{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T21:28:21Z","timestamp":1793827701533,"version":"4.6.1"},"reference-count":165,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Chem."],"abstract":"<jats:p>Molecular dynamics (MD) simulation is a computational technique based on Newtonian mechanics and statistical physics that tracks molecular motion and ligand-target recognition at atomic resolution. In recent years, with advances in computational resources and continuous optimization of simulation algorithms, the application of MD simulations in traditional Chinese medicine (TCM) research and development has expanded steadily. Because TCM involves chemically diverse constituents, multiple targets, metabolic transformation, and pathway-level regulation, its mechanisms are difficult to interpret using static or single-target approaches alone. Owing to its high spatiotemporal resolution, MD simulation can characterize binding modes, structural adaptation, and interaction patterns of representative TCM constituents with target proteins. When combined with network pharmacology, multi-omics, artificial intelligence (AI)-assisted modeling, and experimental validation, MD-derived evidence can help transform static compound\u2013target associations into testable mechanistic hypotheses. This review summarizes the methodological development, software platforms, databases, and computational workflows of MD simulation, with emphasis on their relevance to TCM-oriented mechanism research. Representative applications involving flavonoids, alkaloids, glycosides, terpenoids, and polysaccharides are discussed to show how MD provides molecular-level evidence for selected compound-target interactions, membrane-associated behavior, receptor recognition, and free-energy profiles. The review also highlights key challenges, including high computational cost, insufficient sampling, uncertain force-field parameters, difficulty in modeling multicomponent systems, limited trajectory reproducibility, and insufficient experimental validation. Looking ahead, the further integration of artificial intelligence, network pharmacology, and high-throughput screening is exp ected to enhance the role of MD simulations in the modernization of TCM research.<\/jats:p>","DOI":"10.3389\/fchem.2026.1879034","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T15:49:44Z","timestamp":1784821784000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Molecular dynamics simulation in traditional Chinese medicine research: from molecular mechanisms to multiscale validation"],"prefix":"10.3389","volume":"14","author":[{"given":"Xinyi","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Pharmacy, Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haitao","family":"Du","sequence":"additional","affiliation":[{"name":"Shandong Academy of Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haotian","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanan","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Shandong Academy of Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengru","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shandong Academy of Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Ding","sequence":"additional","affiliation":[{"name":"Shandong Academy of Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Wang","sequence":"additional","affiliation":[{"name":"Shandong Academy of Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate structure prediction of biomolecular interactions with AlphaFold 3","volume":"630","author":"Abramson","year":"2024","journal-title":"Nature"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1589","DOI":"10.1021\/cr040426m","article-title":"Molecular dynamics: survey of methods for simulating the activity of proteins","volume":"106","author":"Adcock","year":"2006","journal-title":"Chem. 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