Keywords Coarse graining Á Curvature elasticity Á Lipid bilayer Á Mediated
interactions Á Multiscaling Á Simulation
Contents
1 Introduction . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . 238
2 Theory and Simulation of Lipid Bilayers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
2.1 Basic Continuum Theory Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
2.2 Coarse-Grained Lipid Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
2.3 Obtaining Material Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
2.4 The Tension of Lipid Membranes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
2.5 Membrane Heterogeneity and Lipid Rafts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252
3 Membrane–Protein Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
3.1 Hydrophobic Mismatch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
3.2 Curvature-Mediated Interactions Between Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258
4 Multiscale Modeling of Lipid and Membrane Protein Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
4.1 Multiscale Modeling: Approaches and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
4.2 The Light-Harvesting Complex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267
5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
1 Introduction
Lipid bilayers and membrane proteins are one important class of biological
systems for which the relationship between single molecule properties and the
behavior of complex nanoscopically structured materials has been under intense
investigation for a long time. In the present review we address how approaches
combining theory, simulation, and experiment may help us gain a better understanding of phenomena in biomembranes. A general overview of theoretical
considerations and continuum theory of lipid membranes is given and different
modeling and simulation approaches to biomembrane systems are introduced. In
particular, we introduce several generic lipid simulation models and show how
these models can help us understand material properties of lipid bilayers such as
bending and Gaussian curvature modulus, or membrane tension. We discuss timely
topics such as lipid rafts, membrane–protein interactions, and curvature-mediated
interactions between proteins. These fundamental theoretical and modeling investigations are important for understanding the principles that govern the aggregation
phenomena in biological membranes that lead to large superstructures such as the
light-harvesting complex of green plants. In Sect. 4 of this chapter, we give an
overview of multiscale modeling approaches that try to go beyond generic lipid
and protein models and attempt to ensure a certain chemical specificity while still
benefiting from the time- and length-scale advantages of coarse-grained simulations. The section concludes with the example of the light-harvesting complex of
green plants, for which we show first steps toward a multiscale simulation model
that allows one to go back and forth between a coarse-grained and an atomistic
238
M. Deserno et al.
interactions Á Multiscaling Á Simulation
Contents
1 Introduction . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . 238
2 Theory and Simulation of Lipid Bilayers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
2.1 Basic Continuum Theory Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
2.2 Coarse-Grained Lipid Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
2.3 Obtaining Material Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
2.4 The Tension of Lipid Membranes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
2.5 Membrane Heterogeneity and Lipid Rafts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252
3 Membrane–Protein Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
3.1 Hydrophobic Mismatch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
3.2 Curvature-Mediated Interactions Between Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258
4 Multiscale Modeling of Lipid and Membrane Protein Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
4.1 Multiscale Modeling: Approaches and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
4.2 The Light-Harvesting Complex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267
5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
1 Introduction
Lipid bilayers and membrane proteins are one important class of biological
systems for which the relationship between single molecule properties and the
behavior of complex nanoscopically structured materials has been under intense
investigation for a long time. In the present review we address how approaches
combining theory, simulation, and experiment may help us gain a better understanding of phenomena in biomembranes. A general overview of theoretical
considerations and continuum theory of lipid membranes is given and different
modeling and simulation approaches to biomembrane systems are introduced. In
particular, we introduce several generic lipid simulation models and show how
these models can help us understand material properties of lipid bilayers such as
bending and Gaussian curvature modulus, or membrane tension. We discuss timely
topics such as lipid rafts, membrane–protein interactions, and curvature-mediated
interactions between proteins. These fundamental theoretical and modeling investigations are important for understanding the principles that govern the aggregation
phenomena in biological membranes that lead to large superstructures such as the
light-harvesting complex of green plants. In Sect. 4 of this chapter, we give an
overview of multiscale modeling approaches that try to go beyond generic lipid
and protein models and attempt to ensure a certain chemical specificity while still
benefiting from the time- and length-scale advantages of coarse-grained simulations. The section concludes with the example of the light-harvesting complex of
green plants, for which we show first steps toward a multiscale simulation model
that allows one to go back and forth between a coarse-grained and an atomistic
238
M. Deserno et al.