Screening macrocyclic peptide libraries by yeast display allows control of selection process and affinity ranking

Sara Linciano, Ylenia Mazzocato, Zhanna Romanyuk, Filippo Vascon, Lluc Farrera-Soler, Edward Will, Yuyu Xing, Shiyu Chen, Yoichi Kumada, Marta Simeoni, Alessandro Scarso, Laura Cendron, Christian Heinis and Alessandro Angelini ()
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Sara Linciano: Ca’ Foscari University of Venice
Ylenia Mazzocato: Ca’ Foscari University of Venice
Zhanna Romanyuk: Ca’ Foscari University of Venice
Filippo Vascon: University of Padua
Lluc Farrera-Soler: École Polytechnique Fédérale de Lausanne (EPFL)
Edward Will: École Polytechnique Fédérale de Lausanne (EPFL)
Yuyu Xing: Chinese Academy of Sciences
Shiyu Chen: Chinese Academy of Sciences
Yoichi Kumada: Sakyo-ku
Marta Simeoni: Informatics and Statistics, Ca’ Foscari University of Venice
Alessandro Scarso: Ca’ Foscari University of Venice
Laura Cendron: University of Padua
Christian Heinis: École Polytechnique Fédérale de Lausanne (EPFL)
Alessandro Angelini: Ca’ Foscari University of Venice

Nature Communications, 2025, vol. 16, issue 1, 1-23

Abstract: Abstract Macrocyclic peptides represent an attractive drug modality due to their favourable properties and amenability to in vitro evolution techniques such as phage or mRNA display. Although very powerful, these technologies are not without limitations. In this work, we address some of their drawbacks by developing a yeast display-based strategy to generate, screen and characterise structurally diverse disulfide-cyclised peptides. The use of quantitative flow cytometry enables real-time monitoring of the screening of millions of individual macrocyclic peptides, leading to the identification of ligands with good binding properties to five different protein targets. X-ray analysis of a selected ligand in complex with its target reveals optimal shape complementarity and extensive surface interaction, explaining its exquisite affinity and selectivity. The yeast display-based approach described here offers a facile, quantitative and cost-effective alternative to rapidly and efficiently discover and characterise genetically encoded macrocyclic peptide ligands with sufficiently good binding properties against therapeutically relevant targets.

Date: 2025
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DOI: 10.1038/s41467-025-60907-x

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