The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
A coarse grain model for DNA
Open accessAbstract
Understanding the behavior of DNA at the molecular level is of considerable fundamental and engineering importance. While adequate representations of DNA exist at the atomic and continuum level, there is a relative lack of models capable of describing the behavior of DNA at mesoscopic length scales. We present a mesoscale model of DNA that reduces the complexity of a nucleotide to three interactions sites, one each for the phosphate, sugar, and base, thereby rendering the investigation of DNA up to a few microns in length computationally tractable. The charges on these sites are considered explicitly. The model is parametrized using thermal denaturation experimental data at a fixed salt concentration. The validity of the model is established by its ability to predict several aspects of DNA behavior, including salt-dependent melting, bubble formation and rehybridization, and the mechanical properties of the molecule as a function of salt concentration.
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Perspective: Coarse-grained models for biomolecular systems
Noid, W. G. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4818908 · Cited by 893
The power of coarse graining in biomolecular simulations
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Martini coarse-grained force field: Extension to RNA
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First-principle approach to rescale the dynamics of simulated coarse-grained macromolecular liquids
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Analytical rescaling of polymer dynamics from mesoscale simulations
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Metadata
- Authors
- Knotts, T. A., Rathore, N., Schwartz, D. C., & de Pablo, J. J.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2007-02-23
- Volume
- 126
- Issue
- 8
- Pages
- 084901-084901
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W1976308393
- Cited by
- 311
- References
- 38
- FWCI
- 6.11
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
