chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling

Dear Prof. Stoll,

Thank you very much for submitting your manuscript "chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

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Arne Elofsson

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Reviewer's Responses to Questions

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Reviewer #1: In their article "chiLife: An open-source Python package for in silico spin labelling and integrative protein modelling", Tessmer and Stoll present a very nice piece of software that can be easily integrated into other Python code, allowing programmers to easily attach ensembles of spin labels to protein models and perform a number of calculations with such models.

The package is well designed, open source and the description in the paper is very good. The authors have included a number of examples and code listings which will make it easy for users to learn how to use the library.

This library will be an important addition to the field of spin-labelling EPR and I think, due to the way it is constructed, it will also be very useful in other fields such as FRET.

It would be great if the package could also work with nucleic acids. I guess, such a feature is already on the list for an upcoming version.

I recommend publication of this paper.

Some minor points:

1.It is not entirely clear to me how the fetch method deals with models that have multiple copies in the ASU - is it possible to fetch a specific chain of the model, e.g. using xl.fetch('1omp_A') or something similar? Will the user be warned that there are multiple chains?

2.PDB files sometimes contain ligands and solvent molecules that can interfere with calculations but are difficult to detect automatically. Sometimes it makes sense to include them, sometimes not. It would be great if the program could output a stripped-down version of the input .pdb file, containing all the atoms used in the calculations. Is such a method already included?

3.Are bipedal spin labels such as Rx or the Cu-NTA label supported?

Reviewer #2: In the article 'chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling' the authors publish an truly useful follow-up article to their landmark paper 'Comparative evaluation of spin-label modeling methods for protein structural studies'. In the article the authors introduce and further provide detailed insights to chiLife package. The chiLife package has the capability to correctly model paramagnetic labels on biomolecuels that eventually lead information such as their distance between them and solvent accessibility. However the most striking ability is that it is written fully in python that makes it freely accessible and foremost easily integrated into other programs such as NIH-Xplor, pyRosetta and others. This is a big step forward to programs such as DeerRosetta and MMM.

The authors lead the reader through the article with numerous examples that become widely accessible to the none-EPR expert. Most important the reader can subsequently integrate chiLife in his/her own research. I deeply enjoyed and appreciated the overlap between the experimental and simulated distances presented in figure 1 and 7, that show the correct modeling approaches used in the publication. I appreciate the ease on how to add costume labels to chiLife that will become more useful in the timeline of bio-molecular EPR. Once labels are added to the biomolecule the local environment can be repacked via customized scoring function. Now while repacking has been applied to many systems before, here the authors introduce a 'scoring function', which gives the user the ultimate freedom to apply to wide range of systems that stretch further than the normal protein system. However I would like to have more information on how to apply those scoring function.

Lastly the authors treat an under estimated strength of EPR, which is the membrane docking function and solvent accessibility. Since the age of Hubell and side directed spin labeling researchers have used EPR to get information on localized environment that changes upon applying molecular stimuli. Specifically a study by Ralf Langen treated the membrane remodeling ability introduced by the bar domain. Here, we have a tool that can correctly interpret such data and see domain reorientation that introduce specific biological functions.

Overall, I want to recommend the article for publication. One slight addition would be a specific outline on how to install the software, which is in detail provided on the chiLife website with all other tutorials (see 'Availability').

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes: Thomas Schmidt

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References:

Review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. 24 Feb 2023 27 Feb 2023

Dear Prof. Stoll,

Thank you very much for submitting your manuscript "chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations. Please address the minor criticisms of the reviewers and we can move the manuscript to full acceptance.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Alexander MacKerell

Academic Editor

PLOS Computational Biology

Arne Elofsson

Section Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact gro.solp@loibpmocsolp immediately:

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at gro.solp@serugif .

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5 .

Reproducibility:

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

References:

Review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. 10 Mar 2023 16 Mar 2023 28 Mar 2023

PCOMPBIOL-D-22-01886R2

chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling

Dear Dr Stoll,

I am pleased to inform you that your manuscript has been formally accepted for publication in PLOS Computational Biology. Your manuscript is now with our production department and you will be notified of the publication date in due course.

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