Year: 2024
Type: article
Abstract: This work describes estimation of yields of complex, multicomponent reactions (MCRs) based on the modeled networks of mechanistic steps spanning both the main reaction pathway as well as immediate and downstream side reactions. Because experimental values of the kinetic rate constants for individual mechanistic transforms are extremely sparse, these constants are approximated here using Mayr’s nucleophilicity and electrophilicity parameters fine-tuned by correction terms grounded in linear free-energy relationships. With this formalism, the model trained on the mechanistic networks of only 20 – but mechanistically- and yield-diverse MCRs – transfers well to newly discovered MCRs that are based on markedly different mechanisms and types of individual mechanistic transforms. These results suggest that mechanistic-level approach to yield estimation may be a useful alternative to models that are derived from full-reaction data and lack information about yield-lowering side reactions. The ability to predict the yields of organic reactions is of tremendous value for synthetic chemistry, limiting the number of unproductive experiments. Here, the authors describe estimation of yields of complex, multicomponent reactions (MCRs) based on the modeled networks of mechanistic steps spanning both the main reaction pathway as well as immediate and downstream side reactions.
Source: Nature Communications
Language: English
Topic: Chemical Reaction Mechanisms
Subfield: Organic Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,790
Funder: Institute for Basic Science
Awards: G1042849371, G1209599001, G8524864788
OpenAlex ID: W4404759629
