Synthesis of trans -β-Elemene

Artificial Intelligence for Retrosynthetic Planning Needs Both Data and Expert Knowledge

Rapid advancements in artificial intelligence (AI) have enabled breakthroughs across many scientific disciplines. In organic chemistry, the challenge of planning complex multistep chemical syntheses should conceptually be well-suited for AI. Yet, the development of AI synthesis planners trained solely on reaction-example-data has stagnated and is not on par with the performance of "hybrid" algorithms combining AI with expert knowledge. This Perspective examines possible causes of these shortcomings, extending beyond the established reasoning of insufficient quantities of reaction data. Drawing attention to the intricacies and data biases that are specific to the domain of synthetic chemistry, we advocate augmenting the unique capabilities of AI with the knowledge base and the reasoning strategies of domain experts. By actively involving synthetic chemists, who are the end users of any synthesis planning software, into the development process, we envision to bridge the gap between computer algorithms and the intricate nature of chemical synthesis.

Engineering Escherichia coli BL21 (DE3) for high-yield production of germacrene A, a precursor of β-elemene via combinatorial metabolic engineering strategies

β-elemene is one of the most commonly used antineoplastic drugs in cancer treatment. As a plant-derived natural chemical, biologically engineering microorganisms to produce germacrene A to be converted to β-elemene harbors great expectations since chemical synthesis and plant isolation methods come with their production deficiencies. In this study, we report the design of an Escherichia coli cell factory for the de novo production of germacrene A to be converted to β-elemene from a simple carbon source. A series of systematic approaches of engineering the isoprenoid and central carbon pathways, translational and protein engineering of the sesquiterpene synthase, and exporter engineering yielded high-efficient β-elemene production. Specifically, deleting competing pathways in the central carbon pathway ensured the availability of acetyl-coA, pyruvate, and glyceraldehyde-3-phosphate for the isoprenoid pathways. Adopting lycopene color as a high throughput screening method, an optimized NSY305N was obtained via error-prone polymerase chain reaction mutagenesis. Further overexpression of key pathway enzymes, exporter genes, and translational engineering produced 1161.09 mg/L of β-elemene in a shake flask. Finally, we detected the highest reported titer of 3.52 g/L of β-elemene and 2.13 g/L germacrene A produced by an E. coli cell factory in a 4-L fed-batch fermentation. The systematic engineering reported here generally applies to microbial production of a broader range of chemicals. This illustrates that rewiring E. coli central metabolism is viable for producing acetyl-coA-derived and pyruvate-derived molecules cost-effectively.

Asymmetric total synthesis of (1S,2S,4S)-β-elemene

Elemenes are sesquiterpene natural products extracted from Chinese medicinal herbs and have been used as an important antitumor drug in China. Here, we report the first stereoselective total synthesis of (1S,2S,4S)-β-elemene using (R)-carvone as a chiral pool starting material. The isopropenyl moiety was achieved in a highly stereoselective manner through 1,4-Michael conjugate addition. The following transformations like regio- and stereoselective aldol condensation, Wittig olefination have been employed as the key steps, resulting in a concise total synthesis of (1S,2S,4S)-β-elemene. Our accomplishment will allow further biological investigations of this natural product and open opportunities for developing a new potentially promising antitumor drug.

The first asymmetric total synthesis of (1S,2S,4S)-β-elemene was accomplished in five steps or eight steps by using the chiral pool strategy.