Preprint / Version 1

Systems pharmacology approaches in herbal medicine research: a brief review

Authors

  • Myunggyo Lee Department of Pharmacy, College of Pharmacy, Pusan National University, Busan 46241, Korea
  • Hyejin Shin Korean Medicine (KM) Convergence Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Korea
  • Musun Park Korean Medicine (KM) Data Division, Korea Institute of Oriental Medicine, Daejeon 34054, Korea
  • Aeyung Kim Korean Medicine (KM) Application Center, Korea Institute of Oriental Medicine, Daegu 41062, Korea
  • Seongwon Cha Korean Medicine (KM) Data Division, Korea Institute of Oriental Medicine, Daejeon 34054, Korea
  • Haeseung Lee Department of Pharmacy, College of Pharmacy, Pusan National University, Busan 46241, Korea

Keywords:

Drug-induced transcriptome, Herbal medicine, Network pharmacology, Systems pharmacology, Traditional medicine

Abstract

Herbal medicine, a multi-component treatment, has been extensively practiced for treating various symptoms and diseases. However, its molecular mechanism of action on the human body is unknown, which impedes the development and application of herbal medicine. To address this, recent studies are increasingly adopting systems pharmacology, which interprets pharmacological effects of drugs from consequences of the interaction networks that drugs might have. Most conventional network-based approaches collect associations of herb-compound, compound-target, and target-disease from individual databases, respectively, and construct an integrated network of herb-compound-target-disease to study the complex mechanisms underlying herbal treatment. More recently, rapid advances in high-throughput omics technology have led numerous studies to exploring gene expression profiles induced by herbal treatments to elicit information on direct associations between herbs and genes at the genome-wide scale. In this review, we summarize key databases and computational methods utilized in systems pharmacology for studying herbal medicine. We also highlight recent studies that identify modes of action or novel indications of herbal medicine by harnessing drug-induced transcriptome data. Keywords: Drug-induced transcriptome, Herbal medicine, Network pharmacology, Systems pharmacology, Traditional medicine

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