[Research methods and technological advancements in herbal material science].
- 1State Key Laboratory of Phytochemistry and Natural Medicines，Dalian Institute of Chemical Physics，Chinese Academy of Sciences，Dalian 116023，China.
- 2Ganjiang Chinese Medicine Innovation Center，Nanchang 330000，China.
- 3Shanghai Institute of Materia Medica，Chinese Academy of Sciences，Shanghai 201203，China.
Abstract
Traditional Chinese medicine （TCM）， as a complex system of substances， has long faced the challenges of an unclear material basis and obscure mechanisms of action， which has hindered its modernization and internationalization. To address these challenges， the "Herbalome" project was launched in 2007. This initiative aims to systematically reveal the material composition， structure， and biological functions of TCM through the integration of multidisciplinary technologies， thereby elucidating the synergistic mechanisms of multi-component and multi-target interactions. This paper reviews key methodological and technological advancements in the field of herbal material science. Specifically， regarding the composition and structural identification of herbal compounds， the integration of liquid chromatography-mass spectrometry with two-dimensional chromatography and intelligent data mining strategies has enabled high-throughput characterization of the complex chemical constituents of TCMs， as well as the discovery of novel compounds. Furthermore， advancements in multidimensional high-performance preparative chromatography and the development of novel multidimensional multi-channel separation and purification devices have overcome bottlenecks in the large-scale systematic preparation of TCM compounds. Additionally， nuclear magnetic resonance technology， enhanced by artificial intelligence techniques， such as intelligent heteronuclear single quantum coherence （HSQC） recognition and deep learning models， has significantly improved the efficiency and accuracy of structural identification. In the study of the biological effects of herbal substances， target-oriented and phenotype-oriented pharmacological technologies， such as cellular label-free integrative pharmacology， thermal proteome profiling， and affinity mass spectrometry， have facilitated the discovery of targets and the elucidation of mechanisms for bioactive components in TCM. Moreover， TCM databases and computational simulation techniques， including virtual screening， molecular dynamics， and artificial intelligence prediction models， have supported the construction and simulation of complex "multi-component and multi-target" interaction networks. Structural biology techniques， particularly cryo-electron microscopy， have provided atomic-level insights into the interactions between TCM bioactive components and target proteins， advancing our understanding of structure-activity relationships and multi-target mechanisms. In conclusion， the synergistic advancement of various techniques， including separation analysis， bioeffect evaluation， and computational modelling， is driving a paradigm shift in herbal material science from "experience-dependent" to "data-driven" approaches. The ongoing emergence and integration of novel technologies will continue to reveal unexplored areas within traditional Chinese medicine， systematically elucidate its multi-component， multi-target synergistic mechanisms， and enable the in-depth discovery of novel structures， targets， and biological effects. This progress will provide innovation insights to support the inheritance and innovation of traditional Chinese medicine as well as modern drug discovery.
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BibTeX
@article{liu2026research,
title = {{[Research methods and technological advancements in herbal material science].}},
author = {Yan-Fang Liu and Han Zhou and Ji-Xia Wang and Ai-Jin Shen and Dian Liu and Yang Han and Wen-Yi Yu and Bin Yuan and Zhen Wang and Jie Zeng and Xing-Ya Xue and Jia-Tao Feng and Zhi-Mou Guo and Xin-Miao Liang},
journal = {Se pu = Chinese journal of chromatography},
year = {2026},
month = aug,
doi = {10.3724/sp.j.1123.2026.03008},
url = {https://europepmc.org/article/MED/42865268},
note = {CC BY},
}
RIS
TY - JOUR
TI - [Research methods and technological advancements in herbal material science].
AU - Yan-Fang Liu
AU - Han Zhou
AU - Ji-Xia Wang
AU - Ai-Jin Shen
AU - Dian Liu
AU - Yang Han
AU - Wen-Yi Yu
AU - Bin Yuan
AU - Zhen Wang
AU - Jie Zeng
AU - Xing-Ya Xue
AU - Jia-Tao Feng
AU - Zhi-Mou Guo
AU - Xin-Miao Liang
PY - 2026
DA - 2026/08/01
JO - Se pu = Chinese journal of chromatography
DO - 10.3724/sp.j.1123.2026.03008
UR - https://europepmc.org/article/MED/42865268
AB - Traditional Chinese medicine （TCM）， as a complex system of substances， has long faced the challenges of an unclear material basis and obscure mechanisms of action， which has hindered its modernization and internationalization. To address these challenges， the "Herbalome" project was launched in 2007. This initiative aims to systematically reveal the material composition， structure， and biological functions of TCM through the integration of multidisciplinary technologies， thereby elucidating the synergistic mechanisms of multi-component and multi-target interactions. This paper reviews key methodological and technological advancements in the field of herbal material science. Specifically， regarding the composition and structural identification of herbal compounds， the integration of liquid chromatography-mass spectrometry with two-dimensional chromatography and intelligent data mining strategies has enabled high-throughput characterization of the complex chemical constituents of TCMs， as well as the discovery of novel compounds. Furthermore， advancements in multidimensional high-performance preparative chromatography and the development of novel multidimensional multi-channel separation and purification devices have overcome bottlenecks in the large-scale systematic preparation of TCM compounds. Additionally， nuclear magnetic resonance technology， enhanced by artificial intelligence techniques， such as intelligent heteronuclear single quantum coherence （HSQC） recognition and deep learning models， has significantly improved the efficiency and accuracy of structural identification. In the study of the biological effects of herbal substances， target-oriented and phenotype-oriented pharmacological technologies， such as cellular label-free integrative pharmacology， thermal proteome profiling， and affinity mass spectrometry， have facilitated the discovery of targets and the elucidation of mechanisms for bioactive components in TCM. Moreover， TCM databases and computational simulation techniques， including virtual screening， molecular dynamics， and artificial intelligence prediction models， have supported the construction and simulation of complex "multi-component and multi-target" interaction networks. Structural biology techniques， particularly cryo-electron microscopy， have provided atomic-level insights into the interactions between TCM bioactive components and target proteins， advancing our understanding of structure-activity relationships and multi-target mechanisms. In conclusion， the synergistic advancement of various techniques， including separation analysis， bioeffect evaluation， and computational modelling， is driving a paradigm shift in herbal material science from "experience-dependent" to "data-driven" approaches. The ongoing emergence and integration of novel technologies will continue to reveal unexplored areas within traditional Chinese medicine， systematically elucidate its multi-component， multi-target synergistic mechanisms， and enable the in-depth discovery of novel structures， targets， and biological effects. This progress will provide innovation insights to support the inheritance and innovation of traditional Chinese medicine as well as modern drug discovery.
SN - 1000-8713
SN - 1872-2059
ER -