Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review

Mengyue Fan; Ching Jin; Daping Li; Yingshan Deng; Lin Yao; Yongjun Chen; Yu-Ling Ma; Taiyi Wang

doi:10.3389/fphar.2023.1289901

Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review

Front Pharmacol. 2023 Nov 14:14:1289901. doi: 10.3389/fphar.2023.1289901. eCollection 2023.

Authors

Mengyue Fan¹, Ching Jin², Daping Li¹, Yingshan Deng³, Lin Yao¹, Yongjun Chen¹, Yu-Ling Ma⁴, Taiyi Wang^{1

4}

Affiliations

¹ Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
² Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL, United States.
³ College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China.
⁴ Oxford Chinese Medicine Research Centre, University of Oxford, Oxford, United Kingdom.

Abstract

The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Currently, computational approaches play a pivotal role in simulating various pharmacological processes of TCM. The application of network analysis in TCM research has provided an effective means to explain the pharmacological mechanisms underlying the actions of herbs or formulas through the lens of biological network analysis. Along with the advances of network analysis, computational science has coalesced around the core chain of TCM research: formula-herb-component-target-phenotype-ZHENG, facilitating the accumulation and organization of the extensive TCM-related data and the establishment of relevant databases. Nonetheless, recent years have witnessed a tendency toward homogeneity in the development and application of these databases. Advancements in computational technologies, including deep learning and foundation model, have propelled the exploration and modeling of intricate systems into a new phase, potentially heralding a new era. This review aims to delves into the progress made in databases related to six key entities: formula, herb, component, target, phenotype, and ZHENG. Systematically discussions on the commonalities and disparities among various database types were presented. In addition, the review raised the issue of research bottleneck in TCM computational pharmacology and envisions the forthcoming directions of computational research within the realm of TCM.

Keywords: TCM databases; complex biological system; formula-ZHENG relationship; network analysis; systems pharmacology.

Publication types

Review

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Natural Science Foundation of China (82374075 to TW), Taishan Scholar Youth Project of Shandong Province (TW). This work was also supported, in part, by National Natural Science Foundation of China (82274128 to LY), Joint Fund of Shandong Provincial Natural Science Foundation (ZR2021LZY020 to LY).