CMA-DTI: a cross-modal fusion and attentive interaction network for interpretable drug-target interaction prediction (opens in new tab)

BackgroundDrug–target interaction (DTI) prediction is an important task in early-stage drug discovery. Although deep learning methods have improved predictive performance, effectively integrating heterogeneous drug representations and providing interpretable evidence for local interaction patterns remain challenging.MethodsWe propose CMA-DTI, a cross-modal fusion and attentive interaction framework for DTI prediction. CMA-DTI integrates GCN-based molecular graph representations, ChemBERTa-der...