分子模拟在环糊精包合反应中的应用研究进展

Recent Advances in the Application of Molecular Simulation in Research on Cyclodextrin Inclusion

环糊精可作为主体通过超分子相互作用与客体分子形成包合物,从而起到保护或增强客体分子性质的作用。分子模拟是探究该相互作用的一种重要研究手段,在环糊精包合反应中得到了广泛的应用。本文首先对分子模拟进行概述,主要包括量子力学、分子对接和分子动力学模拟;其次,分别总结了分子对接和分子动力学模拟的基本原理、主流软件及常用力场等,之后分别从分子结构变化表征、分子间相互作用表征、溶剂效应及协同稳定4个方面总结了其在研究环糊精包合过程中的应用进展;研究表明,疏水空腔的大小及客体在空腔内的初始方向对客体/环糊精包合物结构都有非常重要的影响;范德华相互作用是环糊精包合反应的主要推动力,分子间氢键的形成是包合物稳定的重要因素;显式溶剂模型是研究环糊精包合反应溶剂效应的有利工具;最后,作者认为对于环糊精包合过程,可从多尺度及机器学习两方面,结合分子模拟进行后续相关研究。

Cyclodextrin(CD)can form inclusion complexes with the guest molecule through supramolecular interaction,preserving or even enhancing the properties of the guest molecule.Molecular simulation is an important research tool to explore the interaction of CD with the guest molecule,which has been widely used in research on cyclodextrin inclusion reaction.In this paper,a brief overview of molecular simulations including quantum mechanics,molecular docking and molecular dynamics simulation was given,and the basic principles of and mainstream software and commonly used force fields for molecular docking and molecular dynamic simulation were summarized.Moreover,recent progresses on their application in cyclodextrin inclusion research were reviewed from four aspects:characterization of molecular structure changes,characterization of intermolecular interaction,solvent effects and synergistic stabilization.Research results show that the size of the hydrophobic cavity and the initial orientation of the guest within the cavity have very important effects on the structure of guest/cyclodextrin inclusion complexes;van der Waals interactions are the major driving force for the cyclodextrin inclusion reaction,and the formation of intermolecular hydrogen bonds is an important factor for the stability of the inclusion complex.The explicit solvent model is a powerful tool to study the solvent effect of the cyclodextrin inclusion reaction.Finally,the authors believe that molecular simulation will be useful for further investigations of the cyclodextrin inclusion process from the perspectives of multi-scale phenomena and machine learning.