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

碳负离子 化学 电泳剂 位阻效应 计算化学 亲电取代 迈克尔反应 立体化学 有机化学 催化作用
作者
Ruibin Liu,Erik Antonio Vázquez-Montelongo,Shuhua Ma,Jana Shen
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:63 (15): 4912-4923 被引量:14
标识
DOI:10.1021/acs.jcim.3c00720
摘要

Predictive modeling and understanding 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 the den- sity 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 in the Cβ charge accompanying carbanion formation. The least expensive reactant-only properties, the electrophilicity index and the Cβ charge also show strong rank correlations, suggesting their utility as quantum descriptors. A second objective of the work is to clarify the effect of the β-dimethylaminomethyl (DMAM) substitution which is incorporated in the warheads of several FDA-approved covalent drugs. Our data suggests that the beta-DMAM substitution is cationic at neutral pH in solution and it promotes acrylamide’s intrinsic reactivity by enhancing the charge accumulation at Calpha upon carbanion formation. In contrast, the inductive effect of the beta-trimethylaminomethyl substitution is diminished due to steric hindrance. Together, these results reconcile the current views of the intrinsic reactivities of acrylamides and contribute to large-scale predictive modeling and understanding of the structure-activity relationships of Michael acceptors for rational TCI design.
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