RT Journal Article
T1 Morphological profiling data resource enables prediction of chemical compound properties
A1 Wolff, Christopher
A1 Neuenschwander, Martin
A1 Beese, Carsten Jörn
A1 Sitani, Divya
A1 Ramos, Maria C.
A1 Srovnalova, Alzbeta
A1 Varela Liste, María José
A1 Polishchuk, Pavel
A1 Skopelitou, Katholiki E.
A1 Škuta, Ctibor
A1 Stechmann, Bahne
A1 Brea Floriani, José Manuel
A1 Clausen, Mads Hartvig
A1 Dzubak, Petr
A1 Fernández-Godino, Rosario
A1 Genilloud, Olga
A1 Hajduch, Marian
A1 Loza García, María Isabel
A1 Lehmann, Martin
A1 Kries, Jens Peter von
A1 Sun, Han
A1 Schmied, Christopher
K1 Chemical compound properties
K1 Small molecule libraries
K1 Cell Painting
AB 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
PB Elsevier
YR 2025
FD 2025-05-16
LK https://hdl.handle.net/10347/45235
UL https://hdl.handle.net/10347/45235
LA eng
NO Christopher Wolff, Martin Neuenschwander, Carsten Jörn Beese, Divya Sitani, Maria C. Ramos, Alzbeta Srovnalova, María José Varela, Pavel Polishchuk, Katholiki E. Skopelitou, Ctibor Škuta, Bahne Stechmann, José Brea, Mads Hartvig Clausen, Petr Dzubak, Rosario Fernández-Godino, Olga Genilloud, Marian Hajduch, María Isabel Loza, Martin Lehmann, Jens Peter von Kries, Han Sun, Christopher Schmied, Morphological profiling data resource enables prediction of chemical compound properties, iScience, Volume 28, Issue 5, 2025, 112445, ISSN 2589-0042, https://doi.org/10.1016/j.isci.2025.112445
NO This project was supported by the Leibniz-Forschungsinstitut für Molekulare Pharmakologie via the Integrated Project titled: “Machine Learning Enhanced Cell Morphology Profiling in Molecular Pharmacology” awarded to J.P.V.K., H.S., and C.S. This project was funded by the German Federal Ministry for Education and Research under grant number AZA 16KX1816. The selection of Bioactive compounds was supported by the Ministry of Education, Youth and Sports of the Czech Republic (LM2023052). This work was supported by the EGI DataHub and EGI Check-in services from Cyfronet and GRNET, provided from the EGI-ACE project (Horizon 2020) under Grant number 101017567
DS Minerva
RD 27 abr 2026