Morphological profiling data resource enables prediction of chemical compound properties
| dc.contributor.affiliation | Universidade de Santiago de Compostela. Centro de Investigación en Medicina Molecular e Enfermidades Crónicas (CiMUS) | |
| dc.contributor.affiliation | Universidade de Santiago de Compostela. Departamento de Farmacoloxía, Farmacia e Tecnoloxía Farmacéutica | |
| dc.contributor.author | Wolff, Christopher | |
| dc.contributor.author | Neuenschwander, Martin | |
| dc.contributor.author | Beese, Carsten Jörn | |
| dc.contributor.author | Sitani, Divya | |
| dc.contributor.author | Ramos, Maria C. | |
| dc.contributor.author | Srovnalova, Alzbeta | |
| dc.contributor.author | Varela Liste, María José | |
| dc.contributor.author | Polishchuk, Pavel | |
| dc.contributor.author | Skopelitou, Katholiki E. | |
| dc.contributor.author | Škuta, Ctibor | |
| dc.contributor.author | Stechmann, Bahne | |
| dc.contributor.author | Brea Floriani, José Manuel | |
| dc.contributor.author | Clausen, Mads Hartvig | |
| dc.contributor.author | Dzubak, Petr | |
| dc.contributor.author | Fernández-Godino, Rosario | |
| dc.contributor.author | Genilloud, Olga | |
| dc.contributor.author | Hajduch, Marian | |
| dc.contributor.author | Loza García, María Isabel | |
| dc.contributor.author | Lehmann, Martin | |
| dc.contributor.author | Kries, Jens Peter von | |
| dc.contributor.author | Sun, Han | |
| dc.contributor.author | Schmied, Christopher | |
| dc.date.accessioned | 2026-01-16T13:42:54Z | |
| dc.date.available | 2026-01-16T13:42:54Z | |
| dc.date.issued | 2025-05-16 | |
| dc.description.abstract | 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 | |
| dc.description.peerreviewed | SI | |
| dc.description.sponsorship | 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 | |
| dc.identifier.citation | 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 | |
| dc.identifier.doi | 10.1016/j.isci.2025.112445 | |
| dc.identifier.essn | 2589-0042 | |
| dc.identifier.uri | https://hdl.handle.net/10347/45235 | |
| dc.issue.number | 5 | |
| dc.journal.title | iScience | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.isci.2025.112445 | |
| dc.rights | © 2025 The Author(s). Published by Elsevier Inc. This is an open access article distributed under the terms of the Creative Commons CC-BY license | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.accessRights | open access | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Chemical compound properties | |
| dc.subject | Small molecule libraries | |
| dc.subject | Cell Painting | |
| dc.title | Morphological profiling data resource enables prediction of chemical compound properties | |
| dc.type | journal article | |
| dc.type.hasVersion | VoR | |
| dc.volume.number | 28 | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 67b19be7-64a8-45c8-a6e4-ed48a4410ef8 | |
| relation.isAuthorOfPublication | 7765cb9b-b630-44dc-9477-dd266a62bb3c | |
| relation.isAuthorOfPublication.latestForDiscovery | 67b19be7-64a8-45c8-a6e4-ed48a4410ef8 |
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