstream target gene expression. Specifically, ML385 binds to the Neh1, the Cap ‘N’ Collar Basic Leucine Zipper (CNC-bZIP) domain of NRF2, and interferes with the binding of the V-Maf Avian Musculoaponeurotic Fibrosarcoma Oncogene Homolog G (MAFG)-NRF2 protein complex to regulatory DNA binding sequences. In clonogenic assays, when used in combination with platinum-based drugs such as doxorubicin or taxol, ML385 substantially enhances cytotoxicity in NSCLC cells compared to single agents alone. ML385 shows specificity and selectivity for NSCLC cells with KEAP1 mutation leading to gain of NRF2 function. In preclinical models of NSCLC with gain of NRF2 function, ML385 in combination with carboplatin showed significant anti-tumor activity. We demonstrate the discovery and validation of ML385 as a novel and specific NRF2 inhibitor and conclude that targeting NRF2 may represent a promising strategy for the treatment of advanced NSCLC.