Ren Zhixiang, Ren Yiming, Li Zeting, Xu Huan
Peng Cheng Laboratory, Shenzhen, 518055, Guangdong Province, China.
School of Public Health, Anhui University of Science and Technology, Hefei, 231131, Anhui Province, China.
Comput Struct Biotechnol J. 2024 Apr 15;23:1619-1630. doi: 10.1016/j.csbj.2024.04.016. eCollection 2024 Dec.
Mining the potential of traditional Chinese medicine (TCM) in treating modern diseases requires a profound understanding of its action mechanism and a comprehensive knowledge system that seamlessly bridges modern medical insights with traditional theories. However, existing databases for modernizing TCM are plagued by varying degrees of information loss, which impede the multidimensional dissection of pharmacological effects. To address this challenge, we introduce traditional Chinese medicine modernization (TCMM), the currently largest modernized TCM database that integrates pioneering intelligent pipelines. By aligning high-quality TCM and modern medicine data, TCMM boasts the most extensive TCM modernization knowledge, including 20 types of modernized TCM concepts such as prescription, ingredient, target and 46 biological relations among them, totaling 3,447,023 records. We demonstrate the efficacy and reliability of TCMM with two features, prescription generation and knowledge discovery, the outcomes show consistency with biological experimental results. A publicly available web interface is at https://www.tcmm.net.cn/.
挖掘中药治疗现代疾病的潜力，需要深刻理解其作用机制，并构建一个能将现代医学见解与传统理论无缝衔接的全面知识体系。然而，现有的中药现代化数据库存在不同程度的信息丢失问题，这阻碍了对药理作用的多维度剖析。为应对这一挑战，我们推出了中药现代化（TCMM）数据库，它是目前最大的整合了先进智能管道的现代化中药数据库。通过整合高质量的中药和现代医学数据，TCMM拥有最广泛的中药现代化知识，包括20种现代化中药概念，如方剂、成分、靶点等，以及它们之间的46种生物学关系，共计3,447,023条记录。我们通过方剂生成和知识发现这两个功能展示了TCMM的有效性和可靠性，结果与生物学实验结果一致。其公开的网页界面为https://www.tcmm.net.cn/ 。
