Evidence mapPaperPMID 42564957Full record

ReviewFrontiers in chemistry2026

Molecular dynamics simulation in traditional Chinese medicine research: from molecular mechanisms to multiscale validation.

Xinyi Zhou, Haitao Du, Haotian Yang, Yanan Hu, Cheng Wang, Mengru Zhang, Xiaoyan Ding, Ping Wang

Abstract readReview
In one paragraph

Review in Frontiers in chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xinyi ZhouSchool of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China.
Haitao DuShandong Academy of Chinese Medicine, Jinan, China.
Haotian YangSchool of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China.
Yanan HuSchool of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China.
Cheng WangShandong Academy of Chinese Medicine, Jinan, China.
Mengru ZhangShandong Academy of Chinese Medicine, Jinan, China.
Xiaoyan DingShandong Academy of Chinese Medicine, Jinan, China.
Ping WangShandong Academy of Chinese Medicine, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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-target 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.

Indexed as

bioactive compound screeninghigh-throughput screeningmolecular dynamics simulationtarget mechanismstraditional Chinese medicine drug development

Identifiers

PMID42564957
PMCPMC13446134

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.