Morphological profiling data resource enables prediction of chemical compound properties
Christopher Wolff1, Martin Neuenschwander1, Carsten Jörn Beese1
1Leibniz-Forschungsinstitut für Molekulare Pharmakologie im Forschungsverbund Berlin e.V. (FMP), Campus Berlin-Buch, Robert-Roessle-Str. 10, 13125 Berlin, Germany.
Iscience
|May 19, 2025
Summary
This study introduces a Cell Painting morphological profiling resource for drug discovery, enabling rapid prediction of compound bioactivity and facilitating mechanism of action exploration.
Area of Science:
- Cellular imaging and high-content screening
- Drug discovery and chemical biology
- Bioinformatics and data analysis
Background:
- Cell Painting assay is a powerful tool for morphological profiling in drug discovery.
- Predicting compound bioactivity and mechanisms of action (MOAs) is crucial.
- A comprehensive, high-quality morphological profiling resource is needed.
Purpose of the Study:
- To create a comprehensive morphological profiling resource using EU-OPENSCREEN Bioactive compounds.
- To validate the robustness and quality of the generated data.
- To demonstrate the utility of the resource for exploring MOAs and compound properties.
Main Methods:
- Utilized the Cell Painting assay on Hep G2 and U2 OS cell lines.
- Generated data across four imaging sites using high-throughput confocal microscopy.
- Performed extensive assay optimization and data quality control.
- Correlated morphological profiles with compound activity, toxicity, MOAs, and protein targets.
Main Results:
- Generated a robust and high-quality morphological profiling dataset.
- Validated the consistency of data across multiple imaging sites.
- Demonstrated significant correlations between morphological profiles and biological activities.
- Showcased the ability to compare morphological features between different cell lines.
Conclusions:
- The developed resource provides a valuable tool for drug discovery research.
- Morphological profiling can effectively predict compound bioactivity and mechanisms of action.
- The dataset facilitates deeper exploration of compound-target interactions and MOAs.
Keywords:
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