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Dynamic Strategic Bond Analysis Yields a Ten-Step Synthesis of 20-nor-Salvinorin A, a Potent κ-OR Agonist.

Jeremy J Roach, Yusuke Sasano, Cullen L Schmid, Saheem Zaidi, Vsevolod Katritch, Raymond C Stevens, Laura M Bohn, Ryan A Shenvi

ACS central science December 27, 2017 DOI: 10.1021/acscentsci.7b00488 via PubMed

Summary

AI-generated from the abstract

Deleting a single carbon atom (C20) from the complex plant metabolite salvinorin A stabilizes its molecular skeleton, simplifies its laboratory synthesis to just 10 steps, and preserves its high affinity and selectivity for the human kappa-opioid receptor. The work also introduces a general workflow for identifying structural changes that keep molecular complexity high while reducing synthetic complexity.

Study at a glance

Characteristics Theoretical or methodological paper Peer reviewed
Key finding Deletion of C20 from salvinorin A stabilizes the skeleton, simplifies synthesis to 10 steps, and retains high affinity and selectivity for the kappa-opioid receptor.

Abstract

Salvinorin A (SalA) is a plant metabolite that agonizes the human kappa-opioid receptor (κ-OR) with high affinity and high selectivity over mu- and delta-opioid receptors. Its therapeutic potential has stimulated extensive semisynthetic studies and total synthesis campaigns. However, structural modification of SalA has been complicated by its instability, and efficient total synthesis has been frustrated by its dense, complex architecture. Treatment of strategic bonds in SalA as dynamic and dependent on structural perturbation enabled the identification of an efficient retrosynthetic pathway. Here we show that deletion of C20 simultaneously stabilizes the SalA skeleton, simplifies its synthesis, and retains its high affinity and selectivity for the κ-OR. The resulting 10-step synthesis now opens the SalA scaffold to deep-seated property modification. Finally, we describe a workflow to identify structural changes that retain molecular complexity, but reduce synthetic complexity-two related, but independent ways of looking at complexity.

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