Download Advances in Computational Biology by Hugo O. Villar (Eds.) PDF

By Hugo O. Villar (Eds.)

ISBN-10: 1559389796

ISBN-13: 9781559389792

The second one quantity in a sequence which goals to target advances in computational biology. This quantity discusses such themes as: statistical research of protein sequences; growth in large-scale series research; and the structure of loops in proteins

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The phase diagram in Figure 7(b). The value of ^p is chosen to be close to the hydrophobic thickness of fluid DMPC bilayers. Figure 14 shows the lipid-concentration profiles of DMPC and DSPC as a function of distance, r, from the protein. The protein is seen to select the lipid species (in this case DMPC) which most easily wets the hydrophobic surface of the protein. Conversely, the protein-lipid interface is depleted in the other species. Hence, the protein-lipid interactions lead to compositional heterogeneities.

Mean field theory of this type suppresses the lateral fluctuations in the transition region, and it will, therefore, lead to estimates of the correlation length that are too low. It is only possible to obtain reliable values for the correlation length near the transition by using computer simulation on microscopic models. Using a Monte Carlo simulation, Scott (1986) studied a continuum model of a lipid membrane with a small number of hydrocarbon chains and a single polypeptide (or small protein).

Results from computer-simulation calculations are shown for the free energy functional, J(^m(N), T, L), as a function of bilayer composition, c, for different lattice sizes, /. ,/. 5 K. \im{L) refers to the chemical potential at phase coexistence. limit. At these temperatures the mixture is therefore in a one-phase region at all compositions. The phase diagram spanned by temperature and chemical potential was obtained from data of the type presented in Figure 9 and is shown in Figure 10(a). The solid line in Figure 10(a) indicates the line of coexistence between the gel and fluid lipid phases.

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