Wang Yi, Zhang Han, Zhang Bo-Li, Zhao Xiao-Ping
Department of Chinese Medicine Science & Engineering,Zhejiang University Hangzhou 310058,China.
State Key Laboratory of Component Chinese Medicine,Tianjin University of Traditional Chinese Medicine Tianjin 301617,China.
Zhongguo Zhong Yao Za Zhi. 2020 Jan;45(1):1-6. doi: 10.19540/j.cnki.cjcmm.20200203.501.
The discovery of active constituents of traditional Chinese medicine(TCM) faces multiple challenges, such as limited approaches to evaluate poly-pharmacological effects, and the lack of systematic methods to identify active constituents. Aimed at these bottleneck problems in the field, the present study intensively discussed the key scientific problems in the identification of active constituents of TCM, based on scientific methodologies including systematology, information theory, and synergetics. A comprehensive strategy is herein proposed to investigate the correlations between the chemical composition and biological activities of TCM, from macro-, meso-, and micro-scales. Moreover, in this study, we systematically proposed the methodology of the multimodal identification of TCM active constituents, and thoroughly constructed its core technologies. Its technical framework is suggested to be assessed by multimodal information acquisition, centered on multisource information fusion, and focused on interaction evaluation. Furthermore, the core technologies for the multimodal identification of active constituents of TCM were developed in this study, which is according to the characteristics of the exchanges of between TCM and biological organisms, in the aspects of material, energy and information. Finally, two examples of the application of the proposed method were briefly introduced. The proposed methodology provides a novel way to solve the bottlenecks in the study of active constituents of TCM, and lays the foundation for the multimodal study of TCM.
中药活性成分的发现面临诸多挑战，如评估多药理作用的方法有限，以及缺乏识别活性成分的系统方法。针对该领域的这些瓶颈问题，本研究基于系统论、信息论和协同论等科学方法，深入探讨了中药活性成分识别中的关键科学问题。本文提出了一种全面的策略，从宏观、中观和微观尺度研究中药化学成分与生物活性之间的相关性。此外，在本研究中，我们系统地提出了中药活性成分多模态识别的方法，并全面构建了其核心技术。建议通过以多源信息融合为中心、以相互作用评估为重点的多模态信息获取来评估其技术框架。此外，本研究根据中药与生物机体在物质、能量和信息方面交换的特点，开发了中药活性成分多模态识别的核心技术。最后，简要介绍了所提方法的两个应用实例。所提方法为解决中药活性成分研究中的瓶颈提供了一种新途径，为中药的多模态研究奠定了基础。
