AI-driven anticancer peptide de novo design

Conventional cancer treatments can damage healthy tissues and cause substantial off-target toxicity, creating an urgent need for more precise and safer therapies. Anticancer peptides are promising because they can selectively disrupt cancer cells while potentially reducing harm to healthy cells. However, natural anticancer peptides are limited in number and diversity, and identifying effective candidates through large-scale experimental screening is costly and time-consuming. We therefore developed an AI-driven framework for the de novo design of novel anticancer peptides, enabling cancer-type-specific candidate generation and prioritisation followed by experimental validation.