Abstract 4463: A novel method for constructing diverse cyclic peptide libraries for efficient screening of PPI inhibitors

Abstract Cyclic peptides drug design and discovery has experienced a resurgence of interest due to their target specificity and metabolic stability. In this study, we developed a novel methodology for generating extensive, structurally diverse, and synthesizable virtual libraries of cyclic peptides. Such libraries are essential for the identification of hit compounds against a spectrum of therapeutic targets through screening assays. We introduce an innovative strategy for the creation of diverse cyclic peptide libraries leveraging a “hierarchical generation” approach combined with artificial intelligence (AI)-driven sampling. Our approach begins with the generation of a library of representative linear peptides which are subsequently subjected to cyclization via an array of cyclization reactions. The generation of linear peptides is executed via a hierarchical generation method wherein amino acids are initially categorized according to their physicochemical properties. Next, a sequence of these properties is formulated, and the similarity of these property sequences is calculated through sequence alignment algorithm. Low-similarity property sequences are then processed by AI models to generated multiple sequences of amino acids, while high-similarity sequences are judiciously excluded. The iteration of this process yields a set of representative linear peptides, which are then cyclized to produce the desired cyclic peptides. Employing this novel methodology, we have successfully generated a virtual cyclic peptide library encompassing nearly 6 million molecular cyclic peptides (covering approximately 4 thousand trillion peptides) within a single week. Over 1000 representative cyclic peptides were selected for synthesis via the solid-phase peptide synthesis (SPPS) technique, and a cyclic peptide library with high structural diversity was obtained. In conclusion, the structural diversity of our library, combined with the successful screening results, highlights the robustness of our method in designing diverse cyclic peptides, particularly for hit identification against traditionally undruggable targets. Our findings underscore the utility of this cyclic peptide library in discovering potential PPI inhibitors. Citation Format: Zhenyu Wu, Xiaoli Hou, Hongbo Zhang. A novel method for constructing diverse cyclic peptide libraries for efficient screening of PPI inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4463.