This review aims to highlight the role that computational chemistry has played in advancing the supramolecular chemistry field. We demonstrated recent uses of computational methodologies to elucidate noncovalent interactions in various processes occurring in supramolecular systems. We also emphasized the contributions of these techniques to studying reactions within confined space, showing how computational methodologies help clarify the effects of reactivity and conformational locking. Furthermore, we underscore the utilization of Molecular Dynamics (MD) in elucidating dynamical processes, understanding temperature and pressure effects, and exploring conformational space within supramolecular chemistry. Finally, we highlight the impact that the age of machine learning has on computational chemistry, showing how these universal approximators can enhance existing methods, predict properties, and efficiently explore the chemical space encompassed by these complex systems.

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超分子化学：探索电子结构、分子动力学和机器学习方法的使用

本综述旨在强调计算化学在推进超分子化学领域所发挥的作用。我们展示了最近使用计算方法来阐明超分子系统中发生的各种过程中的非共价相互作用。我们还强调了这些技术对研究有限空间内的反应的贡献，展示了计算方法如何帮助阐明反应性和构象锁定的影响。此外，我们强调分子动力学（MD）在阐明动力学过程、理解温度和压力效应以及探索超分子化学中的构象空间方面的应用。最后，我们强调机器学习时代对计算化学的影响，展示这些通用逼近器如何增强现有方法、预测特性并有效探索这些复杂系统所包含的化学空间。