Remodeling oncogenic transcriptomes by small molecules targeting NONO.

Much of the human proteome is involved in mRNA homeostasis, but most RNA-binding proteins lack chemical probes. Here we identify electrophilic small molecules that rapidly and stereoselectively decrease the expression of transcripts encoding the androgen receptor and its splice variants in prostate cancer cells. We show by chemical proteomics that the compounds engage C145 of the RNA-binding protein NONO. Broader profiling revealed that covalent NONO ligands suppress an array of cancer-relevant genes and impair cancer cell proliferation. Surprisingly, these effects were not observed in cells genetically disrupted for NONO, which were instead resistant to NONO ligands. Reintroduction of wild-type NONO, but not a C145S mutant, restored ligand sensitivity in NONO-disrupted cells. The ligands promoted NONO accumulation in nuclear foci and stabilized NONO-RNA interactions, supporting a trapping mechanism that may prevent compensatory action of paralog proteins PSPC1 and SFPQ. These findings show that NONO can be co-opted by covalent small molecules to suppress protumorigenic transcriptional networks.

Discovery of JNJ-63576253, a Next-Generation Androgen Receptor Antagonist Active Against Wild-Type and Clinically Relevant Ligand Binding Domain Mutations in Metastatic Castration-Resistant Prostate Cancer.

Numerous mechanisms of resistance arise in response to treatment with second-generation androgen receptor (AR) pathway inhibitors in metastatic castration-resistant prostate cancer (mCRPC). Among these, point mutations in the ligand binding domain can transform antagonists into agonists, driving the disease through activation of AR signaling. To address this unmet need, we report the discovery of JNJ-63576253, a next-generation AR pathway inhibitor that potently abrogates AR signaling in models of human prostate adenocarcinoma. JNJ-63576253 is advancing as a clinical candidate with potential effectiveness in the subset of patients who do not respond to or are progressing while on second-generation AR-targeted therapeutics.

Tales of 1,008 small molecules: phenomic profiling through live-cell imaging in a panel of reporter cell lines.

Phenomic profiles are high-dimensional sets of readouts that can comprehensively capture the biological impact of chemical and genetic perturbations in cellular assay systems. Phenomic profiling of compound libraries can be used for compound target identification or mechanism of action (MoA) prediction and other applications in drug discovery. To devise an economical set of phenomic profiling assays, we assembled a library of 1,008 approved drugs and well-characterized tool compounds manually annotated to 218 unique MoAs, and we profiled each compound at four concentrations in live-cell, high-content imaging screens against a panel of 15 reporter cell lines, which expressed a diverse set of fluorescent organelle and pathway markers in three distinct cell lineages. For 41 of 83 testable MoAs, phenomic profiles accurately ranked the reference compounds (AUC-ROC ≥ 0.9). MoAs could be better resolved by screening compounds at multiple concentrations than by including replicates at a single concentration. Screening additional cell lineages and fluorescent markers increased the number of distinguishable MoAs but this effect quickly plateaued. There remains a substantial number of MoAs that were hard to distinguish from others under the current study's conditions. We discuss ways to close this gap, which will inform the design of future phenomic profiling efforts.

Therapeutic efficacy of a respiratory syncytial virus fusion inhibitor.

Respiratory syncytial virus is a major cause of acute lower respiratory tract infection in young children, immunocompromised adults, and the elderly. Intervention with small-molecule antivirals specific for respiratory syncytial virus presents an important therapeutic opportunity, but no such compounds are approved today. Here we report the structure of JNJ-53718678 bound to respiratory syncytial virus fusion (F) protein in its prefusion conformation, and we show that the potent nanomolar activity of JNJ-53718678, as well as the preliminary structure-activity relationship and the pharmaceutical optimization strategy of the series, are consistent with the binding mode of JNJ-53718678 and other respiratory syncytial virus fusion inhibitors. Oral treatment of neonatal lambs with JNJ-53718678, or with an equally active close analog, efficiently inhibits established acute lower respiratory tract infection in the animals, even when treatment is delayed until external signs of respiratory syncytial virus illness have become visible. Together, these data suggest that JNJ-53718678 is a promising candidate for further development as a potential therapeutic in patients at risk to develop respiratory syncytial virus acute lower respiratory tract infection.Respiratory syncytial virus causes lung infections in children, immunocompromised adults, and in the elderly. Here the authors show that a chemical inhibitor to a viral fusion protein is effective in reducing viral titre and ameliorating infection in rodents and neonatal lambs.

Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids.

In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation. However, several issues hamper accurate analysis. In particular, signal attenuation within the tissue of the spheroids prevents the acquisition of a complete image for spheroids over 100 micrometers in diameter. And quantitative analysis of large 3D image data sets is challenging, creating a need for methods which can be applied to large-scale experiments and account for impeding factors. We present a robust, computationally inexpensive 2.5D method for the segmentation of spheroid cultures and for counting proliferating cells within them. The spheroids are assumed to be approximately ellipsoid in shape. They are identified from information present in the Maximum Intensity Projection (MIP) and the corresponding height view, also known as Z-buffer. It alerts the user when potential bias-introducing factors cannot be compensated for and includes a compensation for signal attenuation.

Molecular mechanism of respiratory syncytial virus fusion inhibitors.

Respiratory syncytial virus (RSV) is a leading cause of pneumonia and bronchiolitis in young children and the elderly. Therapeutic small molecules have been developed that bind the RSV F glycoprotein and inhibit membrane fusion, yet their binding sites and molecular mechanisms of action remain largely unknown. Here we show that these inhibitors bind to a three-fold-symmetric pocket within the central cavity of the metastable prefusion conformation of RSV F. Inhibitor binding stabilizes this conformation by tethering two regions that must undergo a structural rearrangement to facilitate membrane fusion. Inhibitor-escape mutations occur in residues that directly contact the inhibitors or are involved in the conformational rearrangements required to accommodate inhibitor binding. Resistant viruses do not propagate as well as wild-type RSV in vitro, indicating a fitness cost for inhibitor escape. Collectively, these findings provide new insight into class I viral fusion proteins and should facilitate development of optimal RSV fusion inhibitors.

Integrating High-Dimensional Transcriptomics and Image Analysis Tools into Early Safety Screening: Proof of Concept for a New Early Drug Development Strategy.

During drug discovery and development, the early identification of adverse effects is expected to reduce costly late-stage failures of candidate drugs. As risk/safety assessment takes place rather late during the development process and due to the limited ability of animal models to predict the human situation, modern unbiased high-dimensional biology readouts are sought, such as molecular signatures predictive for in vivo response using high-throughput cell-based assays. In this theoretical proof of concept, we provide findings of an in-depth exploration of a single chemical core structure. Via transcriptional profiling, we identified a subset of close analogues that commonly downregulate multiple tubulin genes across cellular contexts, suggesting possible spindle poison effects. Confirmation via a qualified toxicity assay (in vitro micronucleus test) and the identification of a characteristic aggregate-formation phenotype via exploratory high-content imaging validated the initial findings. SAR analysis triggered the synthesis of a new set of compounds and allowed us to extend the series showing the genotoxic effect. We demonstrate the potential to flag toxicity issues by utilizing data from exploratory experiments that are typically generated for target evaluation purposes during early drug discovery. We share our thoughts on how this approach may be incorporated into drug development strategies.