The Use of Informer Sets in Screening: Perspectives on an Efficient Strategy to Identify New Probes.

Small-molecule discovery typically involves large-scale screening campaigns, spanning multiple compound collections. However, such activities can be cost- or time-prohibitive, especially when using complex assay systems, limiting the number of compounds tested. Further, low hit rates can make the process inefficient. Sparse coverage of chemical structure or biological activity space can lead to limited success in a primary screen and represents a missed opportunity by virtue of selecting the "wrong" compounds to test. Thus, the choice of screening collections becomes of paramount importance. In this perspective, we discuss the utility of generating "informer sets" for small-molecule discovery, and how this strategy can be leveraged to prioritize probe candidates. While many researchers may assume that informer sets are focused on particular targets (e.g., kinases) or processes (e.g., autophagy), efforts to assemble informer sets based on historical bioactivity or successful human exposure (e.g., repurposing collections) have shown promise as well. Another method for generating informer sets is based on chemical structure, particularly when the compounds have unknown activities and targets. We describe our efforts to screen an informer set representing a collection of 100,000 small molecules synthesized through diversity-oriented synthesis (DOS). This process enables researchers to identify activity early and more extensively screen only a few chemical scaffolds, rather than the entire collection. This elegant and economic outcome is a goal of the informer set approach. Here, we aim not only to shed light on this process, but also to promote the use of informer sets more widely in small-molecule discovery projects.

Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling.

Anti-cancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM, a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the cell lines' molecular features. Our findings include compounds that killed by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, which killed via the multi-drug resistance protein ABCB1. The PRISM drug repurposing resource (https://depmap.org/repurposing) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation.

Genetic and transcriptional evolution alters cancer cell line drug response.

Human cancer cell lines are the workhorse of cancer research. Although cell lines are known to evolve in culture, the extent of the resultant genetic and transcriptional heterogeneity and its functional consequences remain understudied. Here we use genomic analyses of 106 human cell lines grown in two laboratories to show extensive clonal diversity. Further comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Notably, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single-cell-derived clones demonstrated that continuous instability quickly translates into heterogeneity of the cell line. When the 27 MCF7 strains were tested against 321 anti-cancer compounds, we uncovered considerably different drug responses: at least 75% of compounds that strongly inhibited some strains were completely inactive in others. This study documents the extent, origins and consequences of genetic variation within cell lines, and provides a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.

High Throughput Screen Identifies Interferon γ-Dependent Inhibitors of Toxoplasma gondii Growth.

Toxoplasma gondii is an obligate intracellular parasite capable of causing severe disease due to congenital infection and in patients with compromised immune systems. Control of infection is dependent on a robust Th1 type immune response including production of interferon gamma (IFN-γ), which is essential for control. IFN-γ activates a variety of antimicrobial mechanisms in host cells, which are then able to control intracellular parasites such as T. gondii. Despite the effectiveness of these pathways in controlling acute infection, the immune system is unable to eradicate chronic infections that can persist for life. Similarly, while antibiotic treatment can control acute infection, it is unable to eliminate chronic infection. To identify compounds that would act synergistically with IFN-γ, we performed a high-throughput screen of diverse small molecule libraries to identify inhibitors of T. gondii. We identified a number of compounds that inhibited parasite growth in vitro at low µM concentrations and that demonstrated enhanced potency in the presence of a low level of IFN-γ. A subset of these compounds act by enhancing the recruitment of light chain 3 (LC3) to the parasite-containing vacuole, suggesting they work by an autophagy-related process, while others were independent of this pathway. The pattern of IFN-γ dependence was shared among the majority of analogs from 6 priority scaffolds, and analysis of structure activity relationships for one such class revealed specific stereochemistry associated with this feature. Identification of these IFN-γ-dependent leads may lead to development of improved therapeutics due to their synergistic interactions with immune responses.

High-Throughput Screens To Identify Autophagy Inducers That Function by Disrupting Beclin 1/Bcl-2 Binding.

Autophagy, a lysosomal degradation pathway, plays a crucial role in cellular homeostasis, development, immunity, tumor suppression, metabolism, prevention of neurodegeneration, and lifespan extension. Thus, pharmacological stimulation of autophagy may be an effective approach for preventing or treating certain human diseases and/or aging. We sought to establish a method for developing new chemical compounds that specifically induce autophagy. To do this, we developed two assays to identify compounds that target a key regulatory node of autophagy induction-specifically, the binding of Bcl-2 (a negative regulator of autophagy) to Beclin 1 (an allosteric modulator of the Beclin 1/VPS34 lipid kinase complex that functions in autophagy initiation). These assays use either a split-luciferase assay to measure Beclin 1/Bcl-2 binding in cells or an AlphaLISA assay to directly measure direct Beclin 1/Bcl-2 binding in vitro. We screened two different chemical compound libraries, comprising ∼300 K compounds, to identify small molecules that disrupt Beclin 1/Bcl-2 binding and induce autophagy. Three novel compounds were identified that directly inhibit Beclin 1/Bcl-2 interaction with an IC50 in the micromolar range and increase autophagic flux. These compounds do not demonstrate significant cytotoxicity, and they exert selectivity for disruption of Bcl-2 binding to the BH3 domain of Beclin 1 compared with the BH3 domain of the pro-apoptotic Bcl-2 family members, Bax and Bim. Thus, we have identified candidate molecules that serve as lead templates for developing potent and selective Beclin 1/Bcl-2 inhibitors that may be clinically useful as autophagy-inducing agents.

Small-molecule inhibitors directly target CARD9 and mimic its protective variant in inflammatory bowel disease.

Advances in human genetics have dramatically expanded our understanding of complex heritable diseases. Genome-wide association studies have identified an allelic series of CARD9 variants associated with increased risk of or protection from inflammatory bowel disease (IBD). The predisposing variant of CARD9 is associated with increased NF-κB-mediated cytokine production. Conversely, the protective variant lacks a functional C-terminal domain and is unable to recruit the E3 ubiquitin ligase TRIM62. Here, we used biochemical insights into CARD9 variant proteins to create a blueprint for IBD therapeutics and recapitulated the mechanism of the CARD9 protective variant using small molecules. We developed a multiplexed bead-based technology to screen compounds for disruption of the CARD9-TRIM62 interaction. We identified compounds that directly and selectively bind CARD9, disrupt TRIM62 recruitment, inhibit TRIM62-mediated ubiquitinylation of CARD9, and demonstrate cellular activity and selectivity in CARD9-dependent pathways. Taken together, small molecules targeting CARD9 illustrate a path toward improved IBD therapeutics.

A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay.

Background: Large-scale image sets acquired by automated microscopy of perturbed samples enable a detailed comparison of cell states induced by each perturbation, such as a small molecule from a diverse library. Highly multiplexed measurements of cellular morphology can be extracted from each image and subsequently mined for a number of applications. Findings: This microscopy dataset includes 919 265 five-channel fields of view, representing 30 616 tested compounds, available at "The Cell Image Library" (CIL) repository. It also includes data files containing morphological features derived from each cell in each image, both at the single-cell level and population-averaged (i.e., per-well) level; the image analysis workflows that generated the morphological features are also provided. Quality-control metrics are provided as metadata, indicating fields of view that are out-of-focus or containing highly fluorescent material or debris. Lastly, chemical annotations are supplied for the compound treatments applied. Conclusions: Because computational algorithms and methods for handling single-cell morphological measurements are not yet routine, the dataset serves as a useful resource for the wider scientific community applying morphological (image-based) profiling. The dataset can be mined for many purposes, including small-molecule library enrichment and chemical mechanism-of-action studies, such as target identification. Integration with genetically perturbed datasets could enable identification of small-molecule mimetics of particular disease- or gene-related phenotypes that could be useful as probes or potential starting points for development of future therapeutics.

Selective Chemical Inhibition of PGC-1α Gluconeogenic Activity Ameliorates Type 2 Diabetes.

Type 2 diabetes (T2D) is a worldwide epidemic with a medical need for additional targeted therapies. Suppression of hepatic glucose production (HGP) effectively ameliorates diabetes and can be exploited for its treatment. We hypothesized that targeting PGC-1α acetylation in the liver, a chemical modification known to inhibit hepatic gluconeogenesis, could be potentially used for treatment of T2D. Thus, we designed a high-throughput chemical screen platform to quantify PGC-1α acetylation in cells and identified small molecules that increase PGC-1α acetylation, suppress gluconeogenic gene expression, and reduce glucose production in hepatocytes. On the basis of potency and bioavailability, we selected a small molecule, SR-18292, that reduces blood glucose, strongly increases hepatic insulin sensitivity, and improves glucose homeostasis in dietary and genetic mouse models of T2D. These studies have important implications for understanding the regulatory mechanisms of glucose metabolism and treatment of T2D.

Identification of Highly Specific Diversity-Oriented Synthesis-Derived Inhibitors of Clostridium difficile.

In 2013, the Centers for Disease Control highlighted Clostridium difficile as an urgent threat for antibiotic-resistant infections, in part due to the emergence of highly virulent fluoroquinolone-resistant strains. Limited therapeutic options currently exist, many of which result in disease relapse. We sought to identify molecules specifically targeting C. difficile in high-throughput screens of our diversity-oriented synthesis compound collection. We identified two scaffolds with apparently novel mechanisms of action that selectively target C. difficile while having little to no activity against other intestinal anaerobes; preliminary evidence suggests that compounds from one of these scaffolds target the glutamate racemase. In vivo efficacy data suggest that both compound series may provide lead optimization candidates.

Diversity-oriented synthesis yields novel multistage antimalarial inhibitors.

Antimalarial drugs have thus far been chiefly derived from two sources-natural products and synthetic drug-like compounds. Here we investigate whether antimalarial agents with novel mechanisms of action could be discovered using a diverse collection of synthetic compounds that have three-dimensional features reminiscent of natural products and are underrepresented in typical screening collections. We report the identification of such compounds with both previously reported and undescribed mechanisms of action, including a series of bicyclic azetidines that inhibit a new antimalarial target, phenylalanyl-tRNA synthetase. These molecules are curative in mice at a single, low dose and show activity against all parasite life stages in multiple in vivo efficacy models. Our findings identify bicyclic azetidines with the potential to both cure and prevent transmission of the disease as well as protect at-risk populations with a single oral dose, highlighting the strength of diversity-oriented synthesis in revealing promising therapeutic targets.

Correlating chemical sensitivity and basal gene expression reveals mechanism of action.

Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ∼19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.

Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset.

UNLABELLED: Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2). SIGNIFICANCE: We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses.

Advancing Biological Understanding and Therapeutics Discovery with Small-Molecule Probes.

Small-molecule probes can illuminate biological processes and aid in the assessment of emerging therapeutic targets by perturbing biological systems in a manner distinct from other experimental approaches. Despite the tremendous promise of chemical tools for investigating biology and disease, small-molecule probes were unavailable for most targets and pathways as recently as a decade ago. In 2005, the NIH launched the decade-long Molecular Libraries Program with the intent of innovating in and broadening access to small-molecule science. This Perspective describes how novel small-molecule probes identified through the program are enabling the exploration of biological pathways and therapeutic hypotheses not otherwise testable. These experiences illustrate how small-molecule probes can help bridge the chasm between biological research and the development of medicines but also highlight the need to innovate the science of therapeutic discovery.

Target-based identification of whole-cell active inhibitors of biotin biosynthesis in Mycobacterium tuberculosis.

Biotin biosynthesis is essential for survival and persistence of Mycobacterium tuberculosis (Mtb) in vivo. The aminotransferase BioA, which catalyzes the antepenultimate step in the biotin pathway, has been established as a promising target due to its vulnerability to chemical inhibition. We performed high-throughput screening (HTS) employing a fluorescence displacement assay and identified a diverse set of potent inhibitors including many diversity-oriented synthesis (DOS) scaffolds. To efficiently select only hits targeting biotin biosynthesis, we then deployed a whole-cell counterscreen in biotin-free and biotin-containing medium against wild-type Mtb and in parallel with isogenic bioA Mtb strains that possess differential levels of BioA expression. This counterscreen proved crucial to filter out compounds whose whole-cell activity was off target as well as identify hits with weak, but measurable whole-cell activity in BioA-depleted strains. Several of the most promising hits were cocrystallized with BioA to provide a framework for future structure-based drug design efforts.

Evolving BioAssay Ontology (BAO): modularization, integration and applications.

The lack of established standards to describe and annotate biological assays and screening outcomes in the domain of drug and chemical probe discovery is a severe limitation to utilize public and proprietary drug screening data to their maximum potential. We have created the BioAssay Ontology (BAO) project (http://bioassayontology.org) to develop common reference metadata terms and definitions required for describing relevant information of low-and high-throughput drug and probe screening assays and results. The main objectives of BAO are to enable effective integration, aggregation, retrieval, and analyses of drug screening data. Since we first released BAO on the BioPortal in 2010 we have considerably expanded and enhanced BAO and we have applied the ontology in several internal and external collaborative projects, for example the BioAssay Research Database (BARD). We describe the evolution of BAO with a design that enables modeling complex assays including profile and panel assays such as those in the Library of Integrated Network-based Cellular Signatures (LINCS). One of the critical questions in evolving BAO is the following: how can we provide a way to efficiently reuse and share among various research projects specific parts of our ontologies without violating the integrity of the ontology and without creating redundancies. This paper provides a comprehensive answer to this question with a description of a methodology for ontology modularization using a layered architecture. Our modularization approach defines several distinct BAO components and separates internal from external modules and domain-level from structural components. This approach facilitates the generation/extraction of derived ontologies (or perspectives) that can suit particular use cases or software applications. We describe the evolution of BAO related to its formal structures, engineering approaches, and content to enable modeling of complex assays and integration with other ontologies and datasets.

Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling.

High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cell-based and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.

An Overview of the Challenges in Designing, Integrating, and Delivering BARD: A Public Chemical-Biology Resource and Query Portal for Multiple Organizations, Locations, and Disciplines.

Recent industry-academic partnerships involve collaboration among disciplines, locations, and organizations using publicly funded "open-access" and proprietary commercial data sources. These require the effective integration of chemical and biological information from diverse data sources, which presents key informatics, personnel, and organizational challenges. The BioAssay Research Database (BARD) was conceived to address these challenges and serve as a community-wide resource and intuitive web portal for public-sector chemical-biology data. Its initial focus is to enable scientists to more effectively use the National Institutes of Health Roadmap Molecular Libraries Program (MLP) data generated from the 3-year pilot and 6-year production phases of the Molecular Libraries Probe Production Centers Network (MLPCN), which is currently in its final year. BARD evolves the current data standards through structured assay and result annotations that leverage BioAssay Ontology and other industry-standard ontologies, and a core hierarchy of assay definition terms and data standards defined specifically for small-molecule assay data. We initially focused on migrating the highest-value MLP data into BARD and bringing it up to this new standard. We review the technical and organizational challenges overcome by the interdisciplinary BARD team, veterans of public- and private-sector data-integration projects, who are collaborating to describe (functional specifications), design (technical specifications), and implement this next-generation software solution.

Niche-based screening identifies small-molecule inhibitors of leukemia stem cells.

Efforts to develop more effective therapies for acute leukemia may benefit from high-throughput screening systems that reflect the complex physiology of the disease, including leukemia stem cells (LSCs) and supportive interactions with the bone marrow microenvironment. The therapeutic targeting of LSCs is challenging because LSCs are highly similar to normal hematopoietic stem and progenitor cells (HSPCs) and are protected by stromal cells in vivo. We screened 14,718 compounds in a leukemia-stroma co-culture system for inhibition of cobblestone formation, a cellular behavior associated with stem-cell function. Among those compounds that inhibited malignant cells but spared HSPCs was the cholesterol-lowering drug lovastatin. Lovastatin showed anti-LSC activity in vitro and in an in vivo bone marrow transplantation model. Mechanistic studies demonstrated that the effect was on target, via inhibition of HMG-CoA reductase. These results illustrate the power of merging physiologically relevant models with high-throughput screening.

An interactive resource to identify cancer genetic and lineage dependencies targeted by small molecules.

The high rate of clinical response to protein-kinase-targeting drugs matched to cancer patients with specific genomic alterations has prompted efforts to use cancer cell line (CCL) profiling to identify additional biomarkers of small-molecule sensitivities. We have quantitatively measured the sensitivity of 242 genomically characterized CCLs to an Informer Set of 354 small molecules that target many nodes in cell circuitry, uncovering protein dependencies that: (1) associate with specific cancer-genomic alterations and (2) can be targeted by small molecules. We have created the Cancer Therapeutics Response Portal (http://www.broadinstitute.org/ctrp) to enable users to correlate genetic features to sensitivity in individual lineages and control for confounding factors of CCL profiling. We report a candidate dependency, associating activating mutations in the oncogene ß-catenin with sensitivity to the Bcl-2 family antagonist, navitoclax. The resource can be used to develop novel therapeutic hypotheses and to accelerate discovery of drugs matched to patients by their cancer genotype and lineage.