Computational prediction of complex cationic rearrangement outcomes.

ABSTRACT: Recent years have seen revived interest in computer-assisted organic synthesis^1,2. The use of reaction- and neural-network algorithms that can plan multistep synthetic pathways have revolutionized this field^1,3-7, including examples leading to advanced natural products^6,7. Such methods typically operate on full, literature-derived 'substrate(s)-to-product' reaction rules and cannot be easily extended to the analysis of reaction mechanisms. Here we show that computers equipped with a comprehensive knowledge-base of mechanistic steps augmented by physical-organic chemistry rules, as well as quantum mechanical and kinetic calculations, can use a reaction-network approach to analyse the mechanisms of some of the most complex organic transformations: namely, cat

SUBMITTER: Klucznik T 

PROVIDER: S-EPMC10864989 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature