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Iterative optimization yields Mcl-1–targeting stapled peptides with selective cytotoxicity to Mcl-1–dependent cancer cells
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Iterative optimization yields Mcl-1–targeting stapled peptides with selective cytotoxicity to Mcl-1–dependent cancer cells
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Iterative optimization yields Mcl-1–targeting stapled peptides with selective cytotoxicity to Mcl-1–dependent cancer cells
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Journal Article
Iterative optimization yields Mcl-1–targeting stapled peptides with selective cytotoxicity to Mcl-1–dependent cancer cells
2018
Overview
Bcl-2 family proteins regulate apoptosis, and aberrant interactions of overexpressed antiapoptotic family members such as Mcl-1 promote cell transformation, cancer survival, and resistance to chemotherapy. Discovering potent and selective Mcl-1 inhibitors that can relieve apoptotic blockades is thus a high priority for cancer research. An attractive strategy for disabling Mcl-1 involves using designer peptides to competitively engage its binding groove, mimicking the structural mechanism of action of native sensitizer BH3-only proteins. We transformed Mcl-1–binding peptides into α-helical, cell-penetrating constructs that are selectively cytotoxic to Mcl-1–dependent cancer cells. Critical to the design of effective inhibitors was our introduction of an all-hydrocarbon cross-link or “staple” that stabilizes α-helical structure, increases target binding affinity, and independently confers binding specificity for Mcl-1 over related Bcl-2 family paralogs. Two crystal structures of complexes at 1.4 Å and 1.9 Å resolution demonstrate how the hydrophobic staple induces an unanticipated structural rearrangement in Mcl-1 upon binding. Systematic sampling of staple location and iterative optimization of peptide sequence in accordance with established design principles provided peptides that target intracellular Mcl-1. This work provides proof of concept for the development of potent, selective, and cell-permeable stapled peptides for therapeutic targeting of Mcl-1 in cancer, applying a design and validation workflow applicable to a host of challenging biomedical targets.
