Zinc-finger antiviral protein (ZAP) is a restriction factor for replication of modified vaccinia virus Ankara (MVA) in human cells.

Modified vaccinia virus Ankara (MVA) is an approved smallpox vaccine and a promising vaccine vector for other pathogens as well as for cancer therapeutics with more than 200 current or completed clinical trials. MVA was derived by passaging the parental Ankara vaccine virus hundreds of times in chick embryo fibroblasts during which it lost the ability to replicate in human and most other mammalian cells. Although this replication deficiency is an important safety feature, the genetic basis of the host restriction is not understood. Here, an unbiased human genome-wide RNAi screen in human A549 cells revealed that the zinc-finger antiviral protein (ZAP), previously shown to inhibit certain RNA viruses, is a host restriction factor for MVA, a DNA virus. Additional studies demonstrated enhanced MVA replication in several human cell lines following knockdown of ZAP. Furthermore, CRISPR-Cas9 knockout of ZAP in human A549 cells increased MVA replication and spread by more than one log but had no effect on a non-attenuated strain of vaccinia virus. The intact viral C16 protein, which had been disrupted in MVA, antagonized ZAP by binding and sequestering the protein in cytoplasmic punctate structures. Studies aimed at exploring the mechanism by which ZAP restricts MVA replication in the absence of C16 showed that knockout of ZAP had no discernible effect on viral DNA or individual mRNA or protein species as determined by droplet digital polymerase chain reaction, deep RNA sequencing and mass spectrometry, respectively. Instead, inactivation of ZAP reduced the number of aberrant, dense, spherical particles that typically form in MVA-infected human cells, suggesting that ZAP has a novel role in interfering with a late step in the assembly of infectious MVA virions in the absence of the C16 protein.

High-throughput screening with nucleosome substrate identifies small-molecule inhibitors of the human histone lysine methyltransferase NSD2.

The histone lysine methyltransferase nuclear receptor-binding SET domain protein 2 (NSD2, also known as WHSC1/MMSET) is an epigenetic modifier and is thought to play a driving role in oncogenesis. Both NSD2 overexpression and point mutations that increase its catalytic activity are associated with several human cancers. Although NSD2 is an attractive therapeutic target, no potent, selective, and bioactive small molecule inhibitors of NSD2 have been reported to date, possibly due to the challenges of developing high-throughput assays for NSD2. Here, to establish a platform for the discovery and development of selective NSD2 inhibitors, we optimized and implemented multiple assays. We performed quantitative high-throughput screening with full-length WT NSD2 and a nucleosome substrate against a diverse collection of bioactive small molecules comprising 16,251 compounds. We further interrogated 174 inhibitory compounds identified in the primary screen with orthogonal and counter assays and with activity assays based on the clinically relevant NSD2 variants E1099K and T1150A. We selected five confirmed inhibitors for follow-up, which included a radiolabeled validation assay, surface plasmon resonance studies, methyltransferase profiling, and histone methylation in cells. We found that all five NSD2 inhibitors bind the catalytic SET domain and one exhibited apparent activity in cells, validating the workflow and providing a template for identifying selective NSD2 inhibitors. In summary, we have established a robust discovery pipeline for identifying potent NSD2 inhibitors from small-molecule libraries.

Data standards in drug discovery: A long way to go.

Each year, millions to trillions of data points are generated to evaluate the response of chemicals and biologicals to human cells in vitro and in vivo using various technologies and endpoints. Despite the vast amount of data available, the development process has not become significantly more efficient in recent years. Given the increasing use of more complex physiological models, which are time-consuming and significantly more expensive, it is crucial to maximize the value of these valuable data through improved standardization.

Etoposide-induced DNA damage is increased in p53 mutants: identification of ATR and other genes that influence effects of p53 mutations on Top2-induced cytotoxicity.

The functional status of the tumor suppressor p53 is a critical component in determining the sensitivity of cancer cells to many chemotherapeutic agents. DNA topoisomerase II (Top2) plays essential roles in DNA metabolism and is the target of FDA approved chemotherapeutic agents. Topoisomerase targeting drugs convert the enzyme into a DNA damaging agent and p53 influences cellular responses to these agents. We assessed the impact of the loss of p53 function on the formation of DNA damage induced by the Top2 poison etoposide. Using human HCT116 cells, we found resistance to etoposide in cell growth assays upon the functional loss of p53. Nonetheless, cells lacking fully functional p53 were etoposide hypersensitive in clonogenic survival assays. This complex role of p53 led us to directly examine the effects of p53 status on topoisomerase-induced DNA damage. A deficiency in functional p53 resulted in elevated levels of the Top2 covalent complexes (Top2cc) in multiple cell lines. Employing genome-wide siRNA screens, we identified a set of genes for which reduced expression resulted in enhanced synthetic lethality upon etoposide treatment of p53 defective cells. We focused on one hit from this screen, ATR, and showed that decreased expression sensitized the p53-defective cells to etoposide in all assays and generated elevated levels of Top2cc in both p53 proficient and deficient cells. Our findings suggest that a combination of etoposide treatment with functional inactivation of DNA repair in p53 defective cells could be used to enhance the therapeutic efficacy of Top2 targeting agents.

AI-based language models powering drug discovery and development.

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

Informing selection of drugs for COVID-19 treatment through adverse events analysis.

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. Therefore, selection of safe drugs for COVID-19 patients is vital for combating this pandemic. Our goal was to evaluate the safety concerns of drugs by analyzing adverse events reported in post-market surveillance. We collected 296 drugs that have been evaluated in clinical trials for COVID-19 and identified 28,597,464 associated adverse events at the system organ classes (SOCs) level in the FDA adverse events report systems (FAERS). We calculated Z-scores of SOCs that statistically quantify the relative frequency of adverse events of drugs in FAERS to quantitatively measure safety concerns for the drugs. Analyzing the Z-scores revealed that these drugs are associated with different significantly frequent adverse events. Our results suggest that this safety concern metric may serve as a tool to inform selection of drugs with favorable safety profiles for COVID-19 patients in clinical practices. Caution is advised when administering drugs with high Z-scores to patients who are vulnerable to associated adverse events.

A genome-wide screen uncovers multiple roles for mitochondrial nucleoside diphosphate kinase D in inflammasome activation.

Noncanonical inflammasome activation by cytosolic lipopolysaccharide (LPS) is a critical component of the host response to Gram-negative bacteria. Cytosolic LPS recognition in macrophages is preceded by a Toll-like receptor (TLR) priming signal required to induce transcription of inflammasome components and facilitate the metabolic reprograming that fuels the inflammatory response. Using a genome-scale arrayed siRNA screen to find inflammasome regulators in mouse macrophages, we identified the mitochondrial enzyme nucleoside diphosphate kinase D (NDPK-D) as a regulator of both noncanonical and canonical inflammasomes. NDPK-D was required for both mitochondrial DNA synthesis and cardiolipin exposure on the mitochondrial surface in response to inflammasome priming signals mediated by TLRs, and macrophages deficient in NDPK-D had multiple defects in LPS-induced inflammasome activation. In addition, NDPK-D was required for the recruitment of TNF receptor-associated factor 6 (TRAF6) to mitochondria, which was critical for reactive oxygen species (ROS) production and the metabolic reprogramming that supported the TLR-induced gene program. NDPK-D knockout mice were protected from LPS-induced shock, consistent with decreased ROS production and attenuated glycolytic commitment during priming. Our findings suggest that, in response to microbial challenge, NDPK-D-dependent TRAF6 mitochondrial recruitment triggers an energetic fitness checkpoint required to engage and maintain the transcriptional program necessary for inflammasome activation.

An Integrated Systems Biology Approach Identifies the Proteasome as A Critical Host Machinery for ZIKV and DENV Replication.

The Zika virus (ZIKV) and dengue virus (DENV) flaviviruses exhibit similar replicative processes but have distinct clinical outcomes. A systematic understanding of virus-host protein-protein interaction networks can reveal cellular pathways critical to viral replication and disease pathogenesis. Here we employed three independent systems biology approaches toward this goal. First, protein array analysis of direct interactions between individual ZIKV/DENV viral proteins and 20,240 human proteins revealed multiple conserved cellular pathways and protein complexes, including proteasome complexes. Second, an RNAi screen of 10,415 druggable genes identified the host proteins required for ZIKV infection and uncovered that proteasome proteins were crucial in this process. Third, high-throughput screening of 6016 bioactive compounds for ZIKV inhibition yielded 134 effective compounds, including six proteasome inhibitors that suppress both ZIKV and DENV replication. Integrative analyses of these orthogonal datasets pinpoint proteasomes as critical host machinery for ZIKV/DENV replication. Our study provides multi-omics datasets for further studies of flavivirus-host interactions, disease pathogenesis, and new drug targets.

A 3D Heterotypic Multicellular Tumor Spheroid Assay Platform to Discriminate Drug Effects on Stroma versus Cancer Cells.

Three-dimensional (3D) cell culture models are thought to mimic the physiological and pharmacological properties of tissues in vivo more accurately than two-dimensional cultures on plastic dishes. For the development of cancer therapies, 3D spheroid models are being created to reflect the complex histology and physiology of primary tumors with the hopes that drug responses will be more similar to and as predictive as those obtained in vivo. The effect of additional cell types in tumors, such as stromal cells, and the resulting heterotypic cell-cell crosstalk can be investigated in these heterotypic 3D cell cultures. Here, a high-throughput screening-compatible drug testing platform based on 3D multicellular spheroid models is described that enables the parallel assessment of toxicity on stromal cells and efficacy on cancer cells by drug candidates. These heterotypic microtissue tumor models incorporate NIH3T3 fibroblasts as stromal cells that are engineered with a reporter gene encoding secreted NanoLUC luciferase. By tracking the NanoLUC signal in the media over time, a time-related measurement of the cytotoxic effects of drugs on stromal cells over the cancer cells was possible, thus enabling the identification of a therapeutic window. An in vitro therapeutic index parameter is proposed to help distinguish and classify those compounds with broad cytotoxic effects versus those that are more selective at targeting cancer cells.

Quantitative High-Throughput Screening Using an Organotypic Model Identifies Compounds that Inhibit Ovarian Cancer Metastasis.

The tumor microenvironment (TME) is a key determinant of metastatic efficiency. We performed a quantitative high-throughput screen (qHTS) of diverse medicinal chemistry tractable scaffolds (44,420 compounds) and pharmacologically active small molecules (386 compounds) using a layered organotypic, robust assay representing the ovarian cancer metastatic TME. This 3D model contains primary human mesothelial cells, fibroblasts, and extracellular matrix, to which fluorescently labeled ovarian cancer cells are added. Initially, 100 compounds inhibiting ovarian cancer adhesion/invasion to the 3D model in a dose-dependent manner were identified. Of those, eight compounds were confirmed active in five high-grade serous ovarian cancer cell lines and were further validated in secondary in vitro and in vivo biological assays. Two tyrosine kinase inhibitors, PP-121 and milciclib, and a previously unreported compound, NCGC00117362, were selected because they had potency at 1 µmol/L in vitro Specifically, NCGC00117362 and PP-121 inhibited ovarian cancer adhesion, invasion, and proliferation, whereas milciclib inhibited ovarian cancer invasion and proliferation. Using in situ kinase profiling and immunoblotting, we found that milciclib targeted Cdk2 and Cdk6, and PP-121 targeted mTOR. In vivo, all three compounds prevented ovarian cancer adhesion/invasion and metastasis, prolonged survival, and reduced omental tumor growth in an intervention study. To evaluate the clinical potential of NCGC00117362, structure-activity relationship studies were performed. Four close analogues of NCGC00117362 efficiently inhibited cancer aggressiveness in vitro and metastasis in vivo Collectively, these data show that a complex 3D culture of the TME is effective in qHTS. The three compounds identified have promise as therapeutics for prevention and treatment of ovarian cancer metastasis.

Translational in vitro research: integrating 3D drug discovery and development processes into the drug development pipeline.

As we witness steady progress towards the development of robust, scalable, and reproducible 3D tissue models for preclinical drug testing, there is a need for systematic physiological and pharmacological validation and benchmarking. Ongoing and future studies should generate evidence as to whether 3D tissue models are more predictive, help reduce the risk of failure rate, and can be used for decision making in the drug discovery and development pipeline. Here, we discuss the importance of harmonizing the validation of these models based on throughput capacity and physiological complexity as a requirement to establish their true translational capacity. We also outline our strategy for a novel 3D-tailored holistic drug discovery concept rather than piecemeal integration of 3D models into the current process.

Discovery of Orally Bioavailable, Quinoline-Based Aldehyde Dehydrogenase 1A1 (ALDH1A1) Inhibitors with Potent Cellular Activity.

Aldehyde dehydrogenases (ALDHs) are responsible for the metabolism of aldehydes (exogenous and endogenous) and possess vital physiological and toxicological functions in areas such as CNS, inflammation, metabolic disorders, and cancers. Overexpression of certain ALDHs (e.g., ALDH1A1) is an important biomarker in cancers and cancer stem cells (CSCs) indicating the potential need for the identification and development of small molecule ALDH inhibitors. Herein, a newly designed series of quinoline-based analogs of ALDH1A1 inhibitors is described. Extensive medicinal chemistry optimization and biological characterization led to the identification of analogs with significantly improved enzymatic and cellular ALDH inhibition. Selected analogs, e.g., 86 (NCT-505) and 91 (NCT-506), demonstrated target engagement in a cellular thermal shift assay (CETSA), inhibited the formation of 3D spheroid cultures of OV-90 cancer cells, and potentiated the cytotoxicity of paclitaxel in SKOV-3-TR, a paclitaxel resistant ovarian cancer cell line. Lead compounds also exhibit high specificity over other ALDH isozymes and unrelated dehydrogenases. The in vitro ADME profiles and pharmacokinetic evaluation of selected analogs are also highlighted.

KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance.

Members of the KDM5 histone H3 lysine 4 demethylase family are associated with therapeutic resistance, including endocrine resistance in breast cancer, but the underlying mechanism is poorly defined. Here we show that genetic deletion of KDM5A/B or inhibition of KDM5 activity increases sensitivity to anti-estrogens by modulating estrogen receptor (ER) signaling and by decreasing cellular transcriptomic heterogeneity. Higher KDM5B expression levels are associated with higher transcriptomic heterogeneity and poor prognosis in ER+ breast tumors. Single-cell RNA sequencing, cellular barcoding, and mathematical modeling demonstrate that endocrine resistance is due to selection for pre-existing genetically distinct cells, while KDM5 inhibitor resistance is acquired. Our findings highlight the importance of cellular phenotypic heterogeneity in therapeutic resistance and identify KDM5A/B as key regulators of this process.

Assay Guidance Manual: Quantitative Biology and Pharmacology in Preclinical Drug Discovery.

The Assay Guidance Manual (AGM) is an eBook of best practices for the design, development, and implementation of robust assays for early drug discovery. Initiated by pharmaceutical company scientists, the manual provides guidance for designing a "testing funnel" of assays to identify genuine hits using high-throughput screening (HTS) and advancing them through preclinical development. Combined with a workshop/tutorial component, the overall goal of the AGM is to provide a valuable resource for training translational scientists.

RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and Three Dimensions.

The widespread use of two-dimensional (2D) monolayer cultures for high-throughput screening (HTS) to identify targets in drug discovery has led to attrition in the number of drug targets being validated. Solid tumors are complex, aberrantly growing microenvironments that harness structural components from stroma, nutrients fed through vasculature, and immunosuppressive factors. Increasing evidence of stromally-derived signaling broadens the complexity of our understanding of the tumor microenvironment while stressing the importance of developing better models that reflect these interactions. Three-dimensional (3D) models may be more sensitive to certain gene-silencing events than 2D models because of their components of hypoxia, nutrient gradients, and increased dependence on cell-cell interactions and therefore are more representative of in vivo interactions. Colorectal cancer (CRC) and breast cancer (BC) models composed of epithelial cells only, deemed single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS), containing fibroblasts were developed for RNAi HTS in 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening. We describe the development of a high-throughput assay platform that can assess physiologically relevant phenotypic differences between screening 2D versus 3D SCTS, 3D SCTS, and MCTS in the context of different cancer subtypes. This assay platform represents a paradigm shift in how we approach drug discovery that can reduce the attrition rate of drugs that enter the clinic.

Exploring Drug Dosing Regimens In Vitro Using Real-Time 3D Spheroid Tumor Growth Assays.

Two-dimensional monolayer cell proliferation assays for cancer drug discovery have made the implementation of large-scale screens feasible but only seem to reflect a simplified view that oncogenes or tumor suppressor genes are the genetic drivers of cancer cell proliferation. However, there is now increased evidence that the cellular and physiological context in which these oncogenic events occur play a key role in how they drive tumor growth in vivo and, therefore, in how tumors respond to drug treatments. In vitro 3D spheroid tumor models are being developed to better mimic the physiology of tumors in vivo, in an attempt to improve the predictability and efficiency of drug discovery for the treatment of cancer. Here we describe the establishment of a real-time 3D spheroid growth, 384-well screening assay. The cells used in this study constitutively expressed green fluorescent protein (GFP), which enabled the real-time monitoring of spheroid formation and the effect of chemotherapeutic agents on spheroid size at different time points of sphere growth and drug treatment. This real-time 3D spheroid assay platform represents a first step toward the replication in vitro of drug dosing regimens being investigated in vivo. We hope that further development of this assay platform will allow the investigation of drug dosing regimens, efficacy, and resistance before preclinical and clinical studies.

A High-Throughput Screening Model of the Tumor Microenvironment for Ovarian Cancer Cell Growth.

The tumor microenvironment plays an important role in the processes of tumor growth, metastasis, and drug resistance. We have used a multilayered 3D primary cell culture model that reproduces the human ovarian cancer metastatic microenvironment to study the effect of the microenvironment on the pharmacological responses of different classes of drugs on cancer cell proliferation. A collection of oncology drugs was screened to identify compounds that inhibited the proliferation of ovarian cancer cells growing as monolayers or forming spheroids, on plastic and on a 3D microenvironment culture model of the omentum metastatic site, and also cells already in preformed spheroids. Target-based analysis of the pharmacological responses revealed that several classes of targets were more efficacious in cancer cells growing in the absence of the metastatic microenvironment, and other target classes were less efficacious in cancer cells in preformed spheres compared to forming spheroid cultures. These findings show that both the cellular context of the tumor microenvironment and cell adhesion mode have an essential role in cancer cell drug resistance. Therefore, it is important to perform screens for new drugs using model systems that more faithfully recapitulate the tissue composition at the site of tumor growth and metastasis.

PAX3-FOXO1 Establishes Myogenic Super Enhancers and Confers BET Bromodomain Vulnerability.

Alveolar rhabdomyosarcoma is a life-threatening myogenic cancer of children and adolescent young adults, driven primarily by the chimeric transcription factor PAX3-FOXO1. The mechanisms by which PAX3-FOXO1 dysregulates chromatin are unknown. We find PAX3-FOXO1 reprograms the cis-regulatory landscape by inducing de novo super enhancers. PAX3-FOXO1 uses super enhancers to set up autoregulatory loops in collaboration with the master transcription factors MYOG, MYOD, and MYCN. This myogenic super enhancer circuitry is consistent across cell lines and primary tumors. Cells harboring the fusion gene are selectively sensitive to small-molecule inhibition of protein targets induced by, or bound to, PAX3-FOXO1-occupied super enhancers. Furthermore, PAX3-FOXO1 recruits and requires the BET bromodomain protein BRD4 to function at super enhancers, resulting in a complete dependence on BRD4 and a significant susceptibility to BRD inhibition. These results yield insights into the epigenetic functions of PAX3-FOXO1 and reveal a specific vulnerability that can be exploited for precision therapy.Significance: PAX3-FOXO1 drives pediatric fusion-positive rhabdomyosarcoma, and its chromatin-level functions are critical to understanding its oncogenic activity. We find that PAX3-FOXO1 establishes a myoblastic super enhancer landscape and creates a profound subtype-unique dependence on BET bromodomains, the inhibition of which ablates PAX3-FOXO1 function, providing a mechanistic rationale for exploring BET inhibitors for patients bearing PAX-fusion rhabdomyosarcoma. Cancer Discov; 7(8); 884-99. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 783.

Microfluidic Mobility Shift Profiling of Lysine Acetyltransferases Enables Screening and Mechanistic Analysis of Cellular Acetylation Inhibitors.

Lysine acetyltransferases (KATs) are critical regulators of signaling in many diseases, including cancer. A major challenge in establishing the targetable functions of KATs in disease is a lack of well-characterized, cell-active KAT inhibitors. To confront this challenge, here we report a microfluidic mobility shift platform for the discovery and characterization of small molecule KAT inhibitors. Novel fluorescent peptide substrates were developed for four well-known KAT enzymes (p300, Crebbp, Morf, and Gcn5). Enzyme-catalyzed acetylation alters the electrophoretic mobility of these peptides in a microfluidic chip, allowing facile and direct monitoring of KAT activity. A pilot screen was used to demonstrate the utility of microfluidic mobility shift profiling to identify known and novel modulators of KAT activity. Real-time kinetic monitoring of KAT activity revealed that garcinol, a natural product KAT inhibitor used in cellular studies, exhibits time-dependent and detergent-sensitive inhibition, consistent with an aggregation-based mechanism. In contrast, the cell-permeable bisubstrate inhibitor Tat-CoA exhibited potent and time-independent KAT inhibition, highlighting its potential utility as a cellular inhibitor of KAT activity. These studies define microfluidic mobility shift profiling as a powerful platform for the discovery and characterization of small molecule inhibitors of KAT activity, and provide mechanistic insights potentially important for the application of KAT inhibitors in cellular contexts.