Mer is a member of the TAM (Tyro3, Axl, Mer) kinase family that has been associated with cancer progression, metastasis, and drug resistance. Their essential function in immune homeostasis has prompted an interest in their role as modulators of antitumor immune response in the tumor microenvironment. Here we illustrate the outcomes of an extensive lead-generation campaign for identification of Mer inhibitors, focusing on the results from concurrent, orthogonal high-throughput screening approaches. Data mining, HT (high-throughput), and DECL (DNA-encoded chemical library) screens offered means to evaluate large numbers of compounds. We discuss campaign strategy and screening outcomes, and exemplify series resulting from prioritization of hits that were identified. Concurrent execution of HT and DECL screening successfully yielded a large number of potent, selective, and novel starting points, covering a range of selectivity profiles across the TAM family members and modes of kinase binding, and offered excellent start points for lead development.
Cell-based assays have long been important within hit discovery paradigms; however, improving the disease relevance of the assay system can positively affect the translation of small-molecule drug discovery, especially if adopted in the initial hit identification assay. Consequently, there is an increasing need for disease-relevant assay systems capable of running at large scale, including the use of induced pluripotent stem cells and donor-derived primary cells. Major hurdles to adopting these assays for high-throughput screening are the cost, availability of cells, and complex protocols. Miniaturization of such assays to 1536-well format is an approach that can reduce costs and increase throughput. Adaptation of these complex cell assays to 1536-well format brings major challenges in liquid handling for high-content assays requiring washing steps and coating of plates. In addition, problematic edge effects and reduced assay quality are frequently encountered. In this study, we describe the novel application of a centrifugal plate washer to facilitate miniaturization of a range of 1536-well cell assays and techniques to reduce edge effects, all of which improved throughput and data quality. Cell assays currently limited in throughput because of cost and complex protocols may be enabled by the techniques presented in this study.
A substantial challenge in phenotypic drug discovery is the identification of the molecular targets that govern a phenotypic response of interest. Several experimental strategies are available for this, the so-called target deconvolution process. Most of these approaches exploit the affinity between a small-molecule compound and its putative targets or use large-scale genetic manipulations and profiling. Each of these methods has strengths but also limitations such as bias toward highaffinity interactions or risks from genetic compensation. The use of computational methods for target and mechanism of action identification is a complementary approach that can influence each step of a phenotypic screening campaign. Here, we describe how cheminformatics and bioinformatics are embedded in the process from initial selection of a focused compound library from a large set of historical small-molecule screens through the analysis of screening results. We present a deconvolution method based on enrichment analysis and using known bioactivity data of screened compounds to infer putative targets, pathways, and biological processes that are consistent with the observed phenotypic response. As an example, the approach is applied to a cellular screen aiming at identifying inhibitors of tumor necrosis factor-α production in lipopolysaccharide-stimulated THP-1 cells. In summary, we find that the approach can contribute to solving the often very complex target deconvolution task.
GlmU is a bifunctional enzyme with acetyltransferase and uridyltransferase activities, and is essential for the biosynthesis of the bacterial cell wall. Inhibition results in a loss of cell viability. GlmU is therefore considered a potential target for novel antibacterial agents. A HTS (high-throughput screen) identified a series of aminoquinazolines with submicromolar potency against the uridyltransferase reaction. Biochemical and biophysical characterization showed competition with UTP binding. We determined the crystal structure of a representative aminoquinazoline bound to the Haemophilus influenzae isoenzyme at a resolution of 2.0 Å. The inhibitor occupies part of the UTP site, skirts the outer perimeter of the GlcNAc1-P (N-acetylglucosamine-1-phosphate) pocket and anchors a hydrophobic moiety into a lipophilic pocket. Our SAR (structure-activity relationship) analysis shows that all of these interactions are essential for inhibitory activity in this series. The crystal structure suggests that the compound would block binding of UTP and lock GlmU in an apo-enzyme-like conformation, thus interfering with its enzymatic activity. Our lead generation effort provides ample scope for further optimization of these compounds for antibacterial drug discovery.
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