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[Application of reverse molecular docking technology in target prediction, active ingredient screening and action mechanism exploration of traditional Chinese medicine].

Authors: Hong-Wei, Guan; Li-Jun, Xu; Hui, Dong;

[Application of reverse molecular docking technology in target prediction, active ingredient screening and action mechanism exploration of traditional Chinese medicine].

Abstract

Traditional Chinese medicine(TCM) modernization has gradually become a worldwide trend. Reverse docking technology has also gradually become a useful tool for TCM modernization. It involves docking a small-molecule drug in the potential binding cavities of a set of clinically relevant macromolecular targets. Detailed analysis of the binding characteristics was used for the ranking of the targets according to the tightness of binding. This process can be used to potentially identify the novel molecular targets for the drug which may be relevant to its mechanism of action or side effect. In order to explore the action mechanism, screen the active ingredients and seek the treating target of TCM, reverse molecular docking technology has been widely used and has achieved remarkable results in recent years. In this review, we summarized the application of reverse molecular docking technology in the target seeking, active ingredients screening and potential mechanism exploration of TCM, which may provide more scientific basis for the clinical research and development of new herbal drugs.

Related Organizations
Keywords

Molecular Docking Simulation, Medicine, Chinese Traditional, Drugs, Chinese Herbal

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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