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116 Mesoscopic model for lipid bilayers with embedded proteins A somehow different scenario arises when a protein is subjected to a negative mismatch, as illustrated in the snapshot in figure 7.8(b), which shows a typical configuration obtained from the simulations on a bilayer with embedded a protein with ˜dP=14 ˚A, thus subjected to negative mismatch ∆d=-23 ˚A. In this case the protein orients antiparallel to the orientation of the lipids; also, the lipids in the vicinity of the protein interdigitate to decrease the bilayer hydrophobic thickness and thus fulfill the matching condition. To better illustrate this phenomenon, we have depicted the end-bead of of the lipid chains in darker color. From the snapshot in figure 7.8(b) it can be seen that, in the vicinity of the protein, the end-tail of the lipids in one monolayer are close to the headgroups of the lipids in the opposite monolayer. As described in section 5.3 of Chapter 5, by increasing the temperature above T∗ =0.35, the pure lipid bilayer undergoes a transition from the Lβ ′ phase to a ‘striated’ phase that resembles the Pβ ′ phase of phospholipid bilayers. Interestingly, upon incorporation of a protein, and depending on the mismatch condition, the protein segregates into the striated region whose hydrophobic thickness better matches the protein hydrophobic length. This is clearly shown in the snapshots in figure 7.9, which depict two typical configurations of the systems at a reduced temperature T∗ =0.4, and in the case of proteins with ˜dP=41 ˚A and 18 ˚A, respectively. The calculated value of the pure lipid bilayer hydrophobic thickness is do L =(30.0±0.3) ˚A. Both cases refer to a protein of size NP=7. For positive values of hydrophobic mismatch (see fig- (a) ∆d > 0 (b) ∆d < 0 Figure 7.9: Snapshots of two typical configurations of lipid-protein bilayers at a reduced temperature T ∗ =0.4, in the ‘striated’ gel phase, which resembles the Pβ ′ phase in phospholipid bilayers. The calculated value of the pure lipid bilayer hydrophobic thickness is d o L =(30.0±0.3) ˚A. In (a) is shown the case of a protein of size NP=7 and ˜dP=41 ˚A, thus subjected to a positive mismatch ∆d=11 ˚A, while in (b) is shown the case of a NP=7 size protein, but with ˜dP=18 ˚A, thus subjected to negative mismatch ∆d=-12 ˚A. ure 7.9(a)), the protein prefers to segregate in the striated region formed by lipids in the gel-like state. Instead, in the case of negative mismatch, the protein prefers the region where the chains are fluid-like (see figure 7.9(b)). The interplay between the underlying structure of the striated phase and the mismatch-induced perturbation could provide a mean to tune the lateral organization of membrane proteins, and thus control their segregation in the two-dimensional ordered structure. To understand how ordered structures might form is important because scattering methods
7.4 Conclusion 117 make use of ordered structure as a matrix to determine the three-dimensional structure of proteins [187, 188]. 7.4 Conclusion We have presented a mesoscopic model for lipid bilayers with embedded proteins, which we have studied with the Dissipative Particle Dynamics simulation method. One of our aims was to point out the advantages of the DPD-simulation-CG-model approach by addressing some simple issues related to the collective nature of a threedimensional membrane system, a lipid bilayer containing just one lipid species and an embedded protein. More specifically, we have investigated the effect due to mismatch and protein size on the perturbation induced by the protein on the surrounding lipid bilayer. The perturbation around the protein was quantified in terms of the bilayer hydrophobic thickness profile. We found that the profile may have an exponential form, decays to the value of the thickness of the unperturbed system (i.e. without protein), and can be characterized by the coherence length, ξP, of the spatial fluctuation around the protein. We found that, under well defined thermodynamic conditions, the value of ξP may depend on mismatch and protein size, the larger the mismatch/size the larger ξP. Also, we found that to adapt to a too thin bilayer the protein may tilt (or even bend) in a manner which is mismatch and protein-size dependent. We have found that the model predictions are in qualitative agreement with previous theoretical and experimental findings. We want to stress that the phenomena that we have investigated with the DPD simulation method involve molecular rearrangements in the membrane plane via, among others, diffusion of molecules whose time scale might be outside the range of investigation of more ‘traditional’ simulation techniques, such as MD. The results discussed above refer to a model for DMPC bilayers. The trend shown by these results can also be applied to lipid bilayers with other types of phospholipids, i.e. with longer or shorter hydrocarbon chains then the ones of DMPC. We would like to conclude by saying that the predictions that arise from numerical simulation studies of model systems, such as the one presented here, may be used as a complementary tool to experimental studies to reveal information not otherwise accessible; also, results from numerical studies can provide a framework for the interpretation of experimental data, as well as serve as a source of inspiration for future experiments.
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Mesoscopic models of lipid bilayers
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Promotiecommissie: Promotor: • pr
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ii CONTENTS 5.3 Double-tail lipid b
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2 Introduction 1.1 The cell membran
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4 Introduction between the beads, a
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6 Introduction whether the preferre
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8 Simulation method for coarse-grai
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10 Simulation method for coarse-gra
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III Surface tension in lipid bilaye
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3.2 Method of calculation of surfac
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3.2 Method of calculation of surfac
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3.3 Constant surface tension ensemb
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3.3 Constant surface tension ensemb
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3.4 Surface tension in lipid bilaye
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IV Structural characterization of l
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4.2 Structural quantities 39 been r
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4.3 Computational details 41 lipid
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4.4 Results and discussion 43 ρ(z)
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4.4 Results and discussion 45 one l
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4.4 Results and discussion 47 WH HT
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4.4 Results and discussion 49 Shill
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4.4 Results and discussion 51 chain
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4.4 Results and discussion 53 4.4.4
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4.4 Results and discussion 55 headg
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58 Phase behavior of coarse-grained
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Page 72 and 73: 66 Phase behavior of coarse-grained
Page 85 and 86: VI Interaction of small molecules w
Page 87 and 88: 6.2 Computational details 81 For re
Page 89 and 90: 6.3 Results and Discussion 83 withi
Page 91 and 92: 6.3 Results and Discussion 85 ρ(z)
Page 93 and 94: 6.3 Results and Discussion 87 ρ(z)
Page 95 and 96: 6.3 Results and Discussion 89 S m 0
Page 97 and 98: 6.3 Results and Discussion 91 π(z)
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Page 102 and 103: 96 Mesoscopic model for lipid bilay
Page 104 and 105: 98 Mesoscopic model for lipid bilay
Page 106 and 107: 100 Mesoscopic model for lipid bila
Page 125 and 126: References [1] Tanford, C. Science
Page 127 and 128: 7.4 Conclusion 121 [68] Ono, S.; Ko
Page 129 and 130: 7.4 Conclusion 123 [139] Lee, A. Bi
Page 131 and 132: Summary Biological membranes, as th
Page 133 and 134: agreement we find gives us confiden
Page 135 and 136: Samenvatting Biologische membranen,
Page 137 and 138: de lage temperatuur gel fase of Lβ
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