Dear Prof. Carbone,

Thank you very much for submitting your manuscript "From complete cross-docking to partners identification and binding sites predictions" 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.

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).

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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,

Rachel Kolodny

Associate Editor

PLOS Computational Biology

Nir Ben-Tal

Deputy 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: Dequeker et al. present a protein-protein cross docking approach to identify binding partners for a given set of proteins. It is based on previous work by the Carbone group and indicates significant improvements. Prediction of potential binding partners of proteins is one major goal of bioinformatics and computational biology. The route taken by the authors is interesting and differs from other approaches (mostly based on machine learning trained by experimental input data). The prediction is based on cross docking of all against all proteins in the data set (structures of the proteins need to be known). The approach has the potential to identify protein-protein interaction pairs that cannot be detected based on homology to some known interacting pair. I have, however, some comments:

1. Although the approach is quite clearly explained the scoring and selection of correct complexes is sometimes difficult to understand. As a scoring function the authors use a product of overlap of the interface of a docked structure and the Energy of the docked complex and the pair potential energy. It is not clear why the authors use here a product (as interaction index) and not for example the sum of these contributions (appropriatly weighted).

2. In the scoring the authors use a predicted "reference interface" (not the real native interface) for comparison with a docking interface. This type of reference interface may differ from the correct "native interface". Did the authors check how often this is the case? In such case an incorrect structure would be favored by the score!

3. The authors identify the "correct" partner for a protein with reasonable accuracy (AUC 0.67) and claim that there are only few predicted alternative high affinity (incorrect) complexes. However, my impression by looking at Fig. 2 is that there are quite a number of "dark" spots in the interaction matrix such that there are something like 10-20 putative PPIs for each given protein (on average)?

4. I think it could be useful to look in more detail at some of the "incorrect" predictions. What is the main reason that some incorrect predicted complexes get high interaction scores and hence would be predicted as forming a realistic complex? This is not dicussed.

5. The approach is very computationally demanding which could be a major drawback in putaitve applications. The authors should extend the discussion section to indicate possible sets of proteins (containing a limited number of partners) for which an application of the approach could be useful.

Reviewer #2: Prediction of protein-protein interaction networks is one of the most important biological problems. Experimental techniques for determination of such networks, based on high-throughput methodologies are known to be not very accurate. Computational approaches based on sequence information have been around for a long time, and also suffer from limited accuracy. This study continues the authors' series of publications addressing this issue from the perspective of structural modeling, which is a useful complement to the experimental and sequence-based techniques. In this study, the authors added more structural and physicochemical parameters to their previously used set. The new, expanded set showed a significantly better discrimination power to the non-cognate interactors, thus considerably improving the utility of the method. The paper contains detailed analysis of the approach, parameters variation, and performance on the general and function-specific protein-protein sets, as well as comparison with alternative approaches. The approach is a useful addition to the arsenal of computational techniques for characterization of protein interactions, and as such would be of interest to the biological community.

Reviewer #3: The authors propose a molecular docking approach to predict protein partners and interaction strength. They assessed their algorithm for recovery of known and predicted protein-protein interactions, finding that their algorithm improves upon previous partner identification methods, although it is outperformed by a deep learning method.

MAJOR CONCERNS

The pair extension by homology is fundamental to the paper, but the authors do not provide sufficient evidence for its validity, or for the thresholds used. The authors acknowledge its limitation, but do not provide sufficient explanation or references. “We considered that a structurally characterized interaction found for P1′ and P2′, homologs of P1 and P2, respectively, was a strong indicator of the possibility for P1 and P2 to interact with each other. Nevertheless, we should stress that homology transfer does not guarantee that the interaction between P1 and P2 is functional in the cell.“

The docking-based partner prediction approach shown here is significantly outperformed by existing machine learning methods (AUC 95% versus 79% recovery of known and inferred partners). The authors are not convincing in the need for their method given the poor performance compared to existing methods.

Authors use different levels of homology to define true pairs between different datasets and figures (Figure 2, 5).

The probability at random (grey bars) in figure 2b is unclear.

Figure 5a inset is unclear, what are the grey bars? Additionally, this figure does not clearly support “CD2PI identifies at least one known partner in the top 3 for about a third of the 319 proteins (Fig. 5a, inset)”

Figure 5a is unclear. What are the structures shown in colors? Caption describes these structures as known partners, but there are not 6 blue tones for 2r9p:A.

Figure 5b should include all proteins, not just cases where CCD2PI outperforms DPPI

MINOR POINT

“We combine together physics-based energy, interface matching and protein sociability, three ingredients we previously showed to be relevant to partner identification and discrimination.” Lacks citation.

In summary, some figures in the paper are somewhat difficult to interpret. The evidence supporting pair extension by homology is moderate, and the approach is significantly outperformed by existing methods.

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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.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes: Martin Zacharias

Reviewer #2: Yes: Ilya Vakser

Reviewer #3: No

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.

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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 Prof. Carbone,

Thank you very much for submitting your manuscript "From complete cross-docking to partners identification and binding sites predictions" 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 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,

Rachel Kolodny

Associate Editor

PLOS Computational Biology

Nir Ben-Tal

Deputy Editor

PLOS Computational Biology

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

[LINK]

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: I carefully read the new version of the manuscript and the responses to my concerns. I think the authors successfully responded to my concerns. The manuscript is an interesting approach to predict new putative protein-protein interactions. Very recently, AI approaches such as Alphafold2 have become very successful in predicting not only protein structures but also putative protein-protein interactions. I think it could be very valuable for the manuscript to relate/discuss the "docking" approach of the authors vs. emerging AI based approaches to predict complex structure. This could further improve the manuscript.

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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.

Reviewer #1: Yes

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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

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

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.

Dear Prof. Carbone,

We are pleased to inform you that your manuscript 'From complete cross-docking to partners identification and binding sites predictions' 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,

Rachel Kolodny

Associate Editor

PLOS Computational Biology

Nir Ben-Tal

Deputy Editor

PLOS Computational Biology

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