Low concentration cell painting images enable the identification of highly potent compounds.

Image-based models that use features extracted from cell microscopy images can estimate the activity of small molecules in various biological assays. Typically, models are trained on images stained by an optimized protocol (e.g.

A flexible, image-based, high-throughput platform encompassing in-depth cell profiling to identify broad-spectrum coronavirus antivirals with limited off-target effects.

The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a major threat to global health. Although the World Health Organization ended the public health emergency status, antiviral drugs are needed to address new variants of SARS-CoV-2 and future pandemics. To identify novel broad-spectrum coronavirus drugs, we developed a high-content imaging platform compatible with high-throughput screening.

Leveraging Cell Painting Images to Expand the Applicability Domain and Actively Improve Deep Learning Quantitative Structure-Activity Relationship Models.

The search for chemical hit material is a lengthy and increasingly expensive drug discovery process. To improve it, ligand-based quantitative structure-activity relationship models have been broadly applied to optimize primary and secondary compound properties. Although these models can be deployed as early as the stage of molecule design, they have a limited applicability domain─if the structures of interest differ substantially from the chemical space on which the model was trained, a reliable prediction will not be possible.

Identification of Z-Tyr-Ala-CHN, a Cathepsin L Inhibitor with Broad-Spectrum Cell-Specific Activity against Coronaviruses, including SARS-CoV-2.

The ongoing COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is partly under control by vaccination. However, highly potent and safe antiviral drugs for SARS-CoV-2 are still needed to avoid development of severe COVID-19. We report the discovery of a small molecule, Z-Tyr-Ala-CHN, which was identified in a cell-based antiviral screen.

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.

Development of a cellular high-content, immunofluorescent HBV core assay to identify novel capsid assembly modulators that induce the formation of aberrant HBV core structures.

Hepatitis B Virus (HBV) core protein has multiple functions in the viral life cycle and is an attractive target for new anti-viral therapies. Capsid assembly modulators (CAMs) target the core protein and induce the formation of either morphologically normal (CAM-N) or aberrant structures (CAM-A), both devoid of genomic material. To date a diverse family of CAM-N chemotypes has been identified, but in contrast, described CAM-As are based on the heteroaryldihydropyrimidine (HAP) scaffold.

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.

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.

Genetically Engineered iPSC-Derived FTDP-17 MAPT Neurons Display Mutation-Specific Neurodegenerative and Neurodevelopmental Phenotypes.

Tauopathies such as frontotemporal dementia (FTD) remain incurable to date, partially due to the lack of translational in vitro disease models. The MAPT gene, encoding the microtubule-associated protein tau, has been shown to play an important role in FTD pathogenesis. Therefore, we used zinc finger nucleases to introduce two MAPT mutations into healthy donor induced pluripotent stem cells (iPSCs).

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.

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.

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.

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.

Centrosomes are autocatalytic droplets of pericentriolar material organized by centrioles.

Centrosomes are highly dynamic, spherical organelles without a membrane. Their physical nature and their assembly are not understood. Using the concept of phase separation, we propose a theoretical description of centrosomes as liquid droplets.

Limiting amounts of centrosome material set centrosome size in C. elegans embryos.

Background: The ways in which cells set the size of intracellular structures is an important but largely unsolved problem [1]. Early embryonic divisions pose special problems in this regard. Many checkpoints common in somatic cells are missing from these divisions, which are characterized by rapid reductions in cell size and short cell cycles [2].

Automated tracking and analysis of centrosomes in early Caenorhabditis elegans embryos.

Motivation: The centrosome is a dynamic structure in animal cells that serves as a microtubule organizing center during mitosis and also regulates cell-cycle progression and sets polarity cues. Automated and reliable tracking of centrosomes is essential for genetic screens that study the process of centrosome assembly and maturation in the nematode Caenorhabditis elegans.

Results: We have developed a fully automatic system for tracking and measuring fluorescently labeled centrosomes in 3D time-lapse images of early C.

Centrosome size sets mitotic spindle length in Caenorhabditis elegans embryos.

Just as the size of an organism is carefully controlled, the size of intracellular structures must also be regulated. The mitotic spindle is a supramolecular machine that generates the forces which separate sister chromatids during mitosis. Although spindles show little size variation between cells of the same type, spindle length can vary at least 10-fold between different species.