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A network pharmacology approach for the discovery of active ingredients and their targets in traditional Chinese medicine

A network pharmacology and active ingredient technology, applied in the field of computer-aided drug design, can solve the problems of low proportion of insilico technology and poor application value, and achieve the effect of improving prediction accuracy and efficiency

Active Publication Date: 2015-12-09
ZHEJIANG UNIV
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Problems solved by technology

However, at present, the proportion of insilico technology in the research and development of traditional Chinese medicine is still very low, and its application value cannot be well reflected

Method used

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  • A network pharmacology approach for the discovery of active ingredients and their targets in traditional Chinese medicine

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Embodiment Construction

[0030] In order to make the purpose, embodiment and advantages of the present invention clearer, here in conjunction with specific implementation example, make further detailed description, the following is to use this method to predict a kind of traditional Chinese medicine commonly used in promoting blood circulation, dispelling wind and relieving pain—the activity of Rhizoma Chuanxiong Examples of components and corresponding targets.

[0031] A. Collect compound (drug), protein and interaction data between them to construct the training set.

[0032] The DrugBank3.0 database (C.Knoxetal., NucleicAcidsResearch, 201139(suppl1), p.D1035-D1041) provides information on more than 1,000 US FDA-approved drugs and more than 5,000 experimental drugs in XML format. These drugs are known Information about the target (protein) of the drug and the interaction relationship between these drugs and the protein.

[0033] Download an XML file containing all drug and protein information for ...

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Abstract

The invention discloses a network pharmacology method used for finding active ingredients of traditional Chinese medicine and effect targets thereof. The network pharmacology method comprises the steps as follows: chemical compounds and proteins that can build training sets are collected, and characteristic descriptors are calculated according to molecular structures of the chemical compounds and amino acid sequences of the proteins; the training sets are built based on the characteristic descriptors of the chemical compounds and the proteins, predictive models relative to the interaction of the chemical compounds and the proteins are built according to a machine learning method; the known chemical compound ingredients of the traditional Chinese medicine needing to be forecasted, the characteristic descriptors are calculated, and forecast sets are built; the built predictive models are utilized to forecast the forecast sets, and the chemical compounds and the proteins with the forecasted interaction results greater than a given threshold are used for building a network; and the chemical compounds and the proteins with larger network node connection number are the potential active ingredients and the potential effect targets. The network pharmacology method can improve the finding accuracy rate and finding efficiency of the active ingredients of the traditional Chinese medicine and the effect targets.

Description

technical field [0001] The invention relates to the field of computer-aided drug design, in particular to a network pharmacology method for discovering active ingredients of traditional Chinese medicine and their targets based on the similarity between compounds and proteins. Background technique [0002] Traditional Chinese medicine has the characteristics of multi-component and multi-target synergistic overall action. The relationship between each component and target is actually a complex network structure. However, for a long time, the research and development of traditional Chinese medicine has basically regarded the drug as a single disturbance factor, and based on this to study the relationship between it and the biological response system ("point-system"), which cannot well reflect the traditional Chinese medicine intervention system and biological response. The interactive relationship between systems ("system-system") makes it difficult to clarify the effective sub...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/16
Inventor 黄剑平范骁辉
Owner ZHEJIANG UNIV
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