Protein drug binding site prediction method based on deep learning

A combination site and deep learning technology, applied in proteomics, genomics, informatics, etc., to achieve the effect of accuracy assurance

Pending Publication Date: 2020-07-21
OCEAN UNIV OF CHINA +1
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Problems solved by technology

However, it ignores the important factors that affect the protein binding sit

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  • Protein drug binding site prediction method based on deep learning
  • Protein drug binding site prediction method based on deep learning
  • Protein drug binding site prediction method based on deep learning

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Embodiment Construction

[0043]The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0044] according to Figure 1 to Figure 6 As shown, a protein drug binding site prediction method based on deep learning includes a training model and a prediction model. The training model extracts features and labels from known protein databases, acquires data, completes neural network training, and obtains The model used for prediction, that is, the prediction model, the trained model performs the same preprocessing on the new protein and then extracts features t...

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Abstract

The invention provides a protein drug binding site prediction method based on deep learning, and the method comprises the following steps: 1, selecting a plurality of proteins in a protein database toform a training set, a plurality of proteins to form a verification set, and a plurality of proteins to form a test set, wherein the training set being used for training a training model; step 2, carrying out feature extraction and label extraction on the protein database through the trained training model to obtain data, finishing training of a neural network and obtaining a prediction model; and 3, inputting the new protein into the prediction model, and positioning and predicting the position of the binding site. The method has the advantages that the forming factors of the binding site are comprehensively considered, and the binding site is positioned and predicted based on deep learning.

Description

technical field [0001] The invention belongs to the field of binding site prediction methods, in particular to a method for predicting protein drug binding sites based on deep learning. Background technique [0002] At present, with the emergence of new diseases and the increase of drug resistance of pathogens such as viruses and bacteria, the research and development of drugs is facing enormous pressure. The research and development of drugs needs to go through multiple processes such as the discovery of lead compounds, clinical trials, marketing and tracking, which consumes a lot of manpower, material resources, financial resources and time. The emergence of computer-aided drug design has solved some problems to a certain extent. Computer-aided drug design provides assistance for drug development by using computers to simulate the metabolism and screening of drugs. In computer-aided drug design, virtual screening is a key step, which lays the foundation for the discovery ...

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Application Information

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IPC IPC(8): G16B20/30
CPCG16B20/30
Inventor 魏志强李臻江明建张树刚孟美
Owner OCEAN UNIV OF CHINA
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