An integrated platform approach enables discovery of potent, selective and ligand-competitive cyclic peptides targeting the GIP receptor. Issue 11 (2nd March 2022)

• Record Type: Journal Article
• Authors: Bhushan, Bhaskar; Granata, Daniele; Kaas, Christian S.; Kasimova, Marina A.; Ren, Qiansheng; Cramer, Christian N.; White, Mark D.; Hansen, Ann Maria K.; Fledelius, Christian; Invernizzi, Gaetano; Deibler, Kristine; Coleman, Oliver D.; Zhao, Xin; Qu, Xinping; Liu, Haimo; Zurmühl, Silvana S.; Kodra, Janos T.; Kawamura, Akane; Münzel, Martin
• Is Part Of: Chemical science. Volume 13:Issue 11(2022)
• Page Start: 3256
• Page End: 3262
• Publication Date: 2022-03-02
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d1sc06844j
• Languages: English
• ISSNs: 2041-6520

Abstract

Abstract : mRNA display generates vast datasets of protein binders. Bioinformatic clustering of the sequences combined with high throughput synthesis and analysis methods allow efficient prioritisation of hits for in vivo experiments. Abstract : In any drug discovery effort, the identification of hits for further optimisation is of crucial importance. For peptide therapeutics, display technologies such as mRNA display have emerged as powerful methodologies to identify these desired de novo hit ligands against targets of interest. The diverse peptide libraries are genetically encoded in these technologies, allowing for next-generation sequencing to be used to efficiently identify the binding ligands. Despite the vast datasets that can be generated, current downstream methodologies, however, are limited by low throughput validation processes, including hit prioritisation, peptide synthesis, biochemical and biophysical assays. In this work we report a highly efficient strategy that combines bioinformatic analysis with state-of-the-art high throughput peptide synthesis to identify nanomolar cyclic peptide (CP) ligands of the human glucose-dependent insulinotropic peptide receptor (hGIP-R). Furthermore, our workflow is able to discriminate between functional and remote binding non-functional ligands. Efficient structure–activity relationship analysis (SAR) combined with advanced in silico structural studies allow deduction of a thorough and holistic binding model which informs further chemical optimisation, including efficient half-life extension. We report the identification and design of the first de novo, GIP-competitive, incretin receptor family-selective CPs, which exhibit an in vivo half-life up to 10.7 h in rats. The workflow should be generally applicable to any selection target, improving and accelerating hit identification, validation, characterisation, and prioritisation for therapeutic development.