Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

Dear Dr. Najmanovich,

Thank you very much for submitting your manuscript "Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants" 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. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

Both reviewers were positive overall. The first reviewer had concerns primarily  about the presentation. However, the second reviewer had more significant concerns about some of the methodology (glycans) and focused comparison to experimental data, which I think would improve the paper.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

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

[1] A letter containing a detailed list of your responses to the 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.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. 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,

Roland L. Dunbrack Jr., Ph.D.

Associate Editor

PLOS Computational Biology

Arne Elofsson

Deputy Editor

PLOS Computational Biology

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

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: The manuscript describes an interesting and timely computational study of SARS-CoV-2 Spike protein variants and their impact on infectivity. The results will be very useful not only for the scientific community but also for the public health systems. The methodology presented could be of great help to predict the risk of new strains.

It’s well written. It would however beneficiate from a thorough review:

- Page 9: Explain the meaning of “May 08”

- In Figure 3, it is not clear which data are represented in the y-axis.

- Figure 8: Results showed in figure 8 should be better explained in the main text because there are some inconsistencies. Figure legend should be revised.

- It is not clear the usefulness of 3.5 section

- 3.6 section should be better included in Material & Method section

- A final conclusion should be included. Actual conclusions are more like a summary of the manuscript.

Reviewer #2: In the manuscript “Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants” the authors utilize coarse-grained normal mode analyses to model the dynamics of Spike proteins and calculate transition probabilities between states for a number of Spike variants. The results predict an increase in open-state occupancy for the more infectious D614G via an increase in flexibility of the closed-state and decrease of flexibility of the open-state. The manuscript also presents a high throughput analysis of simulated single amino acid mutations on dynamic properties to seek potential hotspots and individual Spike variants that may be more infectious. The authors introduce a Markov model of occupancy of molecular states with transition probabilities derived from our analysis of dynamics that recapitulates experimental data on conformational state occupancies.

The biological problems addressed in this work are of clear fundamental and therapeutic interest and insights from computational approaches are certainly welcome to improve our understanding of the SARS-CoV-2 spike mechanisms and interactions.

Major points:

1.This is a fairly well-executed technical study describing an interesting combination of computational simulation tools to understand mechanisms of SARS-CoV-2 spike proteins in the native and mutant states. Although some of the presented results are certainly very interesting, the manuscript lacks organization, structure and a clearly formulated methodological objective. The overall presentation of the results is fragmented making difficult to understand the logic and methodological details of this work.

2. There is an enormous literature about this manuscript (both computational and experimental) that is only very briefly mentioned in Introduction. The authors should have critically assessed the previous studies and, more importantly, identify key issues and questions unanswered thus far.

3) The performed CG simulations do not apparently include the glycosylation of the spike, therefore strongly reducing the biological relevance of the entire work. Perhaps the authors should consider a model to mimic the glycosylated microenvironment in the framework of CG approaches. Although glycans are not supported by many CG methods which represents an important limitation in adopting this specific computational approach to study fusion viral proteins where glycosylation plays a key role, there exist CG methods ( such as Martini) where the energetic parameters have been recently extended to N-glycans. Glycans have been widely found to be crucial in the modulation of the spike conformational dynamics and should be considered for modeling of spike proteins. The inclusion of glycans to the model could potentially change the results and this comparison would be very important to substantiate the main findings and conclusions.

4) The authors claim that their results correctly model an increase in open-state occupancy for the more infectious D614G via an increase in flexibility of the closed-state and decrease of flexibility of the open-state.

There have been recently cryo-EM structures of a full-length G614 trimer (Structural impact on SARS-CoV-2 spike protein by D614G substitution. Science 2021, 372, 525-530) for distinct prefusion conformations in the closed, intermediate and 1-up open states (pdb ids 7krq, 7krs, 7krr) that characterized previously disordered regions in spike protein. This study supported the reduced shedding mechanism and suggested the increased stability of the G614 mutant. At the same time, another recent work in PNAS ( The effect of the D614G substitution on the structure of the spike glycoprotein of SARS-CoV-2. Proc. Natl. Acad. Sci. U. S. A. 2021, 118, e2022586118, pdb ids 7bnm, 7bnn, 7bno). These G614 mutant structures were more flexible and wide-open which is in line with the increased flexibility of the open state as proposed in the reviewed manuscript. These studies proposed different mechanisms, but it may reflect the diversity of conformational states adopted by the G614 mutant spike trimer.

Given simplicity of the elastic network models, I would suggest testing these structures ( or at least some of them) to try to reconcile conflicting mechanisms and also understand the effect of the G614 structures on the results and predictions.

5. Could the authors more clearly identify what makes their findings novel to biological community? What do the results of this study add to our current knowledge of the role of protein dynamics in these mechanisms?

6. It would be desirable to also use all-atom MD simulations for some of the studied systems to allow for a comparative analysis of protein flexibility. In general, the analysis of computational simulations are not sufficiently justified which weakens their connection with the biological evidence.

7. I believe that the authors should spend some time thinking how to strengthen the interface between experiment and computations in the manuscript to substantiate key findings.

8) Although the system is fascinating and computational approach is generally appropriate, the manuscript often reads as a set of disconnected observations rather than a cohesive story with the detailed analysis and insightful discussion.

9) The results often lack proper interpretation and integration with experiment to justify findings.

10). I believe that the authors should spend some time thinking how to strengthen the interface between experiment and computations in the manuscript to substantiate key findings.

Minor points:

1. The illustrations are often not sufficiently informative and generally very poor. Many of the plots and data cannot be seen at all. The authors should redesign and redo most of these figures and make them better organize, visible and informative with necessary annotations.

2. The manuscript is lacking a systematic statistical framework for assessing significance and quality of predictions. The authors should more clearly formulate and apply their statistical instruments along a common strategy to provide more confidence of quality and reproducibility of their results.

**********

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.

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

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

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 figures@plos.org.

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

Dear Dr. Najmanovich,

We are pleased to inform you that your manuscript 'Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants' has been provisionally accepted for publication in PLOS Computational Biology.

I'm persuaded the new experimental data confirms your calculations and that your paper should be accepted.

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.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

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

Best regards,

Roland L. Dunbrack Jr., Ph.D.

Associate Editor

PLOS Computational Biology

Arne Elofsson

Deputy Editor

PLOS Computational Biology

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