Medicament combination predicting method based on medicament similarity network data

A combined prediction and similarity technology, applied in the field of bioinformatics, can solve problems such as low accuracy of results, failure to reflect drug similarity network topology information, strong side effects, etc., and achieve the effect of improving accuracy

Active Publication Date: 2019-09-17
XIDIAN UNIV
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Problems solved by technology

In the second category, taking two drugs at the same time leads to strong side effects or less therapeutic effect than taking a single drug. Such a drug combination relationship is called antagonism
This type of method makes good use of the multi-omics da

Method used

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  • Medicament combination predicting method based on medicament similarity network data
  • Medicament combination predicting method based on medicament similarity network data
  • Medicament combination predicting method based on medicament similarity network data

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Embodiment Construction

[0040] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0041] refer to figure 1 , The implementation steps of this example are as follows:

[0042] Step 1, download the drug data and construct five drug similarity networks.

[0043] 1a) Taking the DrugBank database as an example, build a drug chemical structure similarity network N ch :

[0044] 1a1) Download the chemical structure data CH of 1284 drugs from the DrugBank database 1284 ;

[0045] 1a2) Based on the chemical structure data CH of the drug 1284 , use the PaDEL-Descriptor software to get the chemical structure feature set of the drug The collection has 1284 medicinal chemical structure features;

[0046] 1a3) Based on the collection of medicinal chemical structure features Get medicinal chemical structure similarity network N ch , any element in the network is calculated as follows:

[0047]

[0048] Among them, ...

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Abstract

The invention discloses a medicament combination predicting algorithm based on a medicament similarity network, wherein the algorithm mainly settles a problem of low accuracy of a medicament combination predicting result in prior art. The medicament combination predicting algorithm is characterized by comprising steps of downloading data from a medicament database, constructing the medicament similarity network; downloading data from a medicament combination database; obtaining a network importance score based on medicament combination data and the medicament similarity network; obtaining a total set of random walk paths of multiple networks by means of a biased random walk algorithm, and training the total set of the random walk paths for obtaining a medicament node characteristic vector; training the medicament combination data and the medicament node characteristic vector by means of a random forest model, and obtaining a medicament combination predicting model; and inputting medicament pair data into the medicament combination predicting model, obtaining a medicament pair score, and using the medicament pair with score which is higher than 0.5 as a cooperation medicament combination. The medicament combination predicting algorithm improves medicament combination predicting accuracy and can be used for predicting the cooperative medicament combination candidate.

Description

technical field [0001] The invention belongs to the technical field of bioinformatics, and in particular relates to a drug combination prediction method, which can be used to provide candidate drug combination references for drug combination experiments. Background technique [0002] Drug combination therapy refers to the treatment of disease patients with two or more drugs at the same time. According to the effect of drug combination therapy, the relationship of drug combination therapy can be divided into three categories: the first category, the simultaneous use of two drugs at a low dose can achieve the effect of a single drug at a high dose, such a drug combination relationship is called It is synergy. In the second category, taking two drugs at the same time leads to strong side effects or less therapeutic effect than taking a single drug. Such a drug combination relationship is called antagonism. In the third category, the effects of two drugs taken together and tak...

Claims

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Application Information

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IPC IPC(8): G16C20/30G16C20/50
CPCG16C20/30G16C20/50
Inventor 鱼亮夏明飞
Owner XIDIAN UNIV
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