Publications by authors named "Bram Van Hoof"

Liposomes composed of fatty acids and phospholipids are frequently used as model systems for biological cell membranes. In many applications, the encapsulation of proteins and other biomacromolecules in these liposomes is essential. Intriguingly, the concentration of entrapped material often deviates from that in the solution where the liposomes were formed.

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Spontaneous aggregation of lipids into bilayers and vesicles is a key property for the formation of biological membranes. Understanding the compartmentalization achieved by vesicle formation is an important step toward understanding the origin of life, and is crucial in current efforts to develop artificial life. Spontaneously formed vesicles may be applied as artificial cells if they can efficiently encapsulate biomacromolecules.

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Molecular dynamics (MD) simulations are an important tool for studying various interesting phenomena in nature at the molecular level. To allow molecular simulation methods to be applied to larger systems and for longer time scales, coarse grained (CG) models have been developed in which groups of atoms are represented by a single coarse grained particle. In so-called multiscale CG models, an atomistic simulation is coarse grained and subsequently used to derive a CG force field.

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The biosynthesis of the mineralocorticoid hormone aldosterone involves a multistep hydroxylation of 11-deoxycorticosterone at the 11- and 18-positions, resulting in the formation of corticosterone and 18-hydroxycorticosterone, the final precursor of aldosterone. Two members of the cytochrome P450 11B family, CYP11B1 and CYP11B2, are known to catalyze these 11- and 18-hydroxylations, however, only CYP11B2 can oxidize 18-hydroxycorticosterone to aldosterone. It is unknown what sequence of hydroxylations leads to the formation of 18-hydroxycorticosterone.

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Many biological cellular processes occur at the micro- or millisecond time scale. With traditional all-atom molecular modeling techniques it is difficult to investigate the dynamics of long time scales or large systems, such as protein aggregation or activation. Coarse graining (CG) can be used to reduce the number of degrees of freedom in such a system, and reduce the computational complexity.

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