CDIS V1.0: A program for non-targeted rapid identification of cyclic dipeptides

Area of Science:

• Biochemistry and Bioinformatics
• Natural Product Chemistry
• Pharmacology

Background:

• Cyclic dipeptides are six-membered cyclic compounds with diverse pharmacological activities.
• Manual identification of cyclic dipeptides is challenging due to complexity and time requirements.
• Existing methods lack efficiency in identifying novel cyclic dipeptides.

Purpose of the Study:

• To develop a rapid and efficient program for identifying cyclic dipeptides.
• To analyze the cyclic dipeptide composition in raw and vinegar-processed deer antler and vinegar.
• To discover new natural cyclic dipeptides and understand the impact of vinegar processing.

Main Methods:

• Development of the Cyclic Dipeptide Identification System V1.0 (CDIS V1.0) using Python programming.
• Integration of mass spectrometry analysis with multi-level screening and matching algorithms for characteristic fragment ions.
• Analysis of cyclic dipeptide profiles in raw deer antler, vinegar-processed deer antler, and vinegar.

Main Results:

• The CDIS V1.0 program enables rapid identification of cyclic dipeptides within seconds.
• Identified 13, 45, and 50 natural cyclic dipeptides in raw deer antler, vinegar-processed deer antler, and vinegar, respectively.
• Discovered 18 new natural cyclic dipeptides, including five novel lysine-containing cyclic dipeptides.

Conclusions:

• The CDIS V1.0 program significantly enhances the efficiency of cyclic dipeptide identification.
• Vinegar processing alters the cyclic dipeptide composition, suggesting efficacy modulation in Chinese herbal medicines.
• The developed system facilitates the discovery of novel cyclic dipeptides and supports further research into their bioactivities.