Drug target affinity prediction method based on deep learning

A deep learning and prediction method technology, applied in drug reference, biological neural network model, neural architecture, etc., can solve the problem of affecting prediction accuracy, drug-target interaction accuracy is not high, ignoring drug-target interaction combination Affinity and other issues to achieve the effect of improving fault tolerance, compressing the number, and reducing overfitting
CN110689965AActive Publication Date: 2020-01-14UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
UNIV OF ELECTRONICS SCI & TECH OF CHINA
Publication Date
2020-01-14

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Abstract

The invention discloses a drug target affinity prediction method based on deep learning, and relates to the technical field of drug target affinity prediction. The method comprises the steps of: obtaining a drug compound and target protein data from a Davis data set and a KIBA data set; encoding the compound, and representing the protein by using a position specificity scoring matrix; inputting acompound label code into a CNN model, and performing feature extraction on the compound to obtain molecular representation of the compound; inputting the position specificity scoring matrix of the protein into an LSTM model, performing feature extraction on a protein sequence, and learning an order relationship between amino acids in a protein structure and a relationship between residues on the protein sequence to obtain the sequence representation of the protein; and simultaneously inputting the molecular representations of the compounds and the sequence representations of the proteins intoa fully linked layer to predict the affinity of the interaction of the compounds and the proteins. The method can predict the affinity relationship between the drug and the target more accurately.
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Description

technical field

[0001] The present invention relates to the technical field of drug target affinity prediction, in particular, to a method for predicting drug target affinity based on deep learning. Background technique

[0002] The target of a drug refers to the binding site between the drug and the biomacromolecule of the body, and the target of the drug involves receptors, enzymes, ion channels, transporters, the immune system, genes, etc. Most drug molecules produce therapeutic effects through the interaction with target molecules in the human body, so target selection is a very critical step in drug development. The discovery of new drug targets is often the breakthrough for new drug discovery. Drug-target interactions (DTI) prediction is an important part of the drug discovery process. With the development of bioinformatics and the continuous expansion of public data sets, it is possible to use different calculation methods to predict drug-target interactions, which ...

Claims

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