Literature DB >> 36204133

Simulation Best Practices for Lipid Membranes [Article v1.0].

David J Smith1, Jeffery B Klauda2, Alexander J Sodt3.   

Abstract

We establish a reliable and robust standardization of settings for practical molecular dynamics (MD) simulations of pure and mixed (single- and multi-component) lipid bilayer membranes. In lipid membranes research, particle-based molecular simulations are a powerful tool alongside continuum theory, lipidomics, and model, in vitro, and in vivo experiments. Molecular simulations can provide precise and reproducible spatiotemporal (atomic- and femtosecond-level) information about membrane structure, mechanics, thermodynamics, kinetics, and dynamics. Yet the simulation of lipid membranes can be a daunting task, given the uniqueness of lipid membranes relative to conventional liquid-liquid and solid-liquid interfaces, the immense and complex thermodynamic and statistical mechanical theory, the diversity of multiscale lipid models, limitations of modern computing power, the difficulty and ambiguity of simulation controls, finite size effects, competitive continuum simulation alternatives, and the desired application, including vesicle experiments and biological membranes. These issues can complicate an essential understanding of the field of lipid membranes, and create major bottlenecks to simulation advancement. In this article, we clarify these issues and present a consistent, thorough, and user-friendly framework for the design of state-of-the-art lipid membrane MD simulations. We hope to allow early-career researchers to quickly overcome common obstacles in the field of lipid membranes and reach maximal impact in their simulations.

Entities:  

Year:  2019        PMID: 36204133      PMCID: PMC9534443          DOI: 10.33011/livecoms.1.1.5966

Source DB:  PubMed          Journal:  Living J Comput Mol Sci


  137 in total

1.  GROMACS: fast, flexible, and free.

Authors:  David Van Der Spoel; Erik Lindahl; Berk Hess; Gerrit Groenhof; Alan E Mark; Herman J C Berendsen
Journal:  J Comput Chem       Date:  2005-12       Impact factor: 3.376

2.  Free energy of a trans-membrane pore calculated from atomistic molecular dynamics simulations.

Authors:  J Wohlert; W K den Otter; O Edholm; W J Briels
Journal:  J Chem Phys       Date:  2006-04-21       Impact factor: 3.488

3.  Flexible lipid bilayers in implicit solvent.

Authors:  Grace Brannigan; Peter F Philips; Frank L H Brown
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2005-07-26

4.  A novel method for measuring the bending rigidity of model lipid membranes by simulating tethers.

Authors:  Vagelis A Harmandaris; Markus Deserno
Journal:  J Chem Phys       Date:  2006-11-28       Impact factor: 3.488

5.  Determining the Gaussian curvature modulus of lipid membranes in simulations.

Authors:  Mingyang Hu; John J Briguglio; Markus Deserno
Journal:  Biophys J       Date:  2012-03-20       Impact factor: 4.033

6.  Determination of electron density profiles and area from simulations of undulating membranes.

Authors:  Anthony R Braun; Erik G Brandt; Olle Edholm; John F Nagle; Jonathan N Sachs
Journal:  Biophys J       Date:  2011-05-04       Impact factor: 4.033

7.  GridMAT-MD: a grid-based membrane analysis tool for use with molecular dynamics.

Authors:  William J Allen; Justin A Lemkul; David R Bevan
Journal:  J Comput Chem       Date:  2009-09       Impact factor: 3.376

8.  A new force field for simulating phosphatidylcholine bilayers.

Authors:  David Poger; Wilfred F Van Gunsteren; Alan E Mark
Journal:  J Comput Chem       Date:  2010-04-30       Impact factor: 3.376

Review 9.  Force Field Development for Lipid Membrane Simulations.

Authors:  Alexander P Lyubartsev; Alexander L Rabinovich
Journal:  Biochim Biophys Acta       Date:  2016-01-04

Review 10.  Site-Directed Spin Labeling EPR for Studying Membrane Proteins.

Authors:  Indra D Sahu; Gary A Lorigan
Journal:  Biomed Res Int       Date:  2018-01-23       Impact factor: 3.411

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