News Picture Generic

Catalyst for Efficient Cleavage of Allyloxy Bonds

August 19, 2015

Nagoya, Japan 2014 Tetrahedron Prize for Creativity in Organic Chemistry, Palladium and Other Transition Metal-Catalyzed Reactions: Invention and Applications Soft ruthenium and hard Brønsted acid combined catalyst for efficient cleavage of allyloxy bonds. Application to protecting group chemistry with Chemspeed’s Fully Automated SYNTHESIZER “We show that a monocationic CpRu(II) complex of quinaldic acid (QAH) and a monocationic CpRu(IV)(p-allyl)QA complex catalyze efficient cleavage of the allyloxy bond in allyl ethers, allyl esters, allyl carbonates, and allyl carbamates in methanol without the need for additional nucleophiles. The only co-product is volatile allyl methyl ether, enhancing operational simplicity during isolation of the de-protected alcohols, acids, and amines. This clean and high-performance catalytic system should contribute to protecting group chemistry during the multistep synthesis of pharmaceutically important natural products. Full details of this system, including the mechanism, are reported.” For details: Soft ruthenium and hard Brønsted acid combined catalyst for efficient cleavage of allyloxy bonds. Application to protecting group chemistry Shinji Tanaka, Yusuke Suzuki, Hajime Saburi, Masato Kitamura Nagoya University, Graduate School of Pharmaceutical Sciences, Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan Tetrahedron, Volume 71, Issue 37, 16 September 2015, Pages 6559–6568 DOI:10.1016/j.tet.2015.04.088

Other Recent News

Discover more news articles you might be interested in

Read more about Asymmetric hydrogenation of olefins with transition metal-based catalysts: practical insights from screening to production of APIs
News Picture 1 1 V2
Featured
Jan
20

Asymmetric hydrogenation of olefins with transition metal-based catalysts: practical insights from screening to production of APIs

Selective hydrogenation plays a critical role in modern synthetic chemistry, particularly in the pharmaceutical industry, where the production of chiral molecules with high enantiomeric purity is essential for the efficacy and safety of active pharmaceutical ingredients (APIs). 

Read more about Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography
News Picture 1 1 V2
Featured
Jan
6

Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography

The integration of automated synthesis and machine learning (ML) is transforming analytical chemistry by enabling data-driven approaches to method development. Chromatographic column selection, a critical yet time-consuming step in separation science, stands to benefit substantially from such advances.

© Chemspeed Technologies 2026