PCOMPBIOL-D-25-02364

Clustering of SARS-CoV-2 membrane proteins in lipid bilayer membranes

PLOS Computational Biology

Dear Dr. Gopinathan,

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Kind regards,

Arli Aditya Parikesit, PhD

Academic Editor

PLOS Computational Biology

Arne Elofsson

Section Editor

PLOS Computational Biology

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Based on reviewers' report, it is clear that extensive revision to the manuscript is imperative. Please kindly do the needful, and incorporate the letter of reply to the reviewers along with your revised manuscript.

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At this stage, the following Authors/Authors require contributions: Michael E. Colvin, Thomas E. Kuhlman, Siyu Li, Joseph McTiernan, Umar Mohideen, Roya Zandi, Yuanzhong Zhang, and Ajay Gopinathan. Please ensure that the full contributions of each author are acknowledged in the "Add/Edit/Remove Authors" section of our submission form.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: This manuscript integrates long-timescale all-atom MD simulations, continuum modeling using a Cahn–Hilliard framework, and AFM imaging to quantify the interplay between direct M–M interactions and membrane-mediated forces in driving SARS-CoV-2 M protein clustering. The work aims to define the critical interaction energies and protein densities required for the onset of cluster formation, with implications for viral assembly mechanisms.

Overall, the study addresses a biologically important question and employs a rigorous multiscale approach. The manuscript is clearly written and technically sound, but certain aspects need clarifications, methodological justification, and better contextualization within coronavirus biology.

Major,

1, While the physics-based treatment is elegant, the biological implications are underdeveloped. The conclusion that “direct M–M interactions dominate over membrane-mediated interactions” is quantitatively supported, but the structural basis of such interactions is not discussed. Structural models of M dimers (short vs long forms) and known oligomerization interfaces should be incorporated into the interpretation.

2, The manuscript should discuss how the estimated interaction energies (≈ 7.8–9.6 kBT) compare to known coronavirus M protein oligomerization data, and viral assembly thresholds in other enveloped viruses.

3, The discussion would benefit from a clearer explanation of whether the derived critical densities are physiologically plausible in ERGIC membranes.

Minor,

1, Recent cryo-EM studies on coronavirus M oligomeric states should be more thoroughly cited.

Reviewer #2: This manuscript presents an important multiscale investigation of SARS-CoV-2 M-protein clustering using all-atom MD, continuum Cahn–Hilliard modeling, and AFM imaging. The topic is timely, the methods are generally robust, and the results offer quantitative insight into M–M interactions during early viral assembly. The work has clear potential for publication.

However, several issues require clarification before acceptance:

Continuum Model Assumptions:

The model neglects curvature–composition coupling despite the known curvature effects of M proteins (e.g., Introduction, lines 63–71). The authors should justify the flat-membrane approximation and discuss how it may shift critical interaction energies or densities.

Line Tension Estimation:

The thinning-induced line tension (~0.1 kBT/nm) relies on generic elasticity parameters rather than system-specific values. A sensitivity analysis or clearer limitations is needed.

AFM Area Coverage Determination:

Protein coverage estimates depend heavily on threshold selection (S7 Fig). The lowest-density image uses a threshold borrowed from another dataset, which may bias results. A robustness check is recommended.

Mismatch at Higher Densities:

Simulations at 2ρ* and 3ρ* show strong coarsening (Fig. 5c–d), unlike AFM images. The authors should discuss whether biological membranes exhibit mechanisms that arrest phase separation, which are not included in the model.

Applicability of Linear Stability Analysis:

The interaction energy ϵm derived from AFM spacing uses a linear-regime expression (Eq. 15), while AFM patterns are fully nonlinear. The authors should justify this extrapolation or clarify its limitations.

Despite these concerns, the manuscript is promising and would merit publication after major revision.

Reviewer #3: the review is uploaded as an attachment

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Submitted filename: Reviewer_Report_PLOSONE Comp.docx

Dear Prof. Gopinathan,

We are pleased to inform you that your manuscript 'Clustering of SARS-CoV-2 membrane proteins in lipid bilayer membranes' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology.

Best regards,

Arne Elofsson

Section Editor

PLOS Computational Biology

Arne Elofsson

Section Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: The authors have adequately addressed all my concerns, and I have no further comments.

Reviewer #2: the manuscript can be accepted in this form

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

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Reviewer #1: No

Reviewer #2: No