CANPA: Computer-Assisted Natural Products Anticipation

Area of Science:

• Natural Product Chemistry
• Computational Chemistry
• Metabolomics

Background:

• Traditional natural product discovery is slow, with structural information revealed late in the process.
• Existing methods lack predictive capabilities for novel compound structures early on.

Purpose of the Study:

• To introduce MetWork, a novel computational platform for anticipating metabolite structures.
• To demonstrate MetWork's utility in discovering new monoterpene indole alkaloids.

Main Methods:

• Integration of a MS/MS prediction module and a library of biochemical transformations.
• Application of MetWork to a molecular networking-based dereplication strategy.
• Targeted isolation of predicted compounds from Alstonia balansae.

Main Results:

• MetWork successfully anticipated the structures of five previously undescribed sarpagine-like N-oxide alkaloids.
• The study showcases the first nonpeptidic molecular networking-based discovery workflow with computer-generated pre-isolation structures.
• Five novel alkaloids were isolated and identified from Alstonia balansae.

Conclusions:

• MetWork significantly accelerates natural product discovery by predicting structures computationally.
• This platform enables a proactive approach to identifying and isolating novel compounds.
• The successful application highlights a new paradigm in natural product research.