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Cited by 336

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Improved Parametrization of Li+, Na+, K+, and Mg2+ Ions for All-Atom Molecular Dynamics Simulations of Nucleic Acid Systems

Yoo, Jejoong, Aksimentiev, Aleksei·2012·The Journal of Physical Chemistry Letters

Abstract

Atomic-scale modeling of compacted nucleic acids has the ability to reveal the inner workings of spectacular biomolecular machines, yet the outcome of such modeling efforts sensitively depends on the accuracy of the underlying computational models. Our molecular dynamics simulations of an array of 64 parallel duplex DNA revealed considerable artifacts of cation–DNA phosphate interactions in CHARMM and AMBER parameter sets: both the DNA arrangement and the pressure inside the DNA arrays were found to be in considerable disagreement with experiment. To improve the models, we fine-tuned van der Waals interaction parameters for specific ion pairs to reproduce experimental osmotic pressure of binary electrolyte solutions of biologically relevant ions. Repeating the DNA array simulations using our parameters produced results consistent with experiment. Our improved parametrization can be directly applied to molecular dynamics simulations of various charged biomolecular systems, including nucleic acids, proteins, and lipid bilayer membranes.

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Metadata

Authors
Yoo, J., & Aksimentiev, A.
Venue
The Journal of Physical Chemistry Letters
Published
2011-12-13
Volume
3
Issue
1
Pages
45-50
ISSN
1948-7185 (ISSN-L)
OpenAlex
W2316392160
Cited by
336
References
2
FWCI
4.47
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Improved Parametrization of Li+, Na+, K+, and Mg2+ Ions for All-Atom Molecular Dynamics Simulations of Nucleic Acid Systems. https://app.cochat.ai/papers/10.1021/jz201501a
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Yoo, J., & Aksimentiev, A. (2012). Improved Parametrization of Li+, Na+, K+, and Mg2+ Ions for All-Atom Molecular Dynamics Simulations of Nucleic Acid Systems. The Journal of Physical Chemistry Letters. https://doi.org/10.1021/jz201501a

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.