期刊
JOURNAL OF CHEMICAL INFORMATION AND MODELING
卷 63, 期 15, 页码 4912-4923出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.3c00720
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The electronic properties related to the carbanion intermediate were found to be strong predictors of glutathione reactivities of Michael acceptors. The & beta;-DMAM substitution was found to be cationic and enhance the charge accumulation at C-& alpha; upon carbanion formation.
Predictive modeling and understanding of chemical warheadreactivitieshave the potential to accelerate targeted covalent drug discovery.Recently, the carbanion formation free energies as well as other ground-stateelectronic properties from density functional theory (DFT) calculationshave been proposed as predictors of glutathione reactivities of Michaelacceptors; however, no clear consensus exists. By profiling the thiol-Michaelreactions of a diverse set of singly- and doubly-activated olefins,including several model warheads related to afatinib, here we reexaminedthe question of whether low-cost electronic properties can be usedas predictors of reaction barriers. The electronic properties relatedto the carbanion intermediate were found to be strong predictors,e.g., the change in the C-& beta; charge accompanying carbanionformation. The least expensive reactant-only properties, the electrophilicityindex, and the C-& beta; charge also show strong rank correlations,suggesting their utility as quantum descriptors. A second objectiveof the work is to clarify the effect of the & beta;-dimethylaminomethyl(DMAM) substitution, which is incorporated in the warheads of severalFDA-approved covalent drugs. Our data suggest that the & beta;-DMAMsubstitution is cationic at neutral pH in solution and promotes acrylamide'sintrinsic reactivity by enhancing the charge accumulation at C-& alpha; upon carbanion formation. In contrast, the inductiveeffect of the & beta;-trimethylaminomethyl substitution is diminisheddue to steric hindrance. Together, these results reconcile the currentviews of the intrinsic reactivities of acrylamides and contributeto large-scale predictive modeling and an understanding of the structure-activityrelationships of Michael acceptors for rational TCI design.
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