Deep learning drug interaction prediction method and device, medium and equipment

A technology of deep learning and prediction method, applied in the field of medicine, can solve problems such as insufficient consideration of side information, and achieve the effect of improving accuracy and reducing the probability of adverse reactions

Pending Publication Date: 2022-05-24
SOUTH CHINA UNIV OF TECH
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] In order to overcome the shortcomings and deficiencies in the prior art, the purpose of the present invention is to provide a deep learning drug interaction prediction method, device, medium and equipment; this method can sol...

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  • Deep learning drug interaction prediction method and device, medium and equipment
  • Deep learning drug interaction prediction method and device, medium and equipment
  • Deep learning drug interaction prediction method and device, medium and equipment

Examples

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Embodiment 1

[0063] The present embodiment is a deep learning drug interaction prediction method, the principles thereof, such as Figure 1 as shown, its model structure is as follows Figure 2 as shown. Among them, the atomic-level network refers to the internal graph structure of drug molecules composed of atoms as nodes and chemical bonds as edges. Molecular-level network refers to the graph structure between drug molecules composed of different drug molecules as nodes and whether interactions occur as edges. By building models between two different levels of graph networks, the existing molecular graph representations are solved, and the accuracy of drug interaction prediction results is improved.

[0064] The forecasting method consists of the following steps:

[0065] Step S1, obtain the drug molecular information of the two drugs to be predicted.

[0066]In the S2 step, each drug molecular information is entered into the atomic-level network, which encodes the molecular information of eac...

Embodiment 2

[0113]The present embodiment of a storage medium, wherein the storage medium is stored with a computer program, the computer program when executed by the processor so that the processor to perform the deep learning drug interaction prediction method described in Example I.

Embodiment 3

[0115] The present embodiment of a computing device, comprising a processor and a memory for storing a processor executable program, wherein the processor executes the memory stored program, to implement the deep learning drug interaction prediction method described in Example 1.

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Abstract

The invention provides a deep learning drug interaction prediction method and device, a medium and equipment. The method comprises the following steps: acquiring drug molecule information of two to-be-predicted drugs; the atomic-scale network encodes each piece of drug molecule information, captures interaction information between atoms and chemical bonds, and outputs an encoded drug molecule map to represent zatomj; the molecular level network uses a multi-head attention mechanism to extract the relationship between different drug molecules from each drug molecular map expression zatomj, and outputs a molecular map expression zmolj; and converting the output molecular maps zmol1 and zmol2 of the two drugs into a vector so as to obtain a drug interaction prediction result. According to the method, the problem that side information cannot be fully considered in a traditional framework can be solved, and relation information among different drug molecules can be captured, so that the accuracy of a prediction result is improved.

Description

Technical field [0001] The present invention relates to the field of pharmaceutical technology, more particularly, to a deep learning drug interaction prediction method, apparatus, medium and apparatus. Background [0002] Today, multipharmacy has become a common phenomenon, which also leads to increased odds of drug interactions. Drug-Drug Interaction (DDI) is when a patient takes two or more drugs at the same time, and the efficacy of one drug is affected by the effect of another drug, resulting in a weakening of the drug effect or toxic side effects. Therefore, in the case of combination drugs, how to predict and detect possible adverse drug interactions in advance, thereby reducing potential risks and promoting safe drug combination prescription, has become a major problem that needs to be solved urgently in the field of bioinformatics. [0003] With the establishment and development of more and more public data sets, there is great potential for DDI prediction using predicti...

Claims

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Application Information

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IPC IPC(8): G16H70/40G06N3/04G06N3/08
CPCG16H70/40G06N3/08G06N3/045
Inventor 张通饶晓洁孟献兵陈俊龙
Owner SOUTH CHINA UNIV OF TECH
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