Computation helps chemists shorten synthesis of natural product

Computational analysis has helped chemists achieve concise total syntheses of two terpene natural products, according to a new study.

Led by Yale University’s Timothy Newhouse, the team reports a nine-step route to paspaline A, a dense hexacyclic molecule with anticancer properties that was previously made in 25 and 27 steps. The researchers also disclose the first synthesis of the related compound emindole PB in 13 steps, confirming its structure (ChemRxiv 2018, DOI: 10.26434/chemrxiv.7322330.v1). These shortened routes could provide faster access to biologically useful analogs.

In planning the syntheses, the chemists took a cue from how nature builds the molecules, focusing on the key biosynthetic step that fungi use when making each molecule: an indole cyclization for paspaline A and a methyl shift for emindole PB. The team identified three possible precursors that could access both steps. Using a computational method called density functional theory (DFT), the team modeled the energetics of reactions with each precursor to evaluate which one had the highest likelihood of success. They then designed a synthetic route that proceeded through that intermediate.

While other groups have used computation to identify possible bond-making steps in a synthesis or to rationalize why a synthesis worked after completion, Newhouse says, their team took the less explored strategy of using computation to evaluate variations on a single synthetic step.

Study coauthor and graduate student Daria E. Kim says they’ve made hundreds of milligrams of paspaline A and about 10 g of the key intermediate using the new route.

The ability to prioritize a synthetic route based on DFT analysis is exciting, says University of North Carolina, Chapel Hill’s Jeffrey Johnson, whose lab reported a 27-step synthesis of paspaline A in 2015. Calculations provide chemists planning synthetic routes with valuable data that are relatively easy to obtain, he says. The strategy may be less applicable, however, in cases when a team is unsure about the mechanism of the key step.

Natural products expert Dattatraya H. Dethe at the Indian Institute of Technology says this computational approach could shorten synthetic routes to natural products and also raise the overall rate of success.