Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS, 4 Place Jussieu, 75005, Paris, France.
Qubit Pharmaceuticals, Incubateur Paris Biotech Santé, 24 rue du Faubourg Saint Jacques, 75014, Paris, France.
Chemphyschem. 2022 Sep 16;23(18):e202200349. doi: 10.1002/cphc.202200349. Epub 2022 Jul 8.
Modeling chemical reactions using Quantum Chemistry is a widely used predictive strategy capable to complement experiments in order to understand the intrinsic mechanisms guiding the chemicals towards the most favorable reaction products. However, at this purpose, it is mandatory to use reliable and computationally tractable theoretical methods. In this work, we focus on six Diels-Alder reactions of increasing complexity and perform an extensive benchmark of middle- to low-cost computational approaches to predict the characteristic reactions energy barriers. We found that Density Functional Theory, using the ωB97XD, LC-ωPBE, CAM-B3LYP, M11 and MN12SX functionals, with empirical dispersion corrections coupled to an affordable 6-31G basis set, provides quality results for this class of reactions, at a small computational effort. Such efficient and reliable simulation protocol opens perspectives for hybrid QM/MM molecular dynamics simulations of Diels-Alder reactions including explicit solvation.
使用量子化学模拟化学反应是一种广泛应用的预测策略,能够补充实验以理解指导化学反应生成最有利产物的内在机制。然而,为此目的,必须使用可靠且计算上易于处理的理论方法。在这项工作中,我们专注于六个具有递增复杂性的 Diels-Alder 反应,并对中低计算成本的计算方法进行了广泛的基准测试,以预测特征反应能垒。我们发现,使用 ωB97XD、LC-ωPBE、CAM-B3LYP、M11 和 MN12SX 函数,加上经验色散校正并耦合一个负担得起的 6-31G 基组的密度泛函理论,为这一类反应提供了高质量的结果,计算工作量小。这种高效可靠的模拟方案为包括显式溶剂化在内的 Diels-Alder 反应的QM/MM 分子动力学模拟开辟了前景。