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A quantitative coarse-grain model for lipid bilayers

A quantitative coarse-grain model for lipid bilayers
A quantitative coarse-grain model for lipid bilayers
A simplified particle-based computer model for hydrated phospholipid bilayers has been developed and applied to quantitatively predict the major physical features of fluid-phase biomembranes. Compared with available coarse-grain methods, three novel aspects are introduced. First, the main electrostatic features of the system are incorporated explicitly via charges and dipoles. Second, water is accurately (yet efficiently) described, on an individual level, by the soft sticky dipole model. Third, hydrocarbon tails are modeled using the anisotropic Gay?Berne potential. Simulations are conducted by rigid-body molecular dynamics. Our technique proves 2 orders of magnitude less demanding of computational resources than traditional atomic-level methodology. Self-assembled bilayers quantitatively reproduce experimental observables such as electron density, compressibility moduli, dipole potential, lipid diffusion, and water permeability. The lateral pressure profile has been calculated, along with the elastic curvature constants of the Helfrich expression for the membrane bending energy; results are consistent with experimental estimates and atomic-level simulation data. Several of the results presented have been obtained for the first time using a coarse-grain method. Our model is also directly compatible with atomic-level force fields, allowing mixed systems to be simulated in a multiscale fashion.
1520-5207
802-815
Orsi, Mario
62904259-9a93-4d02-8ce6-d8ef53dfcbf1
Haubertin, David Y.
6a871348-21e0-41de-88d9-31e6b70be6e5
Sanderson, Wendy E.
0cc3f930-2c22-4a5a-b8b0-a7bc4e457e24
Essex, Jonathan W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
Orsi, Mario
62904259-9a93-4d02-8ce6-d8ef53dfcbf1
Haubertin, David Y.
6a871348-21e0-41de-88d9-31e6b70be6e5
Sanderson, Wendy E.
0cc3f930-2c22-4a5a-b8b0-a7bc4e457e24
Essex, Jonathan W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5

Orsi, Mario, Haubertin, David Y., Sanderson, Wendy E. and Essex, Jonathan W. (2008) A quantitative coarse-grain model for lipid bilayers. The Journal of Physical Chemistry B, 112 (3), 802-815. (doi:10.1021/jp076139e). (PMID:18085766)

Record type: Article

Abstract

A simplified particle-based computer model for hydrated phospholipid bilayers has been developed and applied to quantitatively predict the major physical features of fluid-phase biomembranes. Compared with available coarse-grain methods, three novel aspects are introduced. First, the main electrostatic features of the system are incorporated explicitly via charges and dipoles. Second, water is accurately (yet efficiently) described, on an individual level, by the soft sticky dipole model. Third, hydrocarbon tails are modeled using the anisotropic Gay?Berne potential. Simulations are conducted by rigid-body molecular dynamics. Our technique proves 2 orders of magnitude less demanding of computational resources than traditional atomic-level methodology. Self-assembled bilayers quantitatively reproduce experimental observables such as electron density, compressibility moduli, dipole potential, lipid diffusion, and water permeability. The lateral pressure profile has been calculated, along with the elastic curvature constants of the Helfrich expression for the membrane bending energy; results are consistent with experimental estimates and atomic-level simulation data. Several of the results presented have been obtained for the first time using a coarse-grain method. Our model is also directly compatible with atomic-level force fields, allowing mixed systems to be simulated in a multiscale fashion.

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e-pub ahead of print date: 18 December 2007
Published date: 24 January 2008
Organisations: Chemistry

Identifiers

Local EPrints ID: 149193
URI: http://eprints.soton.ac.uk/id/eprint/149193
ISSN: 1520-5207
PURE UUID: 4730f4b2-6063-40f5-b1d8-ed8635739f6f
ORCID for Jonathan W. Essex: ORCID iD orcid.org/0000-0003-2639-2746

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Date deposited: 30 Apr 2010 08:51
Last modified: 14 Mar 2024 02:37

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Contributors

Author: Mario Orsi
Author: David Y. Haubertin
Author: Wendy E. Sanderson

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