Title |
Validating lipid force fields against experimental data: Progress, challenges and perspectives
|
---|---|
Published in |
Biochimica et Biophysica Acta (BBA), February 2016
|
DOI | 10.1016/j.bbamem.2016.01.029 |
Pubmed ID | |
Authors |
David Poger, Bertrand Caron, Alan E. Mark |
Abstract |
Biological membranes display a great diversity in lipid composition and lateral structure that is crucial in a variety of cellular functions. Simulations of membranes have contributed significantly to the understanding of the properties, functions and behaviour of membranes and membrane-protein assemblies. This success relies on the ability of the force field used to describe lipid-lipid and lipid-environment interactions accurately, reproducibly and realistically. In this review, we present some recent progress in lipid force-field development and validation strategies. In particular, we highlight how a range of properties obtained from various experimental techniques on lipid bilayers and membranes, can be used to assess the quality of a force field. We discuss the limitations and assumptions that are inherent to both computational and experimental approaches and how these can influence the comparison between simulations and experimental data. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 2 | 67% |
France | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 33% |
Members of the public | 1 | 33% |
Unknown | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 2% |
Czechia | 2 | 1% |
Uruguay | 1 | <1% |
Germany | 1 | <1% |
Poland | 1 | <1% |
Unknown | 157 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 44 | 27% |
Researcher | 33 | 20% |
Student > Master | 19 | 12% |
Student > Bachelor | 19 | 12% |
Student > Doctoral Student | 10 | 6% |
Other | 20 | 12% |
Unknown | 20 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 38 | 23% |
Biochemistry, Genetics and Molecular Biology | 31 | 19% |
Agricultural and Biological Sciences | 24 | 15% |
Physics and Astronomy | 12 | 7% |
Engineering | 7 | 4% |
Other | 28 | 17% |
Unknown | 25 | 15% |