The impact of monovalent ion force field model in nucleic acids simulations

文献信息

发布日期 2009-08-18

DOI 10.1039/B912067J

影响因子 3.676

作者

Agnes Noy, Ignacio Soteras, F. Javier Luque

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摘要

Different classical models for monovalent ions (typically used to neutralize proteins or nucleic acids) are available in the literature and are widely used in molecular dynamics simulations without a great knowledge of their quality, consistency with the macromolecular force field and impact on the global simulation results. In this paper the ability of several of the most popular ion models to reproduce both quantum mechanics and experimental results is examined. Artefacts due to the use of incorrect ion models in molecular dynamics simulations of concentrated solutions of NaCl and KCl in water and of a short DNA duplex in 500 mM aqueous solutions of NaCl and KCl have been analyzed. Our results allow us to discuss the robustness and reliability of different ion models and to highlight the source of potential errors arising from non-optimal models. However, it is also found that the structural and dynamic characteristics of DNA (as an example of a heavily charged macromolecule) in near-physiological conditions are quite independent of the ion model used, providing support to most already-published simulations of macromolecules.

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来源期刊

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.