D'Alessando Maira, Amadei Andrea, Stener Mauro, Aschi Massimiliano
Dipartimento di Scienze Fisiche e Chimiche, Universita' di l'Aquila, Via Vetoio s.n.c., 67100 l, 'Aquila, Italy.
J Comput Chem. 2015 Mar 5;36(6):399-407. doi: 10.1002/jcc.23814. Epub 2014 Dec 24.
Essential Dynamics (ED) is a powerful tool for analyzing molecular dynamics (MD) simulations and it is widely adopted for conformational analysis of large molecular systems such as, for example, proteins and nucleic acids. In this study, we extend the use of ED to the study of clusters of arbitrary size constituted by weakly interacting particles, for example, atomic clusters and supramolecular systems. The key feature of the method we present is the identification of the relevant atomic-molecular clusters to be analyzed by ED for extracting the information of interest. The application of this computational approach allows a straightforward and unbiased conformational study of the local microstructures in liquids, as emerged from semiclassical MD simulations. The good performance of the method is demonstrated by calculating typical observables of liquid water, that is, NMR, NEXAFS O1s, and IR spectra, known to be rather sensitive both to the presence and to the conformational features of hydrogen-bonded clusters.
主成分动力学（ED）是一种用于分析分子动力学（MD）模拟的强大工具，它被广泛应用于蛋白质和核酸等大分子系统的构象分析。在本研究中，我们将ED的应用扩展到由弱相互作用粒子构成的任意大小的团簇研究中，例如原子团簇和超分子系统。我们提出的方法的关键特征是识别由ED分析的相关原子 - 分子团簇，以提取感兴趣的信息。这种计算方法的应用使得能够对液体中的局部微观结构进行直接且无偏的构象研究，这是从半经典MD模拟中得出的。通过计算液态水的典型可观测量，即已知对氢键团簇的存在和构象特征都相当敏感的核磁共振（NMR）、近边X射线吸收精细结构光谱（NEXAFS O1s）和红外光谱，证明了该方法的良好性能。
