Discovery of Cyclic Peptide Inhibitors Targeting PD-L1 for Cancer Immunotherapy

John Fetse1, Zhen Zhao1, Hao Liu1

  • 1Division of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, 2464 Charlotte Street, Kansas City, Missouri 64108, United States.

Insights

Cyclic peptides targeting programmed cell death ligand-1 (PD-L1) show enhanced anti-tumor activity. Macrocyclization scanning effectively improved peptide stability and bioactivity for cancer immunotherapy applications.

Area of Science:

  • Immunology
  • Biochemistry
  • Medicinal Chemistry

Background:

  • Blockade of the programmed cell death ligand-1 (PD-L1) and programmed cell death-1 (PD-1) interaction is a successful cancer immunotherapy strategy.
  • Peptides offer advantages as immune checkpoint inhibitors but face challenges with stability and delivery.
  • Cyclization of peptides can enhance their biological activity and stability.

Purpose of the Study:

  • To discover cyclic anti-PD-L1 peptides with improved bioactivity using macrocyclization scanning.
  • To evaluate the efficacy of these cyclic peptides in blocking PD-1/PD-L1 interaction and in vivo anti-tumor activity.

Main Methods:

  • Macrocyclization scanning was employed to generate cyclic peptides targeting PD-L1.
  • The PD-1/PD-L1 blocking activity of the cyclic peptides was assessed.
  • In vivo anti-tumor activity of the optimized cyclic peptides was evaluated.

Main Results:

  • Cyclic peptides exhibited up to a 34-fold improvement in PD-1/PD-L1 blocking activity compared to linear counterparts.
  • The developed cyclic peptides demonstrated significant in vivo anti-tumor efficacy.
  • Macrocyclization scanning proved effective in enhancing serum stability and bioactivity.

Conclusions:

  • Macrocyclization scanning is a viable strategy for optimizing bioactive peptides, particularly for modulating protein-protein interactions.
  • Cyclic anti-PD-L1 peptides represent a promising therapeutic approach for cancer immunotherapy.
  • This methodology can be applied to improve other therapeutic peptides targeting protein-protein interactions.

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