Downstream processing and structure confirmation of chemoenzymatically produced macrocycles

Cyclic peptides have been reported to possess biological properties ranging from antibacterial to immunosuppressive to anti-tumor, and the dominant trend in peptide drug discovery over the last two decades has been a shift away from naturally derived cyclic peptides and towards cyclic peptide analogues optimised for potency, stability, and pharmacokinetic features.1

Similarly, the discovery of cyclic peptides with distinctive properties such cell membrane pen-etration, oral bioavailability, chemical stability, metabolic stability, and uniform structure was made possible through the development of assemble and modification techniques. The validation of efficient peptide synthesis is hampered by challenges in the successful identification of cyclic peptide sequences by mass spectrometry, adding challenges in the future develop-ment and study of relevant cyclic peptides.2

In this research, a set of predicted fragment ions was created by improving the De novo pep-tide sequencing methods to be applicable with cyclic peptides.3

Several cyclic peptides have been examined using a UHPLC-QToF (Ultra high performance liquid chromatography linked to a quadrupole Time-of-Flight mass spectrometer) and the results have been compared to previously generated predicted data. The analysis of the successfully compared ions highlighted reproducible patterns; this data will be used to develop automated methods to verify the successful synthesis of cyclic peptides.

Python scripts were used to produce the predicted fragmentation pattern of the cyclic peptides and compared them to their experimental data. This approach will be used in the future in conjunction with Machine Learning techniques for further development.

References
1. S. H. Joo Biomol. Ther. 2012, 20, 19-26.
2. A. I. Llobet, et al. J.Org.Chem. 2019, 84, 4615-4628.
3. M. Yilmaz, W. E. Fondrie, W. Bittremieux, S. Oh, W. S. Noble bioRxiv 2022.