The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user-friendly toolkit, BioNavi-NP, is developed to predict the biosynthetic pathways for both NPs and NP-like compounds. First, a single-step bio-retrosynthesis prediction model is trained using both general organic and biosynthetic reactions through end-to-end transformer neural networks. Based on this model, plausible biosynthetic pathways can be efficiently sampled through an AND-OR tree-based planning algorithm from iterative multi-step bio-retrosynthetic routes. Extensive evaluations reveal that BioNavi-NP can identify biosynthetic pathways for 90.2% of 368 test compounds and recover the reported building blocks as in the test set for 72.8%, 1.7 times more accurate than existing conventional rule-based approaches. The model is further shown to identify biologically plausible pathways for complex NPs collected from the recent literature. The toolkit as well as the curated datasets and learned models are freely available to facilitate the elucidation and reconstruction of the biosynthetic pathways for NPs.

Natural products are the major resource of drug discovery, and terpenoids represent the largest family of natural products. Terpenome is defined as all terpenoid-like and terpenoidderived natural compounds, including the terpenoids, steroids, and their derivatives. Herein, aiming to navigate the chemical and biological space of terpenome, the first comprehensive database dedicated to terpenome research has been developed by collecting over 110 000 terpenome molecules from various resources, distributed in 14 351 species, belonging to 1109 families, and showing activity against 1366 biological targets. Much of the publically available information or computationally predicted properties for each terpenome molecule is annotated and integrated into TeroKit (http://terokit.qmclab.com/), serving as free Web server for academic use. Moreover, several practical toolkits, such as target profiling and conformer generation modules, are also implemented to facilitate the drug discovery of terpenome.

Enzymatic plasticity, as a modern term referring to the functional conversion of an enzyme, is significant for enzymatic activity redesign. The bacterial diterpene cyclase CotB2 is a typical plastic enzyme by which its native form precisely conducts a chemical reaction while its mutants diversify the catalytic functions drastically. Many efforts have been made to disclose the mysteries of CotB2 enzyme catalysis. However, the catalytic details and regulatory mechanism toward the precise chemo- and stereoselectivity are still elusive. In this work, multiscale simulations are employed to illuminate the biocyclization mechanisms of the linear substrate into the final product cyclooctat-9-en-7-ol with a 5–8–5 fused ring scaffold, and the derailment products arising from the premature quenching of reactive carbocation intermediates are also discussed. The two major regulatory factors, local electrostatic stabilization effects from aromatic residues or polar residue in pocket and global features of active site including pocket-contour and pocket-hydrophobicity, are responsible for the enzymatic plasticity of CotB2. Further comparative studies of representative Euphorbiaceae and fungal diterpene cyclase (RcCS and PaFS) show a correlation between pocket plasticity and product diversity, which inspires a tentative enzyme product prediction and the rational diterpene cyclases’ reengineering in the future.

Terpenoids represent the largest family of natural products (NPs) with dramatically chemical and structural diversity, which makes terpenoids the important compound resources of drug discovery. However, comprehensive understanding on the structure− function features for terpenoid NPs is limited. In this work, we have systematically explored the chemical and biological space of terpenoid NPs, including their distribution, physicochemical properties, scaffold features, and functional applications, by utilizing various cheminformatics and bioinformatics approaches. We have not only confirmed that terpenoid NPs have good drug-likeness and great potential for drug discovery but, more importantly, illuminated the uniqueness of cyclic scaffold diversity in different species (plants, fungi, bacteria, and animals) and the specificity of biological function for the dominant fused-ring scaffolds of terpenoids. The present work supplies a valuable reference for identifying the new structure and unknown function of terpenoid NPs.

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