Multidimensional Design of Anticancer Peptides

The computer‐assisted design and optimization of peptides with selective cancer cell killing activity was achieved through merging the features of anticancer peptides, cell‐penetrating peptides, and tumor‐homing peptides. Machine‐learning classifiers identified candidate peptides that possess the predicted properties. Starting from a template amino acid sequence, peptide cytotoxicity against a range of cancer cell lines was systematically optimized while minimizing the effects on primary human endothelial cells. The computer‐generated sequences featured improved cancer‐cell penetration, induced cancer‐cell apoptosis, and were enabled a decrease in the cytotoxic concentration of co‐administered chemotherapeutic agents in vitro. This study demonstrates the potential of multidimensional machine‐learning methods for rapidly obtaining peptides with the desired cellular activities.