Peer review of: Backmapping triangulated surfaces to coarse-grained membrane models (2020)

Reviewers' comments: 

Reviewer #1 (Remarks to the Author): 

Overall this is an excellent manuscript on what I think is a game-changing tool; it will be highly 
useful in taking molecular level simulations to the next level in terms of system size. I have no 
problem with the methods - they are demonstrated in the manuscript to work. 

My comments are minor, but ones I feel. should be addressed. They concern the context of the 
present work. The authors provide comparisons to other approaches and indicate how theirs is 
better, but I feel the references to 50 and 51 are confusing- are you saying that the CG/DTS 
implementation is better than the methods employed in these papers? If so please explain how. 
Secondly it would be good to give examples of how current CG studies in the literature would 
benefit from using this approach, for example Jefferies and Khalid J Mol Biol 2020 already showed 
membrane undulations around vesicles, without CG-DTS, what would DTS add here? This is not a 
criticism of the present paper but an opportunity to show what extra the method could do. Also 
could the method be applied to the Fluctuating Finite Element approach of S.A. Harris for example 
see PloS Comp Biol, 2018. 

Finally, it would be good to have a comment on how portions of the CG system could then be 
converted to all-atom detail for fine-grained studies of small patches. 

Overall, I think this is an excellent & timely manuscript that will be undoubtedly be very useful and 
highly cited. 

Reviewer #2 (Remarks to the Author): 

Overall, this manuscript describes a timely and necessary tool to build CG models from 
triangulated meshes. The developers have created an algorithm that improves upon existing lipid 
packing software such as LipidWrapper. By using a pointillism approach and constructing the 
membrane with monolayers, rather than bilayers, the algorithm accounts for the increased number 
of lipids in the outer leaflet compared to the inner leaflet, and thus reduces the amount of time it 
would otherwise take to equilibrate a curved structure. The authors show (in at least one case) 
that their method is able to produce stable conformations ready for production runs. The work 
provides a much needed tool for computational biologists / biophysicists / chemists. The figures 
are clear, the data support the conclusions. The software was provided for review during the 
review process. 

Considerations for additional elaboration in the manuscript: 

1) Do the authors plan to maintain and continue to develop the code? 
2) Could the authors please elaborate on the file types output by DTS and thus required as inputs 
for their algorithm? 
3) Could the authors elaborate on ease of user application, whether the user must modify the 
scripts with the appropriate parameters (such as APL) or whether the parameters are executed as 
arguments in the command line? 
4) The authors describe using an EM tomography map to create their triangulated mesh. Could the 
authors elaborate on the method of triangulation they used to generate their mesh from the 
tomography, and how easily the program could be modified to accept other triangulated mesh files 
(such as: dae, stl, or obj)? 
5) Could the algorithm be easily modified to generate monolayer (rather than bilayer) structures? 
6) The authors claim that they were able to achieve “stable” structures ready for simulation with 
the MARTINI model. For the mitochondrial membrane model, the authors do not comment on 
whether this resulting configuration was stable. Could the authors provide evidence that the 

structure was able to achieve an energy-minimized conformation? Additionally, is the system also 
stable if the headgroup restraints are removed? It seems like a model this complex with such high 
variation in curvature would not be stable with short equilibrations and a very short production 
(2ns). If the system does not achieve a stable conformation, could the authors explain how the 
system evolves and any additional precautions users should take when working with systems like 
this? Could they also provide a general discussion of the challenges and additional considerations 
of working with bilayer systems of “unprecedented” size and shape? 
7) There is a brief discussion on membrane heterogeneity and curvature. Did the authors then use 
an average APL to build the complex systems with heterogeneous membrane compositions? Did 
these membranes take longer to converge? Was there any evidence that the variation in APL 
caused local deformations from the starting mesh or the formation of pores? 

Figure 1 does not have any lettering (A-E) as suggested by the text. 
In the SI-F: first paragraph, final sentence: “backmapped” is misspelled as “backmaped” 

This review was provided by Rommie E. Amaro and Abigail Dommer. 

Reviewer #3 (Remarks to the Author): 

In their manuscript "Backmapping triangulated surfaces to coarse-grained membrane models" 
Pezeshkian et al. describe, with three examples, a computational tool they call TS2CG. The tool 
takes as its input a triangulated surface in 3D and outputs a particle-based description of a 
biomembrane with a corresponding 3D geometry. The latter can then be used for molecular 
dynamics simulations of the biomembrane. 

I strongly believe that software developers should be given the credit they deserve. However, I 
also think that the TS2CG tool does not represent an advance in scientific understanding that is 
likely to influence thinking in the field. To thus end, I do not find the manuscript suitable to be 
published in Nature Communications. More suitable venues would be, e.g., the journals SoftwareX 
or Molecular Simulation. 

With regards to the TS2CG tool itself, I would like to draw the authors' attention to the following 
two points: 

1) Currently the tool matches the areas of the two leaflets. This, however, does not guarantee that 
the preferred local curvature of the CG model agrees with that of the triangulated surface, because 
the area difference of the leaflets does not in fact predict the preferred curvature of the 
membrane, see Biophys. J. 115 1638 (2018), Nano Lett. 19 5011 (2019), and Biophys. J. 118 624 
(2020). 

2) Instead of a one-way script to map a triangulated surface to CG, it would be greatly more 
impactful to create a two-way mapping of the two Hamiltonians, such that the CG simulation 
would have a way of influencing the triangulated surface simulation and vice versa. Connecting the 
two simulations in such a rigorous way into a true multiscale simulation would be highly desirable.