Thursday, May 9, 2019

NMRlipids III: Quantifying intermolecular interactions in binary lipid mixtures

After trying to rationalize the data in the NMRlipids III manuscript, I think that we should emphasize more the evaluation of lipid-cholesterol interactions in binary lipid bilayer against experiments. As far as I know, the quantitative comparison of intermolecular interactions between simulations and experiments has not been done much. Therefore, the procedures in this manuscript could be useful also for other than POPC/cholesterol mixtures.

To facilitate this, I plotted the absolute values of POPC sn-1 acyl chain order parameters as a function of cholesterol concentration from experiments (Fig. 1) and different simulations (slopes*pdf, see also the SI).
Fig 1: Absolute values of sn-1 acyl chain order parameters from experiments (points). The lines are fitted to the values with 0-50 mol % of cholesterol.
The increase is approximately linear below equimolar concentration in both simulations and experiments. To compare the ordering effect of cholesterol between different simulations and experiments, I made a linear fit to the data as a function of cholesterol and plotted the slopes for each carbon segment (Fig. 2).
Fig 2: Slopes of order parameters as a function of cholesterol. Determined by fitting equation SCH(Cchol) =kOPCchol + SCH(0) to the data in Fig 1 (experiment) and slopes*pdf (currently S2-S7 in the SI).
Such a plot enables the comparison of cholesterol ordering effect between different simulations and experiments, even though the data would not be measured exactly at the same concentrations. We could also add some literature data with fewer cholesterol concentrations or other lipid media in this figure for comparison.

In addition, the quantitative quality measure for the force field quality, recently contributed by Hanne Antila, could help to evaluate the intermolecular interactions. Some preliminary results are already in the manuscript, but some details in the analysis may need refinement, see issues 65 and 64 in the MATCH repository.

The most important ToDos to progress the manuscript are listed here:
  1. We need to define a appropriate quantitative quality measure to be used in this manuscript, for discussion see issues 65 and 64 in the MATCH repository.
  2. The changes in cholesterol order parameters upon dilution with POPC could be also analyzed from experiments and different simulations.
  3. Results from Lipid14 simulations with cholesterol model would be useful, see issue 7.
  4. Additional data from the literature could be added in the figure showing acyl chain order parameters slopes (Fig. 2).
  5. Figure showing form factors should be updated after all the form factors are calculated properly and the scaling method for experimental form factors is decided, see issue 18.
  6. Section S1 in the supplementary information about reproducibility of CHARMM36 simulations should be written based on the discussion in issue 4. 
  7. Section S3 in the supplementary information about the effect of undulations on the order parameters should be written based on the discussion in issue 16.
  8. The used accuracy for the experimental acyl chain order should be decided, see issue 15.


  1. Regarding lipid14 simulations: I have experimented with running lipid14 in amber before and can run some dynamics trajectories that are needed. I am responding to the issue-7 thread to see exactly where we are on this and what is missing still.

    1. Depending on what Jesper has already in his repositories, I can contribute to the lipid14 simulations as well.

  2. As suggested, the order parameter slopes could be used to compare the effect of cholesterol between different experiments even though the experimental conditions would not match excatly. One motivation for this would to get another experimental data set for the order parameter changes with cholesterol, in addition to the data by Ferreira et al. Therefore, I calculated the slopes from the measurements of DMPC order parameters as a function of cholesterol published by Urbina et al. and Douliez et al. (todo point 4). The results are shown here:

    Taking into account the uncertainties in the assignment, the results from different DMPC experiments are roughly similar. The slopes from POPC experiments are clearly smaller. This can be explained by the stronger dependence of membrane properties on cholesterol in saturated DMPC membrane than in POPC with one monounsaturated chain, as also observed in Lipid14 simulations by Madej et al.

    In addition to the data by Ferreira et al., POPC order parameters upon addition of cholesterol are measured using SDROSS 13C experiments by Leftin et al. However, it seems to me that they report inconsistent results in their two publications (compare Fig. 4 in Leftin14.pdf and Fig. 7 in

    In conclusion, the two independent DMPC measurements upon addition of cholesterol are roughly similar. For POPC we do not have independent experiments, unless we can figure out why two publications by Leftin et al. seem to give different results for POPC/chol (1:1) mixture.

  3. Since I extended the Slipids, MacRog, and CHARMM36 POPC + cholesterol simulations to 500 ns [1-5], I decided to calculate the diffusion coefficients of POPC from them. They have also been experimentally measured at 313 K using NMR [6], and thus could perhaps fit in this manuscript. I plotted the data here:

    It seems that C36 and Slipids capture the effects of cholesterol, but MacRog does not. I'd be happy to extract the values for Berger and Lipid14 as well, but ~500 ns simulations are required.

    There is an obvious problem though, as the hydrodynamic correction [7] should be included. This is tedious to estimate, as each model with each cholesterol concentration would have to be simulated for long enough times (~500 ns) at multiple system sizes. The correction is added (not multiplied) to the curves. However, since the membrane viscosity is not constant over cholesterol concentrations, the correction is not equal for them either. If anyone has ideas on how to proceed, please let me know. Or we can just ditch these data entirely.

    [6] DOI:10.1016/S0006-3495(03)70033-2
    [7] DOI:10.1021/acs.jpcb.6b05102


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