Friday, May 31, 2019

The first annual NMRlipids workshop

Twelve contributors participated in the first annual NMRlipids workshop in Berlin from 15th to 17th of May 2019. The flexible schedule included six presentations and a significant fraction of time was devoted to discussions and working towards the goals of the workshop.

The workshop was opened by Samuli Ollila presenting the current status and open issues in the NMRlipids project (slides available here). The presentation was followed by a discussion to determine the main goals of the workshop:
  1. Define a quantitative quality measure for the structural quality of a lipid bilayer simulation.
  2. Create instructions on how to contribute data into the NMRlipids databank.
  3. Create a universal code to visualize lipid structures in simulations (for example, see this figure).
The second day of the workshop was opened by Ivan Gushchin presenting a principal component analysis of lipid structures (slides available from here). This was followed by Patrick Fuchs presenting the status of analysis code to calculate order parameters from united atom simulations, and Tiago Ferreira presenting order parameter experiments using natural abundance 13C NMR. At the end of the second day,  Stephanie Dawson presented publishing possibilities offered by www.scienceopen.com. The third day of the workshop was opened by Ivan Gushchin presenting the relation between lipid bilayer densities and scattering form factors (slides available from here).

The main outcomes of the workshop are listed here (topics 1-3 correspond to the goals listed above and 4-7 are additional outcomes):
  1. A quantitative measure for the structural quality of lipid bilayer simulations. The aim was to define a simple machine and human readable measure for the structural quality of lipid bilayer in simulations using scattering form factors and order parameters. The main applications would be the NMRlipids III project (see post and post and issue) and the lipid databank. For order parameters, the proposal was to measure the distance from experimental values using the size of the error bar as a unit (see the first page in the document). For the form factor, the task turned out to be more complicated and universal quality measure was not yet defined (see the pages 1-2 in the document).
  2. Instructions to contribute data into the NMRlipids databank. The aim was to generate straightforward instructions on how to contribute data into the NMRlipids project in the way to enable automatic analysis and indexing. The suggestion was to update the current indexing system and read the metadata directly from hashtags given in Zenodo descriptions. Preliminary script to pull data from Zenodo was created, but it is not publicly available yet. I have opened an issue for further discussion.
  3. Visualize structural differences between force fields and lipids. The aim was to create a code which automatically visualizes lipid structure by generating figures like this, and analyze the differences between PC, PS, PG and PE headgroup structures as suggested in the NMRlipids IVb project. The code for this was generated, but it is not yet publicly available.
  4. The analysis code to calculate order parameters from united atom models by Patrick Fuchs is progressing, but it is not yet publicly available. The merging with the current order parameters calculation code was superficially discussed. See also the discussion in the blog after the workshop.
  5. In the discussion following the presentation by Tiago Ferreira, we concluded that the sn-1 chain order parameters from natural abundance 13C NMR may be less accurate than 0.02 (the previously used quantitative accuracy of order parameters) due to the spectral overlap. The order parameters from specifically deuterated samples are probably more accurate for this region. This is relevant for the quantitative quality measure and for the NMRlipids III project. Further discussion is in the issue.  
  6. In the discussion following the presentation by Ivan Gushchin about lipid bilayer density profiles and scattering form factors, we concluded that some of the complications in the NMRlipids III project could be potentially resolved by separately analyzing the effect of POPC and cholesterol densities to the form factors from POPC/cholesterol mixture. 
  7. The possibilities of using Markov state modeling presented by Ivan Gushchin (slide 5) to understand lipid structures and transition rates were discussed. 
The workshop was overall successful and the second NMRlipids workshop will be most likely organized at least partially with the same concept.

Explanation how to measure order parameters with 13C NMR

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.