HDN-DDI: a novel framework for predicting drug-drug interactions using hierarchical molecular graphs and enhanced dual-view representation learning.

ABSTRACT:

Background

Drug-drug interactions (DDIs) especially antagonistic ones present significant risks to patient safety, underscoring the urgent need for reliable prediction methods. Recently, substructure-based DDI prediction has garnered much attention due to the dominant influence of functional groups and substructures on drug properties. However, existing approaches face challenges regarding the insufficient interpretability of identified substructures and the isolation of chemical substructures.

Results

This study introduces a novel framework for DDI prediction termed HDN-DDI. HDN-DDI integrates an explainable substructure extraction module to decompose drug molecules and represents them using innovative hierarchical molecular graphs, which effectively incorporates informatio

SUBMITTER: Sun J 

PROVIDER: S-EPMC11765940 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature