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Synthesizing Natural Products With a Computational Step Saver


Subtle differences in calculated energy landscapes impact synthetic planning.

Researchers at Yale University have slashed the number of steps needed to synthesize two natural anticancer products, using a novel approach to computational analysis in organic chemistry.

Credit: Joshua Zweig

Yale University researchers have reduced the number of steps needed to synthesize two natural anticancer products, using a unique strategy for computational analysis in organic chemistry.

Yale's Timothy Newhouse, Daria Kim, and Joshua Zweig employed density functional theory (DFT) calculations to assess and prioritize seemingly equivalent chemical pathways to plan synthesis.

DFT examines a material's structural, magnetic, and electronic properties to perform computational quantum-mechanical modeling.

The researchers used DFT to synthesize the molecule paspaline A in only nine steps, versus 25 to 27 steps that earlier work required; they also achieved a 13-step path to synthesize the previously unsynthesized emindole PB compound.

Kim said, "A more efficient synthesis allows for the production of a greater amount of material, and also a laboratory process that can more easily be used to produce synthetic analogs."

From YaleNews
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