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Identification and engineering of potent cyclic peptides with selective or promiscuous binding through biochemical profiling and bioinformatic data analysis

Thomas Smith, Bhaskar Bhushan, Daniele Granata, Christian S. Kaas, Birgitte Andersen, Klaas W. Decoene, Qiansheng Ren, Haimo Liu, Xin-Ping Qu, Yang Yang, Pan Jia, Quijia Chen, Martin Münzel, Akane Kawamura

2023RSC Chemical Biology11 citationsDOIOpen Access PDF

Abstract

cyclic peptide ligands can be rapidly generated against a given target using mRNA display. In this study we harness mRNA display technology and the wealth of next generation sequencing (NGS) data generated to explore both experimental approaches and bioinformatic, statistical data analysis of peptide enrichment in cross-screen selections to rapidly generate high affinity CPs with differing intra-family protein selectivity profiles against fibroblast growth factor receptor (FGF-R) family proteins. Using these methods, CPs with distinct selectivity profiles can be generated which can serve as valuable tool compounds to decipher biological questions.

Topics & Concepts

Computational biologyCyclic peptideProfiling (computer programming)ChemistryIdentification (biology)BiochemistryPeptideBiologyComputer scienceBotanyOperating systemChemical Synthesis and AnalysisFibroblast Growth Factor ResearchMonoclonal and Polyclonal Antibodies Research
Identification and engineering of potent cyclic peptides with selective or promiscuous binding through biochemical profiling and bioinformatic data analysis | Litcius