Morphological profiling data resource enables prediction of chemical compound properties.

形态学分析数据资源能够预测化合物的性质

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作者:Wolff Christopher, Neuenschwander Martin, Beese Carsten Jörn, Sitani Divya, Ramos Maria C, Srovnalova Alzbeta, Varela María José, Polishchuk Pavel, Skopelitou Katholiki E, Å kuta Ctibor, Stechmann Bahne, Brea José, Clausen Mads Hartvig, Dzubak Petr, Fernández-Godino Rosario, Genilloud Olga, Hajduch Marian, Loza María Isabel, Lehmann Martin, Peter von Kries Jens, Sun Han, Schmied Christopher
Morphological profiling with the Cell Painting assay has emerged as a promising method in drug discovery research. The assay captures morphological changes across various cellular compartments enabling the rapid prediction of compound bioactivity. We present a comprehensive morphological profiling resource using the carefully curated and well-annotated EU-OPENSCREEN Bioactive compounds. The data were generated across four imaging sites with high-throughput confocal microscopes using the Hep G2 as well as the U2 OS cell lines. We employed an extensive assay optimization process to achieve high data quality across the different sites. An analysis of the extracted profiles validates the robustness of the generated data. We used this resource to compare the morphological features of the different cell lines. By correlating the profiles with overall activity, cellular toxicity, several specific mechanisms of action (MOAs), and protein targets, we demonstrate the dataset's potential for facilitating more extensive exploration of MOAs.

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