Vibrational mode assignment of finite temperature infrared spectra using the AMOEBA polarizable force field

文献信息

发布日期 2015-07-20
DOI 10.1039/C5CP02270C
影响因子 3.676
作者

Florian Thaunay, Jean-Pierre Dognon, Gilles Ohanessian, Carine Clavaguéra


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摘要

The calculation of infrared spectra by molecular dynamics simulations based on the AMOEBA polarizable force field has recently been demonstrated [Semrouni et al., J. Chem. Theory Comput., 2014, 10, 3190]. While this approach allows access to temperature and anharmonicity effects, band assignment requires additional tools, which we describe in this paper. The Driven Molecular Dynamics approach, originally developed by Bowman, Kaledin et al. [Bowman et al. J. Chem. Phys., 2003, 119, 646, Kaledin et al. J. Chem. Phys., 2004, 121, 5646] has been adapted and associated with AMOEBA. Its advantages and limitations are described. The IR spectrum of the Ac-Phe-Ala-NH2 model peptide is analyzed in detail. In addition to differentiation of conformations by reproducing frequency shifts due to non-covalent interactions, DMD allows visualizing the temperature-dependent vibrational modes.

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来源期刊

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
自引率: 10.3%
年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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