Secondary metabolite design and synthesis
次级代谢产物设计和合成

Project Profile 项目简介

AI-driven protein–metabolite interaction analysis, protein complex identification, and compound retro-biosynthesis are employed to elucidate complex natural product biosynthetic pathways. Artificial multi-enzyme complexes are constructed to achieve substrate compartmentalization, enabling efficient synthesis of natural products (Qin et al., 2025, Cell Reports; Fernie et al., 2024, Nature Plants; Liu et al., 2024, Molecular Plant).

基于AI驱动的蛋白代谢物互作，蛋白复合体鉴定，以及化合物生物逆合成，鉴定复杂天然产物合成途径。构建人工多酶复合体实现底物区室化，实现高效天然产物的合成 （Qin et al., 2025, Cell Reprots; Fernie et al., 2024, Nature Plants; Liu et al, 2024, Molecualar Plant）。

代表性成果

1. Qin K., Liu F., Zhang C., Deng R., Fernie A. R. & Zhang Y. (2025). Systems and Synthetic Biology for Plant Natural Product Pathway Elucidation. Cell reports, 44(6): 115715.
2. Fernie A. R., Liu F., & Zhang Y. (2024). Post-genomic Illumination of Paclitaxel Biosynthesis. Nature Plants, 10(12), 1875-1885.
3. Liu F., Fernie A. R., & Zhang Y. (2024). Plant Gene Co-expression Defines the Biosynthetic Pathway of Neuroactive Alkaloids. Molecular Plant, 17(3), 372-374.

Project Figure 项目图