Predicting Transmissibility-Increasing Coronavirus (SARS-CoV-2) Mutations

Round 1

Reviewer 1 Report

In this work, Caliskan and colleagues provide a bioinformatic investigation for the prediction of SARS-CoV-2 S mutations that might enhance the viral contagiousness by associating a machine learning approach with the empirical analysis of the amino acids' chemical properties. The methodology is interesting. However, the main problem is that these data should be integrated with some statistics or a much deeper investigation in the discussion of amino acids resulting critical for the virus infectiveness within the already published data in the literature (i.e. 10.3390/biom11091273), to underline the novelty in their discovery.

Moreover, to enhance the work's value, the authors should build the homology models of the spike protein (or only the RBD) with the mutated amino acids found in their investigations and, if possible, perform MD simulations to provide a model of the mutated residues' exposition to the solvent and thus to the ACE2 receptor.

An extensive review of the English language should be implemented. 

-              Line 36: “Coronavirus 2019 (COVID-19) disease” should be changed in “Coronavirus disease 2019 (COVID-19)

-              Line 57: “S-proteins that are closed … receptor” this sentence is not clear

-              Line 90: “is known to … mutation (E484K)” not clear

-              Since it is a bioinformatic investigation, The “Materials and Methods” section should be renamed as “Methods”

-              In 2.1 there are too few details on the methodology

-              Line 139: “analysis” is repeated twice

-              Line 193: What do the K-means values in the range of 2-12 indicate?

-              Figure 1: the authors should provide a labelling indicating the color code for each group. Moreover, how was the bond strength calculated?

-              Line 220: “This indicates the reliability of our clustering approach” not clear

-              Line 224-227: these lines are exactly the same as lines 204-208.

Author Response

We comprehensively work on each and every comments we received from both the reviewer and updated our manuscripts accordingly. Here is the responses attached with the file.

Author Response File: Author Response.pdf

Reviewer 2 Report

In this article, the author investigated the mutation associated with RBD region and tried to find out which mutations fall into the N501Y and E484K mutations. There are numerous problems in the article in the sense of representation of data and overestimation of the article based on the observed data. I would not recommend this article to be published in its current form. However, the work has potential merits to society in finding mutations related to COVID, so the author needs to revise the whole manuscript very carefully.

There are a few major comments:

1.        It is very hard to interpret the results from Figure 1 and Figure 2. It seems both are similar and even figure captions are the same.

2.        Like Figure 3 and Figure 4. I think the author needs to find a better way to represent the data if both are different.

3. The author characterized the eight features of amino acids; however, some features fall in the same categories. For example, polar amino acids can form H-bonds. Is there any way to shorten or combine similar features together, instead of eight individual features?

4.        In Figure 1, for the K-means clustering algorithm, only four features are shown. Is there any reason to exclude other features in the K-mean?

5.        There are a few minor typos:

a.        page 5, line 199, commas are missing between 10 and 11.

b.        Page 2, line 90, two stop ‘.’ after RBD and before 484.

Author Response

We comprehensively work on each and every comments that we received from both the reviewer and update the manuscripts accordingly. Here we attached the actions that we take for those comments.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

I understand that the authors want to focus mainly on the presentation of the methodology in this paper; however, the resulting data are not sufficiently discussed. This is also crucial to understanding the reliability of the method.

"Our team does not have the data and equipment to perform these analyses. We may ask for your support in this regard." <- regarding this point I am indeed honored by the request, however I have to decline due to a lack of time.

As before.

Author Response

Thank you for providing the review comments to improve our paper. We make changes accordingly and provide the details in the cover latter.

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors fulfil all my concerns. I don't have any further comments on the article. The article can be published in its current form. 

I don't have any further concerns and issues with the reviewed article.

Author Response

Thank you for providing the review remarks to improve our paper. We updated accordingly and details are included in the cover latter and updated paper.

Author Response File: Author Response.pdf