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Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still pose a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.
Publicly available compound and bioactivity databases provide an essential basis for data-driven applications in life-science research and drug design. By analyzing several bioactivity repositories, we discovered differences in compound and target coverage advocating the combined use of data from multiple sources. Using data from ChEMBL, PubChem, IUPHAR/BPS, BindingDB, and Probes & Drugs, we assembled a consensus dataset focusing on small molecules with bioactivity on human macromolecular targets. This allowed an improved coverage of compound space and targets, and an automated comparison and curation of structural and bioactivity data to reveal potentially erroneous entries and increase confidence. The consensus dataset comprised of more than 1.1 million compounds with over 10.9 million bioactivity data points with annotations on assay type and bioactivity confidence, providing a useful ensemble for computational applications in drug design and chemogenomics.
The function of the p53 transcription factor family is dependent on several folded domains. In addition to a DNA-binding domain, members of this family contain an oligomerization domain. p63 and p73 also contain a C-terminal Sterile α-motif domain. Inhibition of most transcription factors is difficult as most of them lack deep pockets that can be targeted by small organic molecules. Genetic knock-out procedures are powerful in identifying the overall function of a protein, but they do not easily allow one to investigate roles of individual domains. Here we describe the characterization of Designed Ankyrin Repeat Proteins (DARPins) that were selected as tight binders against all folded domains of p63. We determine binding affinities as well as specificities within the p53 protein family and show that DARPins can be used as intracellular inhibitors for the modulation of transcriptional activity. By selectively inhibiting DNA binding of the ΔNp63α isoform that competes with p53 for the same promoter sites, we show that p53 can be reactivated. We further show that inhibiting the DNA binding activity stabilizes p63, thus providing evidence for a transcriptionally regulated negative feedback loop. Furthermore, the ability of DARPins to bind to the DNA-binding domain and the Sterile α-motif domain within the dimeric-only and DNA-binding incompetent conformation of TAp63α suggests a high structural plasticity within this special conformation. In addition, the developed DARPins can also be used to specifically detect p63 in cell culture and in primary tissue and thus constitute a very versatile research tool for studying the function of p63.