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

By Hugo O. Villar (Eds.)

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

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Depending on the strength of the van der Waals-like interaction associated with the direct lipid and protein hydrophobic contact, the proteins may still remain dispersed in the fluid phospholipid cc ^ o T—• CO o O CO ^ <4-l CO CO 48 o o CO bJO 00 (M o "o X t—I "o 00 "o _O CM 49 Q) Q E to "D C 03 «/) ;g 'g. U QQ_ Q *+o - - D C - 2 CU . y o 03 DO C |:^5 2 S'5 g o o 9^ ^ "T 2 oo = ^ So u a; OJ Q. W) CD C OS _ E CD «+- - a C £ ^^ 03 CD ^ DO OJ iZ.

Moreover, the attractive lipid-protein interactions tend to keep the Computation of L ipid-Protein Interactions 51 proteins apart by 'spacing' them with lipids. Such 'spacer' lipids are bound in the sense that they are dynamically trapped. Hence, the direct lipid-protein van der Waals-like interactions tend to reduce the degree of protein aggregation. By focusing on a model without direct protein-protein interactions we have therefore managed to isolate the effects of purely lipid-facilitated protein aggregation.

Figure 7 shows selected results from calculations on the lipid bilayer model, Eq. (2), extended to account for interactions between saturated phospholipid acyl chains with different hydrophobic length; cf. Eqs. (4) and (5), specifically dimyristoyl 1 1 L 1 " (a) 1 ^ ^ L r- 1 1 bO 4 Q3 * yv ^ ^ . 0 X J ^ ik X X o ^* J ? H ^ * ^ r I^* 1 J X I o 1 q ^ dX 1 '• ^ ^ % it \ ni ^^ X J X^ A \, '4\ A %\ Jl. 4 A^* 325 1 X ^ h. 0 a^DSPC Figure 7. Monte Carlo computer-simulation data for a DMPC-DSPC mixture described by the model in Eqs.

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