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Exploring the Mechanisms and Target Diseases of Sasang Constitutional Prescription based on Multiscale Interactome

다계층 상호작용 네트워크 기반 사상처방의 작용 기전과 대상 질환 탐색 연구

  • Won-Yung Lee (Dept. of Pathology, College of Korean Medicine, Wonkwang University) ;
  • Ji Hwan Kim (Dept. of Sasang Constitutional Medicine, College of Korean Medicine, Gachon University)
  • 이원융 (원광대학교 한의과대학 병리학교실) ;
  • 김지환 (가천대학교 한의과대학 사상체질의학교실)
  • Received : 2023.11.20
  • Accepted : 2023.12.14
  • Published : 2023.12.29

Abstract

Objectives The aim of this study is to explore the mechanism of action and target diseases of Sasang constitutional prescriptions using a multiscale interactome approach. Methods The compound and target information of Sasang constitutional prescriptions were retrieved from various databases such as the TM-MC, STITCH, and TTD. Key targets for Sasang constitutional prescriptions were identified by selecting the top 100 targets based on the number of simple paths within the constructed network. Diffusion profiles for Sasang constitutional prescriptions and diseases were calculated based on a biased random walk algorithm. Potential diseases and key mechanisms of Sasang constitutional prescriptions were identified by analyzing diffusion profiles. Results We identified 144 Sasang constitutional prescriptions and their targets, finding 80 herbs with effective biological targets. A cluster analysis based on selecting up to 100 key targets for each prescription revealed a more cohesive grouping of prescriptions according to Sasang constitution. We then predicted potential diseases for 62 Sasang constitutional prescriptions using diffusion profiles calculated on a multiscale interactome. Finally, our analysis of diffusion profiles revealed key targets and biological functions of prescriptions in obesity and diabetes. Conclusions This study demonstrates the effectiveness of a multiscale interactome approach in elucidating the complex mechanisms and potential therapeutic applications of prescriptions in Sasang constitutional medicine.

Keywords

Acknowledgement

이 논문은 2022년도 정부(교육부)의 재원으로 한국연구재단 기초연구사업의 지원을 받아 수행된 연구임 (2022R1I1A2066653).

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