Activity-annotated molecular networking accelerates active molecule screening from natural products.

Area of Science:

• Natural Product Chemistry
• Metabolomics
• Bioactivity Screening

Background:

• Screening natural active molecules is challenging and time-consuming.
• Linking massive-scale molecules in crude extracts with their activities can significantly improve this process.

Purpose of the Study:

• Introduce Activity-Annotated Molecular Networking (AAMN) for direct active molecule screening from crude natural extracts.
• Accelerate the identification of bioactive compounds from natural products.

Main Methods:

• Annotate activity data onto molecular networks based on the correlation between molecular abundance and activity.
• Utilize fragmentation trees for high-confidence structure annotation of screened molecules.
• Employ correlation coefficients (r) and multiple hypothesis testing-corrected p values to reduce false discovery rates.

Main Results:

• Applied AAMN to screen for α-glucosidase inhibition active molecules from Urtica laetevirens Maxim.
• Prioritized 34 molecules from a dataset of 12,501 metabolite molecules.
• Confirmed the activity of screened molecules through targeted isolation, demonstrating AAMN's effectiveness.

Conclusions:

• Activity-Annotated Molecular Networking (AAMN) is a robust and practical strategy for active molecule screening from natural products.
• AAMN significantly enhances the efficiency of natural product drug discovery.
• This approach facilitates the rapid identification of bioactive compounds in complex mixtures.