bioRxiv · 10.64898/2026.08.16.745124
TRACER navigates rearrangement-driven sesterterpene chemical space via multimodal enzyme-product representation learning
Abstract
Skeletal rearrangement drives the immense structural complexity of terpene, yet predicting it remains a formidable challenge due to sequence-function decoupling in terpene synthases. Here, we established TRACER (terpene rearrangement annotation via co-attentive enzyme-product representation), a multimodal framework mapping the latent associations between sequence-derived enzyme representations and product chemotypes. Retrospective validation proved TRACERs exceptional precision in predicting compound classes and discriminating skeletal rearrangement (SR) from non-skeletal rearrangement (NSR) pathways. TRACER-guided genome mining characterized two bifunctional synthases, FsPS and AcPS, uncovering four unprecedented carbon skeletons. Density functional theory calculations deciphered these cyclization cascades, pinpointing a critical 5/6/11 tricyclic intermediate as the key branching node for scaffold diversification. Mutagenesis and molecular dynamics simulations suggested that E305 in FsPS enables rearrangement by maintaining active-site water exclusion, whereas its alanine mutation causes premature carbocation quenching. Collectively, this work establishes a predictive paradigm for the rational discovery and mechanistic elucidation of complex terpene architectures.
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Xing, C., Lv, K., Zhang, W., Chen, Y., Lan, K., Zhu, G., Zhu, B., Shen, S.-M., Zhang, X., Gu, Y., Guo, Y.-W., Oikawa, H., Hsiang, T., Zhang, L., Li, Y., Jiang, L., Liu, X.. 2026-08-19. TRACER navigates rearrangement-driven sesterterpene chemical space via multimodal enzyme-product representation learning. https://doi.org/10.64898/2026.08.16.745124
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