The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Systematic coarse-graining of molecular models by the Newton inversion method
Open accessAbstract
Systematic construction of coarse-grained molecular models from detailed atomistic simulations, and even from ab initio simulations is discussed. Atomistic simulations are first performed to extract structural information about the system, which is then used to determine effective potentials for a coarse-grained model of the same system. The statistical-mechanical equations expressing the canonical properties in terms of potential parameters can be inverted and solved numerically according to the iterative Newton scheme. In our previous applications, known as the Inverse Monte Carlo, radial distribution functions were inverted to reconstruct pair potential, while in a more general approach the targets can be other canonical averages. We have considered several examples of coarse-graining; for the united atom water model we suggest an easy way to overcome the known problem of high pressure. Further, we have developed coarse-grained models for L- and D-prolines, dissolved here in an organic solvent (dimethylsulfoxide), keeping their enantiomeric properties from the corresponding all-atom proline model. Finally, we have revisited the previously developed coarse-grained lipid model based on an updated all-atomic force field. We use this model in large-scale meso-scale simulations demonstrating spontaneous formation of different structures, such as vesicles, micelles, and multi-lamellar structures, depending on thermodynamical conditions.
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Cites
Coarse Grained Model for Semiquantitative Lipid Simulations
Marrink, S. J., de Vries, A. H., & Mark, A. E. (2004) · The Journal of Physical Chemistry B · doi:10.1021/jp036508g · Cited by 2,257
Interatomic Potentials from First-Principles Calculations: The Force-Matching Method
Ercolessi, F., & Adams, J. B. (1994) · Europhysics Letters (EPL) · doi:10.1209/0295-5075/26/8/005 · Cited by 1,455
Deriving effective mesoscale potentials from atomistic simulations
Reith, D., Pütz, M., & Müller‐Plathe, F. (2003) · Journal of Computational Chemistry · doi:10.1002/jcc.10307 · Cited by 1,314
Lyubartsev, A. P., & Laaksonen, A. (1995) · Physical Review E · doi:10.1103/physreve.52.3730 · Cited by 852
Self-citationHierarchical modeling of polystyrene: From atomistic to coarse-grained simulations
Harmandaris, V. A., Adhikari, N. P., van der Vegt, N. F. A., & Kremer, K. (2006) · Macromolecules · doi:10.1021/ma0606399 · Cited by 350
Cited by
Computer Simulation of Liquids
Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945
Coarse-Grained Protein Models and Their Applications
Kmiecik, S., Gront, D., Kolinski, M., Wieteska, L., Dawid, A. E., & Kolinski, A. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00163 · Cited by 1,071
Perspective: Coarse-grained models for biomolecular systems
Noid, W. G. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4818908 · Cited by 893
How Water’s Properties Are Encoded in Its Molecular Structure and Energies
Brini, E., Fennell, C. J., Fernandez-Serra, M., Hribar-Lee, B., Lukšič, M., & Dill, K. A. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00259 · Cited by 518
Dry Martini, a Coarse-Grained Force Field for Lipid Membrane Simulations with Implicit Solvent
Arnarez, C., Uusitalo, J. J., Masman, M. F., Ingólfsson, H. I., de Jong, D. H., Melo, M. N., Periole, X., de Vries, A. H., & Marrink, S. J. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/ct500477k · Cited by 278
Metadata
- Authors
- Lyubartsev, A., Mirzoev, A., Chen, L., & Laaksonen, A.
- Venue
- Faraday Discuss.
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2010
- Volume
- 144
- Pages
- 43-56
- ISSN
- 1359-6640 (ISSN-L)
- 1364-5498
- OpenAlex
- W2041551173
- Cited by
- 180
- References
- 5
- FWCI
- 5.64
- 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).
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