Drug target interaction relationship prediction method based on collaborative matrix decomposition

Abstract

The invention discloses a drug target interaction relationship prediction method based on collaborative matrix decomposition, which considers drug attribute similarity and target attribute similarity,and combines drug topological structure similarity and target topological structure similarity to improve drug target interaction relationship prediction accuracy. The method comprises the followingsteps of: acquiring drug attribute similarity and target attribute similarity data and drug target interaction relationship data; constructing a drug attribute feature similarity matrix, a target point attribute feature similarity matrix, a drug topological similarity matrix and a target point topological similarity matrix; performing graph regularization-based collaborative matrix decomposition on the drug target incidence matrix, and integrating attribute feature similarity and topological structure similarity information of the drug and the target to obtain a final target function; and performing iterative updating by using a Newton method to obtain the feature representation of the drug and the target, reconstructing a drug-target interaction relationship matrix, and predicting the drug-target interaction relationship.

Description

technical field [0001] The invention relates to the technical field of drug-target interaction relationship prediction, in particular to a method for predicting drug-target interaction relationship based on synergistic matrix decomposition. Background technique [0002] Drug targets are the binding sites where drugs interact with the human body, including genes, receptors, enzymes, ion channels, transporters, nucleic acids, etc., through the combination of drugs and sites, the changes in biological events are affected, so as to achieve the therapeutic effect of drugs . The identification of drug-target interactions (DTI) is the basis of modern drug discovery and development. Drug-target interaction prediction plays an important role in drug discovery, drug side effect prediction, drug repositioning, and the process of discovering new targets that interact with existing drugs. Traditional biochemical experimental methods for identifying new DTIs require extremely expensive ...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is that the existing method based on matrix decomposition has limited representation information of drugs and targets, and does not consider the local geometric structure information of drugs or targets, resulting in low accuracy in many cases

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