Short total syntheses of the avenaciolide family of natural products

Ferrocene-Mediated Electrochemical Polycyclization of Malonates

We report access to the core of biologically relevant aromatic abietane diterpenoids and to the formal synthesis of podocarpic and lambertic acids or γ-lactones via an electrochemical bicyclization process initiated by the ferrocene-mediated anodic oxidation of a malonate via single electron-transfer. This approach permits escaping the use of excess of oxidants such as Mn(OAc)3 and the associated complicated purification.

Recent Advances in Manganese(III)-Assisted Radical Cyclization for the Synthesis of Natural Products: A Comprehensive Review

Natural products play an important part in synthetic chemistry since they have many pharmacological properties and are used as active drug compounds in pharmaceutical chemistry. However, synthesis of these complex molecules is difficult due to the requirement of various synthetic steps, which include highly regio- and stereoselectivity. Therefore, oxidative radical cyclization assisted by manganese(III) acetate serves as an important step in obtaining spiro-, tricyclic, tetracyclic, and polycyclic derivatives of these compounds. Manganese(III)-based reactions offer a single-step regio- and stereoselective cyclizations and α-acetoxidations, reducing the number of synthetic steps. Also, the manganese(III)-mediated oxidative free radical cyclization method has been successfully applied for the synthesis of cyclic structures found in many natural products. This article presents a broad overview of manganese(III)-based radical reactions of natural products as a key step in overall synthesis. The authors have classified natural product synthesis processes assisted by manganese(III) acetate as intermolecular, intramolecular, oxidation, acetoxidation, aromatization, and polymerization reactions, respectively.

Synthesis of α-exo-Methylene-γ-butyrolactones: Recent Developments and Applications in Natural Product Synthesis

The α-exo-methylene-γ-butyrolactone moiety is present in a vast array of structurally diverse natural products and is often central to their biological activity. In this short review, we summarize new approaches to α-exo-methylene-γ-butyrolactones developed over the past decade as well as their applications in total synthesis.

1 Introduction

2 Approaches to α-exo-Methylene-γ-butyrolactones

2.1 Enantioselective Synthesis via Lactonization Approaches

2.2 Enantioselective Halolactonizations

2.3 Enantioselective Barbier-Type Allylation

2.4 C–H Insertion/Olefination Sequences

2.5 Alkene Cyclization

2.6 Strain-Driven Dyotropic Rearrangement

3 β-(Hydroxymethylalkyl)-α-exo-methylene-γ-butyrolactones

4 Applications in Total Synthesis

4.1 Sesquiterpene Lactones

4.2 Lignans

4.3 Other Monocyclic Natural Products

4.4 Choice of Methodology in Recent Total Syntheses

5 Summary and Outlook

New compounds from Japanese oak wilt disease-associated fungus Raffaelea quercivora

Two new compounds, a new lactone, quercilactone A (1), and (17R)-hydroxynafuredin (5), as well as five known compounds, scytalone (2), 3S,4R-hydoxy-scytalone (3), nafuredin (4), (+)-(3R,5R)-3-hydroxy-5-decanolide (6) and 3-ethyl-4-hydroxy-6-methyl-2H-pyran-2-one (7), were isolated from Raffaelea quercivora, a fungus that causes Japanese oak wilt disease. The structures of these compounds were determined by 1D and 2D NMR spectroscopic analyses. The absolute configuration at C-17 of 5 was determined to be R by the modified Mosher's method. Compounds 1, 2, and 7 exhibited weak phytotoxic activity in lettuce seedlings at a concentration of 100 μg mL^-1.

DP4-AI automated NMR data analysis: straight from spectrometer to structure

A robust system for automatic processing and assignment of raw 13C and 1H NMR data DP4-AI has been developed and integrated into our computational organic molecule structure elucidation workflow. Starting from a molecular structure with undefined stereochemistry or other structural uncertainty, this system allows for completely automated structure elucidation. Methods for NMR peak picking using objective model selection and algorithms for matching the calculated 13C and 1H NMR shifts to peaks in noisy experimental NMR data were developed. DP4-AI achieved a 60-fold increase in processing speed, and near-elimination of the need for scientist time, when rigorously evaluated using a challenging test set of molecules. DP4-AI represents a leap forward in NMR structure elucidation and a step-change in the functionality of DP4. It enables high-throughput analyses of databases and large sets of molecules, which were previously impossible, and paves the way for the discovery of new structural information through machine learning. This new functionality has been coupled with an intuitive GUI and is available as open-source software at https://github.com/KristapsE/DP4-AI.