Mesoscopic models of lipid bilayers and bilayers with embedded ...

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108 Mesoscopic model for lipid bilayers with embedded proteins 30.0 d L (r) [Å] 25.0 20.0 15.0 10.0 5.0 0.0 30.0 d L (r) [Å] 25.0 20.0 15.0 10.0 5.0 0.0 30.0 d L (r) [Å] 25.0 20.0 15.0 10.0 5.0 0.0 eff dP dP eff dP dP eff dP dP ∆d0 0 10 20 30 40 50 60 70 80 90 r [Å] (f) NP = 43, Figure 7.4: Calculated values of dL(r) (open circles) and fitting ones using expression 7.3 (solid line) as a function of the distance r from the protein surface. The data refer to the three protein sizes NP=4, 7, and 43; and to two values of the protein hydrophobic length dP=14˚A (∆d=-10˚A) and 41˚A (∆d=17˚A). Also shown is the ‘level’ value of the unperturbed lipid bilayer thickness d o L =(23.6±0.2) ˚A (dashed line), the calculated protein hydrophobic length dP (gray area), and the effective protein hydrophobic length d eff P (white area), which is defined as the projection of dP onto the normal to the bilayer plane. The data refer to simulations at the reduced temperature T ∗ =0.7. o dL dL dL fit o dL dL dL fit o dL dL dL fit
7.3 Results and discussion 109 that this is also the case for the other values of positive mismatch. The derived values of ξP (using equation 7.3) as function of protein size and hydrophobic mismatch, which are shown in Table 7.2, indicate that there is a mismatch dependence of the perturbation caused by the protein on the surrounding lipids. For a given protein size, NP, if the mismatch is negative, the correlation length increases with decreasing mismatch (absolute value), while for positive mismatch the opposite happens, and the correlation length increases with increasing mismatch. Also, in the case of negative mismatch the decay length increases by increasing the protein size. Instead there is no detectable ξP dependence on NP in the case of ∆d > 0, at least at the considered temperature, i.e. well above the melting temperature of the pure system. The scenario is somehow different when the temperature decreases and approaches the transition temperature, as it is discussed in the next section. Figure 7.4f shows that, for the large protein (NP=43), the lipid thickness profile dL(r) differs from an exponential one. The effect is even more pronounced at lower temperatures (data not shown), at least in the case of negative mismatch (since lower temperature means larger negative mismatch). This non-exponential behavior, and the possible reason for it, will be discussed later. Table 7.2 also gives the values of the pure lipid bilayer hydrophobic thickness d o L obtained from the best fit of dL(r) using equation 7.3. For all the considered cases, the (fitted) compare well with the value of the pure lipid bilayer hydrophobic values of do L thickness, do L =23.6 ˚A, obtained directly from the simulation at the considered temperature. 7.3.2 Lipid-induced protein tilting The protein tilt angle with respect to the bilayer normal as function of ∆d and protein size NP is shown in figure 7.5. The snapshots on the right show typical configurations of the system, for a fixed value of the protein hydrophobic length, for the three protein sizes, NP=4, 7, and 43, and for the largest (positive) value of mismatch, ∆d=26 ˚A, at the considered temperature, T ∗ =0.7. For ∆d < 0 the tilt angle is very small, and is within the statistical tilt-fluctuations to which the protein is subject in the bilayer; as the protein hydrophobic length increases (and the mismatch becomes positive), the protein undergoes a significant tilting. Also, for equal values of hydrophobic mismatch, the “thinner” protein (NP=4) is much more tilted than the “fatter” one (NP=43). These results, combined with the one discussed above, suggest that in the case of proteins with small surface area, the main mechanism to compensate for a large hydrophobic mismatch is the tilt, while in the case of proteins with a large surface area, that cannot accommodate a too large tilt, the mismatch is mainly compensated for by an increase of the bilayer thickness around the protein, as is clearly illustrated by the snapshot in figure 7.5 (NP=43).
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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
Page 64 and 65: 58 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)
Page 99: 6.3 Results and Discussion 93 the l
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
Page 139: ied dat het dichtst bij het hydrofo
Page 143: This thesis is based on the followi
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