Revealing a drug’s mechanism of action (MOA) is costly and time-consuming. In this study, we used deep learning to extract temporal mitochondrial phenotypic features after exposure to drugs with known MOAs using re-identification algorithms. The trained model could then predict the MOAs of unidentified substances, facilitating phenotypic screening-based drug discovery and repurposing.
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This is a summary of: Yu, M. et al. Deep learning large-scale drug discovery and repurposing. Nat. Comput. Sci. https://doi.org/10.1038/s43588-024-00679-4 (2024).
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AI-recognized mitochondrial phenotype enables identification of drug targets.
Nat Comput Sci (2024). https://doi.org/10.1038/s43588-024-00682-9
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Published: 22 August 2024
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DOI: https://doi.org/10.1038/s43588-024-00682-9