The DOI matches its Crossref record; 168 of the 168 references it cites were found in a registry or an index.
The power of coarse graining in biomolecular simulations
Open accessAbstract
Computational modeling of biological systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resolution, coarse grained (CG), beads has opened the way to simulate large‐scale biomolecular processes on time scales inaccessible to all‐atom models. We provide an overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity. A few state‐of‐the‐art examples of protein folding, membrane protein gating and self‐assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods
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The MARTINI Force Field: Coarse Grained Model for Biomolecular Simulations
Marrink, S. J., Risselada, H. J., Yefimov, S., Tieleman, D. P., & de Vries, A. H. (2007) · The Journal of Physical Chemistry B · doi:10.1021/jp071097f · Cited by 5,562
Self-citationThe MARTINI Coarse-Grained Force Field: Extension to Proteins
Monticelli, L., Kandasamy, S. K., Periole, X., Larson, R. G., Tieleman, D. P., & Marrink, S.-J. (2008) · Journal of Chemical Theory and Computation · doi:10.1021/ct700324x · Cited by 2,489
Self-citationCoarse 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
How fast-folding proteins fold
Lindorff-Larsen, K., Piana, S., Dror, R. O., & Shaw, D. E. (2011) · Science · doi:10.1126/science.1208351 · Cited by 1,980
‘Improved parameters for the Martini coarse-grained protein force field’
de Jong, D. H., Singh, G., Bennett, W. F. D., Arnarez, C., Wassenaar, T. A., Schäfer, L. V., Periole, X., Tieleman, D. P., & Marrink, S. J. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct300646g · Cited by 1,486
Duan, Y., & Kollman, P. A. (1998) · Science · doi:10.1126/science.282.5389.740 · Cited by 1,333
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
Theory for the folding and stability of globular proteins
Dill, K. A. (1985) · Biochemistry · doi:10.1021/bi00327a032 · Cited by 1,249
Métézeau, P. (1998) · Research in Microbiology · doi:10.1016/s0923-2508(98)80442-7 · Cited by 1,243
Miyazawa, S., & Jernigan, R. L. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0114 · Cited by 1,230
Cited by
Martini 3: A general purpose force field for coarse-grained molecular dynamics
Souza, P. C. T., Alessandri, R., Barnoud, J., Thallmair, S., Faustino, I., Grünewald, F., Patmanidis, I., Abdizadeh, H., Bruininks, B. M. H., Wassenaar, T. A., et al. (2021) · Nature Methods · doi:10.1038/s41592-021-01098-3 · Cited by 1,551
Wassenaar, T. A., Ingólfsson, H. I., Böckmann, R. A., Tieleman, D. P., & Marrink, S. J. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00209 · Cited by 1,174
Self-citationCombining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
Keith, J. A., Vassilev-Galindo, V., Cheng, B., Chmiela, S., Gastegger, M., Müller, K.-R., & Tkatchenko, A. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00107 · Cited by 849
CHARMM-GUI Martini Maker for Coarse-Grained Simulations with the Martini Force Field
Qi, Y., Ingólfsson, H. I., Cheng, X., Lee, J., Marrink, S. J., & Im, W. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00513 · Cited by 494
Self-citationEmerging Diversity in Lipid–Protein Interactions
Corradi, V., Sejdiu, B. I., Mesa-Galloso, H., Abdizadeh, H., Noskov, S. Y., Marrink, S. J., & Tieleman, D. P. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00451 · Cited by 459
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Metadata
- Authors
- Ingólfsson, H. I., Lopez, C. A., Uusitalo, J. J., de Jong, D. H., Gopal, S. M., Periole, X., & Marrink, S. J.
- Venue
- WIREs Computational Molecular Science
- Publisher
- Wiley
- Published
- 2013-08-27
- Volume
- 4
- Issue
- 3
- Pages
- 225-248
- ISSN
- 1759-0876 (ISSN-L)
- 1759-0884
- OpenAlex
- W1806547840
- Cited by
- 572
- References
- 168
- FWCI
- 15.33
- Type
- journal article
- Language
- en
- Open access
- hybrid
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