4.7 Review

Multi-omics approaches for in-depth understanding of therapeutic mechanism for Traditional Chinese Medicine

期刊

FRONTIERS IN PHARMACOLOGY
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fphar.2022.1031051

关键词

traditional Chinese medicine; multi-omics approaches; quality control; pharmacodynamic effects; network pharmacology analysis; TCM databases

资金

  1. National Science Foundation of China [81774008, 81573702, 32071465, 31871334, 31671374]
  2. Ministry of Science and Technology's national key research and development program grant [2018YFC0910502]

向作者/读者索取更多资源

This article reviews the application and importance of multi-omics approaches in traditional Chinese medicine (TCM) research, including TCM quality assessment, therapeutic mechanism deciphering, network analysis, and database evaluation. With the accumulation of omics data and data-mining resources, deeper understandings of the therapeutic mechanism of TCM have been acquired.
Traditional Chinese Medicine (TCM) is extensively utilized in clinical practice due to its therapeutic and preventative treatments for various diseases. With the development of high-throughput sequencing and systems biology, TCM research was transformed from traditional experiment-based approaches to a combination of experiment-based and omics-based approaches. Numerous academics have explored the therapeutic mechanism of TCM formula by omics approaches, shifting TCM research from the one-target, one-drug to multi-targets, multi-components paradigm, which has greatly boosted the digitalization and internationalization of TCM. In this review, we concentrated on multi-omics approaches in principles and applications to gain a better understanding of TCM formulas against various diseases from several aspects. We first summarized frequently used TCM quality assessment methods, and suggested that incorporating both chemical and biological ingredients analytical methods could lead to a more comprehensive assessment of TCM. Secondly, we emphasized the significance of multi-omics approaches in deciphering the therapeutic mechanism of TCM formulas. Thirdly, we focused on TCM network analysis, which plays a vital role in TCM-diseases interaction, and serves for new drug discovery. Finally, as an essential source for storing multi-omics data, we evaluated and compared several TCM databases in terms of completeness and reliability. In summary, multi-omics approaches have infiltrated many aspects of TCM research. With the accumulation of omics data and data-mining resources, deeper understandings of the therapeutic mechanism of TCM have been acquired or will be gained in the future.

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