Intelligent drug target affinity prediction method and process

Abstract

The invention discloses an intelligent drug target affinity prediction method and process. The method comprises the following steps of S1, data extraction, S2, numeralization processing, S3, redundantinformation processing, S4, data splicing processing, S5, affinity prediction and S6, drug molecular factor prediction. According to the method, the variational automatic encoder is used for removinga lot of redundant information existing in the protein sequence feature vector, reducing the feature dimension and improving the prediction accuracy and efficiency; meanwhile, the quantitative structure-activity relationship between the pharmaceutical chemical mechanism and the target is established through a mathematical statistics method, so that the affinity prediction of the pharmaceutical chemical structure is calculated; thus, double-mode prediction analysis is carried out on drug and target affinity, prediction results can be integrated and analyzed, and the prediction accuracy is remarkably improved.

Description

technical field [0001] The invention relates to the technical field of analysis and prediction of drug target affinity, in particular to an intelligent drug target affinity prediction method and process. Background technique [0002] Drug targets refer to the binding sites of drugs in the body, including gene sites, receptors, enzymes, ion channels, nucleic acids and other biomacromolecules. The key to modern new drug research and development is to find, determine and prepare drug screening targets—molecular drug targets. Drug targets refer to the binding sites of drugs in the body, including gene sites, receptors, enzymes, ion channels, nucleic acids and other biomacromolecules. Selecting and determining novel and effective drug targets is the primary task of new drug development. So far, about 500 therapeutic drug targets have been discovered, among which receptors, especially G-protein-coupled receptor (GPCR) targets account for the vast majority, and there are also enz...

AI Technical Summary

Problems solved by technology

[0003] The drug target affinity prediction method and process is to analyze the relationship between the drug and the target to predict the affinity between the drug and the target. In the process of analyzing the interaction relationship between the drug and the target, the protein sequence There is a lot of redundant information in the feature vector, and the feature dimension is high, which affects the accuracy and efficiency of classification and prediction. At the same time, the analysis of the chemical structure of the drug molecule is lacking in the analysis, resulting in poor prediction results.

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