Automated annotation of complex natural products using a modular fragmentation-based structure assembly (MFSA)...

Area of Science:

• Chemistry
• Biochemistry
• Computational Chemistry

Background:

• Complex natural products (CNPs) possess intricate polycyclic structures, numerous chiral centers, and unique units, making their structural annotation challenging.
• Accurate structural identification of CNPs is crucial for understanding their biological activity and for drug discovery.
• Existing computational methods often struggle with the high complexity and diversity of CNP structures.

Purpose of the Study:

• To introduce a novel strategy, modular fragmentation-based structural assembly (MFSA), for the efficient and accurate structural annotation of complex natural products.
• To develop a user-friendly Python application, CNPs-MFSA, to implement the MFSA strategy.
• To demonstrate the effectiveness of CNPs-MFSA in identifying daphnane-type diterpenoids and other classes of CNPs.

Main Methods:

• The MFSA strategy involves disassembling CNP structures based on fragmentation patterns and characteristic ions.
• Structural reassembly is achieved by recognizing target compounds via a pseudo-library and analyzing neutral losses.
• The CNPs-MFSA software was developed in Python and validated using an in-house daphnane library.

Main Results:

• CNPs-MFSA demonstrated superior Top-1 annotation accuracy compared to established tools like SIRIUS, MS-FINDER, and MetFrag.
• Application of CNPs-MFSA to 56 Thymelaeaceae plants identified 204 high-confidence daphnanes, including 105 novel compounds, from 822 annotated results.
• The workflow was extended to illustrate the annotation of other CNP classes, such as aconitine, paclitaxel, and obakunone analogs.

Conclusions:

• The modular fragmentation-based structural assembly (MFSA) strategy provides a robust and accurate approach for complex natural product structural annotation.
• The CNPs-MFSA tool offers a user-friendly and effective solution for researchers in natural product chemistry and drug discovery.
• This approach significantly advances the identification of novel bioactive compounds from natural sources, particularly within the Thymelaeaceae family.