A graph attention-based deep learning network for predicting biotech-small-molecule drug interactions.

ABSTRACT:

Motivation

The increasing demand for effective drug combinations has made drug-drug interaction prediction a critical task in modern pharmacology. While most existing research focuses on small-molecule drugs, the role of biotech drugs in complex disease treatments remains relatively unexplored. Biotech drugs, derived from biological sources, have unique molecular structures that differ significantly from those of small molecules, making their interactions more challenging to predict.

Results

This study introduces a novel graph attention network-based deep learning framework that improves interaction prediction between biotech and small-molecule drugs. Experimental results demonstrate that the proposed method outperforms existing methods in multiclass drug-drug interac

SUBMITTER: Nasiri F 

PROVIDER: S-EPMC12408249 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature