The DOI matches its Crossref record.
Molecular Dynamics Simulation of the Formation, Structure, and Dynamics of Small Phospholipid Vesicles
Open accessAbstract
Here, we use coarse grained molecular dynamics (MD) simulations to study the spontaneous aggregation of dipalmitoylphosphatidylcholine (DPPC) lipids into small unilamellar vesicles. We show that the aggregation process occurs on a nanosecond time scale, with bicelles and cuplike vesicles formed at intermediate stages. Formation of hemifused vesicles is also observed at higher lipid concentration. With either 25% dipalmitoylphosphatidylethanolamine (DPPE) or lysoPC mixed into the system, the final stages of the aggregation process occur significantly faster. The structure of the spontaneously formed vesicles is analyzed in detail. Microsecond simulations of isolated vesicles reveal significant differences in the packing of the lipids between the inner and outer monolayers, and between PC, PE, and lysoPC. Due to the small size of the vesicles they remain almost perfectly spherical, undergoing very limited shape fluctuations or bilayer undulations. The lipid lateral diffusion rate is found to be faster in the outer than in the inner monolayer. The water permeability coefficient of the pure DPPC vesicles is of the order of 10(-)(3) cm s(-)(1), in agreement with experimental measurements.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
GROMACS: Fast, flexible, and free
Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. C. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20291 · Cited by 19,182
Self-citationCoarse-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
The power of coarse graining in biomolecular simulations
Ingólfsson, H. I., Lopez, C. A., Uusitalo, J. J., de Jong, D. H., Gopal, S. M., Periole, X., & Marrink, S. J. (2014) · WIREs Computational Molecular Science · doi:10.1002/wcms.1169 · Cited by 572
Self-citationAdvances and challenges in smart and functional polymer vesicles
Du, J., & O'Reilly, R. K. (2009) · Soft Matter · doi:10.1039/b905635a · Cited by 572
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-citationMolecular Dynamics Simulation of Nanostructural Organization in Ionic Liquid/Water Mixtures
Jiang, W., Wang, Y., & Voth, G. A. (2007) · The Journal of Physical Chemistry B · doi:10.1021/jp067142l · Cited by 458
Lipids on the move: Simulations of membrane pores, domains, stalks and curves
Marrink, S. J., de Vries, A. H., & Tieleman, D. P. (2009) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/j.bbamem.2008.10.006 · Cited by 440
Self-citationLipid Bilayer Pressure Profiles and Mechanosensitive Channel Gating
Gullingsrud, J., & Schulten, K. (2004) · Biophysical Journal · doi:10.1529/biophysj.103.034322 · Cited by 342
Biological and synthetic membranes: What can be learned from a coarse-grained description?
MULLER, M., KATSOV, K., & SCHICK, M. (2006) · Physics Reports · doi:10.1016/j.physrep.2006.08.003 · Cited by 320
Synaptotagmin-Mediated Bending of the Target Membrane Is a Critical Step in Ca2+-Regulated Fusion
Hui, E., Johnson, C. P., Yao, J., Dunning, F. M., & Chapman, E. R. (2009) · Cell · doi:10.1016/j.cell.2009.05.049 · Cited by 291
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
Self-citationShinoda, W., DeVane, R., & Klein, M. L. (2010) · The Journal of Physical Chemistry B · doi:10.1021/jp9107206 · Cited by 276
Two decades of Martini: Better beads, broader scope
Marrink, S. J., Monticelli, L., Melo, M. N., Alessandri, R., Tieleman, D. P., & Souza, P. C. T. (2023) · WIREs Computational Molecular Science · doi:10.1002/wcms.1620 · Cited by 255
Coarse grained protein- lipid model with application to lipoprotein particles
Shih, A. Y., Arkhipov, A., Freddolino, L., & Schulten, K. (2006) · The Journal of Physical Chemistry B · doi:10.1021/jp0550816 · Cited by 267
Periole, X. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00344 · Cited by 58
Metadata
- Authors
- Marrink, S. J., & Mark, A. E.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2003-11-13
- Volume
- 125
- Issue
- 49
- Pages
- 15233-15242
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2116493166
- Cited by
- 316
- References
- 0
- FWCI
- 4.93
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.