Quantitative Comparison against Experiments Reveals Imperfections in Force Fields’ Descriptions of POPC–Cholesterol Interactions

Abstract

Cholesterol is a central building block in biomembranes, where it induces orientational order, slows diffusion, renders the membrane stiffer, and drives domain formation. Molecular dynamics (MD) simulations have played a crucial role in resolving these effects at the molecular level; yet, it has recently become evident that different MD force fields predict quantitatively different behavior. Although easily neglected, identifying such limitations is increasingly important as the field rapidly progresses toward simulations of complex membranes mimicking the in vivo conditions: pertinent multicomponent simulations must capture accurately the interactions between their fundamental building blocks, such as phospholipids and cholesterol. Here, we define quantitative quality measures for simulations of binary lipid mixtures in membranes against the C−H bond order parameters and lateral diffusion coefficients from NMR spectroscopy as well as the form factors from X-ray scattering. Based on these measures, we perform a systematic evaluation of the ability of commonly used force fields to describe the structure and dynamics of binary mixtures of palmitoyloleoylphosphatidylcholine (POPC) and cholesterol. None of the tested force fields clearly outperforms the others across the tested properties and conditions. Still, the Slipids parameters provide the best overall performance in our tests, especially when dynamic properties are included in the evaluation. The quality evaluation metrics introduced in this work will, particularly, foster future force field development and refinement for multicomponent membranes using automated approaches.

Overlay databank unlocks data-driven analyses of biomolecules for all

“… 15 , 16 , 52 – 56 and the X-ray scattering data from refs. 56 – 62 . In addition, previously unpublished NMR data for POPE, POPG, and DOPC was acquired as described in Supplementary Figs.…”

Martini 3 Coarse-Grained Force Field for Cholesterol

“…This is particularly clear when looking at the percentual increase in thickness relative to pure lipid bilayers (Figure S9), which shows that the Martini 3 model consistently yields a larger increase in thickness compared to Martini 2. It is also worth noting that a recent comparison of AA cholesterol-POPC models found an overall overestimation of the cholesterol thickening effect upon the addition of over 20% cholesterol . This observation hints that the underestimation of cholesterol-induced thickening by the Martini models relative to AA references may not be as critical as previously thought.…”

Evaluating Polarizable Biomembrane Simulations against Experiments

“…X-ray scattering form factors | F ( q )| (leftmost column); and the C–H bond order parameters S CH for headgroup and glycerol backbone (second column from left), sn–1 (second column from right), and sn–2 acyl chains (rightmost column) compared between simulations (red) and experiments (black) using the NMRlipids Databank. The experimental data were originally reported in refs , , , . For the CHARMM-Drude2023 simulations, we selected representative replicas among the three available ones (for all POPC replicas, see SI Figure S1).…”

“…Our previous efforts in benchmarking state-of-the-art nonpolarizable lipid force fields have demonstrated that the quality of predictions for important membrane properties greatly varies between different force fields, particularly for lipid headgroup conformational ensembles and ion binding affinities. − While the ability to capture these membrane properties correctly is important in its own right, it also creates the basis for the description of more complex systems: For example, ion binding affinity regulates membrane surface charge, and having a wide variety of conformations available for lipid headgroups appears essential for capturing realistic protein–lipid interactions . Consequently, such benchmark studies are also urgently needed for polarizable lipid force fields, in particular considering the increased computational cost they come with and their pledge to capture a broader range of physical phenomena at the polar membrane regions.…”