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AI-recognized mitochondrial phenotype enables identification of drug targets

Nature Computational Science volume 4, pages 563–564 (2024)Cite this article

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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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Fig. 1: Deep learning predicts drug MOA via temporal mitochondrial phenotype.

References

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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 4, 563–564 (2024). https://doi.org/10.1038/s43588-024-00682-9

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