Discovering the anti-cancer phytochemical rutin against breast cancer through the methodical platform based on traditional medicinal knowledge

  • Jungwhoi Lee (Department of Biotechnology, College of Applied Life Science, Jeju National University) ;
  • Jungsul Lee (Department of Bio and Brain Engineering, KAIST) ;
  • WooGwang Sim (Department of Bio and Brain Engineering, KAIST) ;
  • Jae-Hoon Kim (Department of Biotechnology, College of Applied Life Science, Jeju National University) ;
  • Chulhee Choi (Department of Bio and Brain Engineering, KAIST) ;
  • Jongwook Jeon (Korean Research Institute of Science Technology and Civilization, Jeonbuk National University)
  • Received : 2023.04.14
  • Accepted : 2023.06.21
  • Published : 2023.11.30

Abstract

A number of therapeutic drugs have been developed from functional chemicals found in plants. Knowledge of plants used for medicinal purposes has historically been transmitted by word of mouth or through literature. The aim of the present study is to provide a systemic platform for the development of lead compounds against breast cancer based on a traditional medical text. To verify our systematic approach, integrating processes consisted of text mining of traditional medical texts, 3-D virtual docking screening, and in vitro and in vivo experimental validations were demonstrated. Our text analysis system identified rutin as a specific phytochemical traditionally used for cancer treatment. 3-D virtual screening predicted that rutin could block EGFR signaling. Thus, we validated significant anti-cancer effects of rutin against breast cancer cells through blockade of EGFR signaling pathway in vitro. We also demonstrated in vivo anti-cancer effects of rutin using the breast cancer recurrence in vivo models. In summary, our innovative approach might be proper for discovering new phytochemical lead compounds designing for blockade of malignant neoplasm including breast cancer.

Keywords

Acknowledgement

This research was supported by the Basic Science Research Program of the Korean National Research Foundation (NRF) and funded by the Ministry of Education (2016R1A6A1A03012862).

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