Lv, Li, and Wang developed ACP-EPC, an interpretable deep learning framework that combines a pre-trained protein language model with multi-view feature extraction to accurately predict anticancer peptides. This computational advancement addresses challenges in peptide-based drug discovery by enhancing predictive accuracy and interpretability, facilitating identification of effective anticancer candidates. Integrating protein sequence understanding with diverse biochemical features, ACP-EPC represents a significant tool for accelerating peptide therapeutic development.