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

Complex natural products (CNPs) feature polycyclic structures, multiple consecutive chiral centers, and nonrepetitive structural units. Given their complexity, the structural annotation of CNPs remains a major bottleneck. Here, we introduce the modular fragmentation-based structural assembly (MFSA) strategy for the target CNP structural annotation. The MFSA strategy disassembled the structure based on fragmentation patterns, recognized targets via a pseudo-library, and reassembled the structure using characteristic ions and neutral losses. As a proof of concept, we focused on daphnane-type diterpenoids, a kind of specific bioactive CNP from Thymelaeaceae plants. Furthermore, we present a user-friendly application named CNPs-MFSA coded in Python. Using an in-house daphnane library, CNPs-MFSA outperformed SIRIUS, MS-FINDER, and MetFrag in Top-1 annotation accuracy. By applying CNPs-MFSA to 56 Thymelaeaceae plants, 204 high-confidence daphnanes within 822 annotated results, including 105 previously unreported compounds were found. Aconitine, paclitaxel, and obakunone analogs were incorporated as additional target CNP classes to illustrate the extension workflow.