Directional Engineering of Cyclic β-Hairpin Peptides for PET/CT Imaging of PD-L1.

Peptide-based radiopharmaceuticals represent an emerging drug modality for the noninvasive diagnosis and targeted radiotherapy of cancer. However, the discovery of peptide ligands that combine high binding affinity with sufficient stability remains a formidable challenge. Conformation-oriented rational design has proven to be a robust strategy for identifying peptide binders to protein targets involved in protein-protein interactions (PPIs), particularly those mediated by well-defined secondary structures such as β-sheets or α-helices. Inspired by the highly structured β-sheet binding interface between programmed death ligand 1 (PD-L1) and its receptor PD-1, we applied a β-hairpin conformation-oriented evolution strategy to engineer high-affinity PD-L1 binders. Starting from a discovered PD-L1-targeting peptide, TPP-1, as a β-hairpin prototype, we iteratively optimized the peptide by sequentially introducing various β-turn motifs, a tryptophan zipper (Trpzip) motif, and subsequently amide cyclization to "lock" the β-hairpin conformation. This process yielded TPP-10, a side-chain to tail cyclized peptide with a highly stabilized β-hairpin structure, as confirmed by circular dichroism (CD) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and molecular dynamics (MD) simulations. TPP-10 exhibited a significant improvement in binding affinity () for PD-L1 compared with TPP-1, along with markedly enhanced stability. We further evaluated these peptides as radioligands using PET imaging with Ga and Cu. [Ga]TPP-10 demonstrated significantly increased tumor uptake and retention in mouse models, and this performance improvement was even more pronounced when the longer-lived radionuclide Cu was employed. Collectively, these results identify TPP-10 as a promising clinical candidate for PD-L1 PET imaging and highlight β-hairpin-oriented peptide engineering as a powerful approach for developing radiopharmaceuticals targeting aberrant PPIs.