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Structure-Guided Discovery of PD-1/PD-L1 Interaction Inhibitors: Peptide Design, Screening, and Optimization via Computation-Aided Phage Display Engineering
- Source :
- Journal of Chemical Information and Modeling; March 2024, Vol. 64 Issue: 5 p1615-1627, 13p
- Publication Year :
- 2024
-
Abstract
- Cancer immunotherapy harnesses the immune system to combat tumors and has emerged as a major cancer treatment modality. The PD-1/PD-L1 immune checkpoint modulates interactions between tumor cells and T cells and has been extensively targeted in cancer immunotherapy. However, the monoclonal antibodies known to target this immune checkpoint have considerable side effects, and novel PD-1/PD-L1 inhibitors are therefore required. Herein, a peptide inhibitor to disrupt PD-1/PD-L1 interactions was designed through structure-driven phage display engineering coupled to computational modification and optimization. BetaPb, a novel peptide library constructed by using the known structure of PD-1/PD-L, was used to develop inhibitors against the immune checkpoint, and specific peptides with high affinity toward PD-1 were screened through enzyme-linked immunosorbent assays, homogeneous time-resolved fluorescence, and biolayer interferometry. A potential inhibitor, B8, was preliminarily screened through biopanning. The binding affinity of B8toward PD-1 was confirmed through computation-aided optimization. Assessment of B8variants (B8.1, B8.2, B8.3, B8.4, and B8.5) demonstrated their attenuation of PD-1/PD-L1 interactions. B8.4exhibited the strongest attenuation efficiency at a half-maximal effective concentration of 0.1 µM and the strongest binding affinity to PD-1 (equilibrium dissociation constant = 0.1 µM). B8.4outperformed the known PD-1/PD-L1 interaction inhibitor PL120131 in disrupting PD-1/PD-L1 interactions, revealing that B8.4has remarkable potential for modification to yield an antitumor agent. This study provides valuable information for the future development of peptide-based drugs, therapeutics, and immunotherapies for cancer.
Details
- Language :
- English
- ISSN :
- 15499596 and 1549960X
- Volume :
- 64
- Issue :
- 5
- Database :
- Supplemental Index
- Journal :
- Journal of Chemical Information and Modeling
- Publication Type :
- Periodical
- Accession number :
- ejs65495134
- Full Text :
- https://doi.org/10.1021/acs.jcim.3c01500