Unknown

Dataset Information

Quantum Descriptors for Predicting and Understanding the Structure-Activity Relationships of Michael Acceptor Warheads.


ABSTRACT: Predictive modeling and understanding of chemical warhead reactivities have the potential to accelerate targeted covalent drug discovery. Recently, the carbanion formation free energies as well as other ground-state electronic properties from density functional theory (DFT) calculations have been proposed as predictors of glutathione reactivities of Michael acceptors; however, no clear consensus exists. By profiling the thiol-Michael reactions of a diverse set of singly- and doubly-activated olefins, including several model warheads related to afatinib, here we reexamined the question of whether low-cost electronic properties can be used as predictors of reaction barriers. The electronic properties related to the carbanion intermediate were found to be strong predictors, e.g., the change i

SUBMITTER: Liu R 

PROVIDER: S-EPMC10837637 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature