背景:计算机硬件和软件功能的创新为分子建模技术和方法的进步铺平了道路,导致其潜在应用的空前扩展。与对接技术相比,通常为每个对映异构体鉴定最稳定的选择-选择和(SO-SA)复合物,分子动力学(MD)技术可以根据SO-SA复合物的能量分布来考虑它们的分布。这种方法提供了在列中发生的过程的更真实的表示。然而,在分子水平上计算对映选择性的基准程序和重点指南仍然缺失。
结果:进行了28个分子动力学模拟,以研究7种N-3,5-二硝基苯甲酰化α-和β-氨基酸(DNB-AA)的对映识别机制,发生在两个基于奎尼和奎尼丁的(QN-AX和QD-AX)手性固定相(CSP)上,在极性离子条件下。MD协议在盒子尺寸方面进行了优化,模拟运行时间,和帧记录频率。随后,所有的轨迹都是通过计算的类型和数量参与的选择和(SA)与两个手性选择器(SO)的相互作用进行分析,以及形成的SA-SO缔合物的构象和相互作用能谱。所有MD都与实验对映体洗脱顺序严格一致,并允许建立(i)盐桥和H键相互作用在对映体识别机制中起关键作用,和(ii)π-阳离子和π-π相互作用是两个SO之间在决定手性识别机制方面的判别化学特征。
结论:这项工作的结果清楚地表明,MD模拟在理解基于金鸡纳生物碱的CSP的对映识别机制方面具有很高的贡献。然而,从这项研究中可以明显看出,MD方案的优化对于所产生结果的质量至关重要.
BACKGROUND: Innovations in computer hardware and software capabilities have paved the way for advances in molecular modelling techniques and methods, leading to an unprecedented expansion of their potential applications. In contrast to the docking technique, which usually identifies the most stable selector-selectand (SO-SA) complex for each enantiomer, the molecular dynamics (MD) technique enables the consideration of a distribution of the SO-SA complexes based on their energy profile. This approach provides a more truthful representation of the processes occurring within the column. However, benchmark procedures and focused guidelines for computational treatment of enantioselectivity at the molecular level are still missing.
RESULTS: Twenty-eight molecular dynamics simulations were performed to study the enantiorecognition mechanisms of seven N-3,5-dinitrobenzoylated α- and β-amino acids (DNB-AAs), occurring with the two quinine- and quinidine-based (QN-AX and QD-AX) chiral stationary phases (CSPs), under polar-ionic conditions. The MD protocol was optimized in terms of box size, simulation run time, and frame recording frequency. Subsequently, all the trajectories were analyzed by calculating both the type and amount of the interactions engaged by the selectands (SAs) with the two chiral selectors (SOs), as well as the conformational and interaction energy profiles of the formed SA-SO associates. All the MDs were in strict agreement with the experimental enantiomeric elution order and allowed to establish (i) that salt-bridge and H-bond interactions play a pivotal role in the enantiorecognition mechanisms, and (ii) that the π-cation and π-π interactions are the discriminant chemical features between the two SOs in ruling the chiral recognition mechanism.
CONCLUSIONS: The results of this work clearly demonstrate the high contribution given by MD simulations in the comprehension of the enantiorecognition mechanism with Cinchona alkaloid-based CSPs. However, from this research endeavor it clearly emerged that the MD protocol optimization is crucial for the quality of the produced results.