Estimation of Liposome Penetration Barriers of Drug Molecules with All-Atom and Coarse-Grained Models.

Liposomes are common carriers of drug molecules, providing enhanced delivery and accumulation of hydrophilic agents or larger biomolecules. Molecular simulations can be used to estimate key features of the drug molecules upon interaction with the liposomes, such as penetration barriers and localization. Herein, we investigate several aspects of the computational estimation of penetration barriers, viz. the potential of mean force (PMFs) along a vector spanning the membrane. First, we provide an evaluation of the all-atom (AA) and coarse-grained (CG) parametrization of 5-aminolevulinic acid (5-ALA) and two of its alkyl esters by computing n-octanol/water partition coefficients. We find that the CG parametrization of the esters performs significantly better than the CG model of 5-ALA, highlighting the difficulty to coarse-grain small, polar molecules. However, the expected trend in partition coefficients is reproduced also with the CG models. Second, we compare PMFs in a small membrane slab described with either the AA or CG models. Here, we are able to reproduce the all-atom PMF of 5-ALA with CG. However, for the alkyl esters it is unfortunately not possible to correctly reproduce both the depth and the penetration barrier of the PMF seen in the AA simulations with any of the tested CG models. We argue that it is more important to choose a CG parametrization that reproduces the depth of the PMF. Third, we compare, using the CG model, PMFs in the membrane slab with PMFs in a large, realistic liposome. We find similar depths but slightly different penetration barriers most likely due to differences in the lipid density along the membrane axis. Finally, we compute PMFs in liposomes with three different lipid compositions. Unfortunately, differences in the PMFs could not be quantified, and it remains to be investigated to what extent liposome simulations can fully reproduce experimental findings.