Cyclic Peptide Characterization with Custom Unnatural Amino Acids

June 1, 2026

Cyclic peptides are a rapidly emerging class of therapeutics that combine the structural complexity of biologics with the synthetic flexibility of small molecules, but their structural diversity and incorporation of unnatural amino acids create significant challenges for mass spectrometry–based characterization. The lack of support for noncanonical residues and cyclic peptide fragmentation complicates reliable MS/MS annotation and limits efficient structure elucidation.

This poster shows how scientists at Merck & Co., use a new customizable workflow in Genedata Expressionist^®, that enables cyclic peptide characterization through user-defined unnatural amino acid editing and adapted peptide mapping for LC‑pseudo‑MS³ data. You will learn how customizable residue definitions and workflow adaptations support MS/MS annotation of cyclic peptides, improve sequence coverage of complex peptide structures, and accelerate structure characterization without requiring digestion. It also demonstrates how flexible, traceable workflows extend peptide mapping to synthetic peptide modalities, enabling scalable and reliable characterization of cyclic peptides with unnatural amino acids. Designed for scientists working in peptide characterization and synthetic peptide drug development.