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In silico drug repositioning: from large-scale transcriptome data to therapeutics

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Abstract

Drug repositioning is an attractive alternative to conventional drug development when new beneficial effects of old drugs are clinically validated because pharmacokinetic and safety profiles are generally already available. Since ~ 30% of drugs newly approved by the US food and drug administration (FDA) are developed through drug repositioning, identifying novel usage for existing drugs is an emerging strategy for developing disease treatments. With advances in next-generation sequencing technologies, available transcriptome data related to diseases have expanded rapidly. Harnessing these resources enables a better understanding of disease mechanisms and drug mode of action (MOA), and moves toward personalized pharmacotherapy. In this review, we briefly outline publicly available large-scale transcriptome databases and tools for drug repositioning. We also highlight recent approaches leading to the discovery of novel drug targets, drug response biomarkers, drug indications, and drug MOA.

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Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) via grants funded by the Korea government (MSIT; NRF-2017R1A6A3A11030794, NRF-2017M3C9A5028690, and NRF-2019R1C1C1008710) to HSL, WKK, and OSK.

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  1. Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, 08826, Republic of Korea

    Ok-Seon Kwon & Hyuk-Jin Cha

  2. Ewha Research Center for Systems Biology, Department of Life Sciences, Ewha Womans University, Seoul, 03760, Republic of Korea

    Wankyu Kim & Haeseung Lee

  3. College of Pharmacy, Seoul National University, Seoul, 08826, Republic of Korea

    Ok-Seon Kwon & Hyuk-Jin Cha

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  1. Ok-Seon Kwon
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Kwon, OS., Kim, W., Cha, HJ. et al. In silico drug repositioning: from large-scale transcriptome data to therapeutics. Arch. Pharm. Res. 42, 879–889 (2019). https://doi.org/10.1007/s12272-019-01176-3

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