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.

Automated quality control tool for high-content imaging data by building 2D prediction intervals on reference biosignatures.

Recent advances in automated microscopy and image analysis enables quantitative profiling of cellular phenotypes (Cell Painting). It paves the way for studying the broad effects of chemical perturbations on biological systems at large scale during lead optimization. Comparison of perturbation biosignatures with biosignatures of annotated compounds can inform on both on- and off-target effects.

Discovery and Pharmacological Characterization of JNJ-64619178, a Novel Small-Molecule Inhibitor of PRMT5 with Potent Antitumor Activity.

The protein arginine methyltransferase 5 (PRMT5) methylates a variety of proteins involved in splicing, multiple signal transduction pathways, epigenetic control of gene expression, and mechanisms leading to protein expression required for cellular proliferation. Dysregulation of PRMT5 is associated with clinical features of several cancers, including lymphomas, lung cancer, and breast cancer. Here, we describe the characterization of JNJ-64619178, a novel, selective, and potent PRMT5 inhibitor, currently in clinical trials for patients with advanced solid tumors, non-Hodgkin's lymphoma, and lower-risk myelodysplastic syndrome.

REMBI: Recommended Metadata for Biological Images-enabling reuse of microscopy data in biology.

Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. We propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy. We hope this publication and the proposed Recommended Metadata for Biological Images (REMBI) will stimulate discussions about their implementation and future extension.

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.

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.

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects.

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.

A duplex real-time RT-PCR assay for profiling inhibitors of four dengue serotypes.

We have developed a duplex real-time RT-PCR assay for profiling antiviral inhibitors of four dengue virus (DENV) serotypes. In this assay, the primers and the probe for amplifying DENV were designed in the conserved regions of the genome after aligned more than 300 nucleotide sequences of four dengue serotypes deposited in the GeneBank. To discriminate the antiviral activity from the cytotoxicity of compounds, a housekeeping gene of the Vero cells, β-actin, was used to design the primers and the probe for the second set of PCR as an internal control, which is used to normalize the RNA levels of dengue-specific PCR due to the cellular toxicity of test compounds.

A homogeneous time-resolved fluorescence assay to identify inhibitors of HIV-1 fusion.

The human immunodeficiency virus type 1 (HIV-1) initiates infection through sequential interactions with CD4 and chemokine coreceptors unmasking the gp41 subunit of the viral envelope protein. Consequently, the N-terminal heptad repeats of gp41 form a trimeric coiled-coil groove in which the C-terminal heptad repeats collapse, generating a stable six-helix bundle. This brings the viral and cell membrane in close proximity enabling fusion and the release of viral genome in the cytosol of the host cell.

Translation of a tumor microenvironment mimicking 3D tumor growth co-culture assay platform to high-content screening.

For drug discovery, cell-based assays are becoming increasingly complex to mimic more realistically the nature of biological processes and their diversifications in diseases. Multicellular co-cultures embedded in a three-dimensional (3D) matrix have been explored in oncology to more closely approximate the physiology of the human tumor microenvironment. High-content analysis is the ideal technology to characterize these complex biological systems, although running such complex assays at higher throughput is a major endeavor.

Phaedra, a protocol-driven system for analysis and validation of high-content imaging and flow cytometry.

High-content screening has brought new dimensions to cellular assays by generating rich data sets that characterize cell populations in great detail and detect subtle phenotypes. To derive relevant, reliable conclusions from these complex data, it is crucial to have informatics tools supporting quality control, data reduction, and data mining. These tools must reconcile the complexity of advanced analysis methods with the user-friendliness demanded by the user community.

Binding kinetics of darunavir to human immunodeficiency virus type 1 protease explain the potent antiviral activity and high genetic barrier.

The high incidence of cross-resistance between human immunodeficiency virus type 1 (HIV-1) protease inhibitors (PIs) limits their sequential use. This necessitates the development of PIs with a high genetic barrier and a broad spectrum of activity against PI-resistant HIV, such as tipranavir and darunavir (TMC114). We performed a surface plasmon resonance-based kinetic study to investigate the impact of PI resistance-associated mutations on the protease binding of five PIs used clinically: amprenavir, atazanavir, darunavir, lopinavir, and tipranavir.

A time-resolved fluorescence assay to identify small-molecule inhibitors of HIV-1 fusion.

Fusion of host cell and human immunodeficiency virus type 1 (HIV-1) membranes is mediated by the 2 "heptad-repeat" regions of the viral gp41 protein. The collapse of the C-terminal heptad-repeat regions into the hydrophobic grooves of a coiled-coil formed by the corresponding homotrimeric N-terminal heptad-repeat regions generates a stable 6-helix bundle. This brings viral and cell membranes together for membrane fusion, facilitating viral entry.