Issue 6, 2023

Partitioning into phosphatidylcholine–cholesterol membranes: liposome measurements, coarse-grained simulations, and implications for bioaccumulation

Abstract

Membrane–water partitioning is an important physical property for the assessment of bioaccumulation and environmental impact. Here, we advance simulation methodology for predicting the partitioning of small molecules into lipid membranes and compare the computational predictions to experimental measurements in liposomes. As a step towards high-throughput screening, we present an automated mapping and parametrization procedure to produce coarse-grained models compatible with the Martini 3 force field. The methodology is general and can also be used for other applications where coarse-grained simulations are appropriate. This article addresses the effect on membrane–water partitioning of adding cholesterol to POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) membranes. Nine contrasting neutral, zwitterionic and charged solutes are tested. Agreement between experiment and simulation is generally good, with the most challenging cases being permanently charged solutes. For all solutes, partitioning is found to be insensitive to membrane cholesterol concentration up to 25% mole fraction. Hence, for assessment of bioaccumulation into a range of membranes (such as those found in fish), partitioning data measured in pure lipid membranes are still informative.

Graphical abstract: Partitioning into phosphatidylcholine–cholesterol membranes: liposome measurements, coarse-grained simulations, and implications for bioaccumulation

Supplementary files

Article information

Article type
Paper
Submitted
23 fev 2023
Accepted
30 apr 2023
First published
02 may 2023
This article is Open Access
Creative Commons BY license

Environ. Sci.: Processes Impacts, 2023,25, 1082-1093

Partitioning into phosphatidylcholine–cholesterol membranes: liposome measurements, coarse-grained simulations, and implications for bioaccumulation

T. D. Potter, N. Haywood, A. Teixeira, G. Hodges, E. L. Barrett and M. A. Miller, Environ. Sci.: Processes Impacts, 2023, 25, 1082 DOI: 10.1039/D3EM00081H

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