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Thanks for the text update. There are no more critical remarks. The topic is important itself. I believe the topic of novel drug candidate against COVID-19 using natural compounds could be extended in series of new studies.
Authors have corrected their manuscript to some extent.
Authors have corrected their manuscript to some extent.
Authors have corrected their manuscript to some extent.
Authors have corrected their manuscript to some extent.
There are no remarks on science content, only on the text presentation. To follow the publication standards please check English again asking a professional agency or fluent English speaker.
After the update, we may accept it for publication without an additional reviewing round.
[# PeerJ Staff Note: The Academic Editor has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at [email protected] for pricing (be sure to provide your manuscript number and title) #]
The authors implemented some changes regarding my comments.
But still, this manuscript needs English checking preferably with native speaker.
The authors implemented some changes regarding my comments.
But still, this manuscript needs English checking preferably with native speaker.
The authors implemented some changes regarding my comments.
But still, this manuscript needs English checking preferably with native speaker.
The authors implemented some changes regarding my comments.
But still, this manuscript needs English checking preferably with native speaker.
Professional article structure, figures, tables are shared.
Methods described in detail and information with possibility of replication
All underlying data have been provided in revised manuscript; they are robust & controlled
The authors addressed all comments.
Thank you for the updates. Major remarks are fixed now. But there are still some remarks for data comparison and cross-validation. Please compare compounds reported using existing databases of chemical compounds such as ChEMBL, PubChem as noted by reviewer #1.
Compare your results with the prediction results of the web-services of biological activity prediction. There are recent publications on ACE2 modeling. Please add it at least to the discussion. Take more time for revision, if you need it. Waiting your revised manuscript.
I thank the authors for submitting to PeerJ.
I have some major comments that should be taken into account.
Please correct English (a few sentences are wordy and somehow unclear. For instance, the sentence: "AutoDock is an automated suite of protein-ligand docking tools that are designed to predict protein interactions with small molecules." can be replaced by the similar from the author's responce: "AutoDock is an automated suite of protein-ligand docking tools used to predict the protein interactions with small molecules such as drug molecule and substrate"., etc).
1. If the authors used a few compounds that can be potential inhibitors against ACE2, could they provide the explanation, why the authors used only those three compounds, that they mentioned?
2. I strongly recommend to add any results of analysis of the compounds using existing databases of chemical compounds such as ChEMBL, PubChem (for instance, exact search or similarity search). Also, it would be great, if the authors can complete their studies by the prediction results of the web-services of biological activity prediction and demonstate the association between the results of prediction and their findings.
I think that the authors should provide more data to prove their findings. For instancem they should add the results of the biological activity prediction or target affinity based on the publicly accessible web-services for prediction of either biological activity and/or target affinity.
I thank the authors for submitting to PeerJ.
I have some major comments that should be taken into account.
1. Please correct English (a few sentences are wordy and somehow unclear. For instance, the sentence: "AutoDock is an automated suite of protein-ligand docking tools that are designed to predict protein interactions with small molecules." can be replaced by the similar from the author's responce: "AutoDock is an automated suite of protein-ligand docking tools used to predict the protein interactions with small molecules such as drug molecule and substrate"., etc).
2. I think that you should provide more data to prove their findings. For instance, you should add the results of the biological activity prediction or target affinity based on the publicly accessible web-services for prediction of either biological activity and/or target affinity.
Kind regards.
After through check with manuscript (track changes) it is evident that authors have amended necessary changes in key areas (Introduction, Methodology, Results, Discussion and Conclusion) with Tables and Figures. Furthermore, the literature is revised with references.
Methods described in detail and information with possibility of replication
All underlying data have been provided; they are robust & controlled.
Authors have amended the manuscript and addressed all the queries raised. The manuscript can now be accepted in present revised form.
We got two reviews suggesting reject the manuscript in its current form. I think the presentation of the material should be improved. Please use the detailed comments from the reviewers. I encourage revise the text, justify the selection of the natural compounds (traditional medicine), and extend the computing. Please note the PeerJ journal policy on molecular docking calculations below.
The topic for coronavirus drug design is really important, but it is very competitive field. Please cite recent literature and approaches.
You are welcome to resubmit the manuscript to PeerJ after revision.
PeerJ policy is that submissions that screen molecules based on network pharmacology or molecular docking calculations must validate the candidate molecules either experimentally, or through molecular dynamics simulations. If the molecular dynamics route is selected, then duplicated simulations (at least 50 ns each) should be conducted on the best ligands (https://peerj.com/about/policies-and-procedures/#discipline-standards).
[# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #]
[# PeerJ Staff Note: The review process has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at [email protected] for pricing (be sure to provide your manuscript number and title) #]
In my opinion, this manuscript has serious issues and cannot be published in its current form:
1) The authors do not provide any rationale under the necessity to inhibit the ACE2 receptor to fight COVID-19. Are ACE2 receptor inhibitors safe? Why inhibition of ACE2 is preferred in comparison with inhibition of SARS-CoV-2? It is not clear from the text of the manuscript.
2) The authors prepared the models of protein (ACE2 receptor), then they prepared the molecular docking and molecular dynamics of the complex protein-inhibitor. So if there is a low resolution of the model, therefore, the results of molecular docking and molecular dynamics are not characterized by high accuracy. I think the better strategy is, to use ligand-based methods, or at least to try to obtain the training set of known ACE2 receptors inhibitors and to make a conclusion whether the ligand-based drug design is suitable in this task.
3) The paper has many typos and unclear phrases:
"Coronavirus contains a genome of approximately 30kb and consists of a 5' cap structure and 3' poly(A) tail that allows it to act as an mRNA for the translation of the
replicase polyproteins. At the beginning of each structural or accessory gene, there is the
presence of transcriptional regulatory sequences (TRSs) which are essential for the expression of each of these genes." Is this phase related to the general idea of the text?
"The available 2D & 3D structures of compounds were retrieved from the PubChem database (Ref)" Is it correct reference here?
"(Palmitoyl Oleoyl Phasphatidyl chlorine" - there is a typo
etc.
1) The authors do not provide any rationale under the necessity to inhibit the ACE2 receptor to fight COVID-19. Are ACE2 receptor inhibitors safe? Why inhibition of ACE2 is preferred in comparison with inhibition of SARS-CoV-2? It is not clear from the text of the manuscript.
2) The authors prepared the models of protein (ACE2 receptor), then they prepared the molecular docking and molecular dynamics of the complex protein-inhibitor. So if there is a low resolution of the model, therefore, the results of molecular docking and molecular dynamics are not characterized by high accuracy. I think the better strategy is, to use ligand-based methods, or at least to try to obtain the training set of known ACE2 receptors inhibitors and to make a conclusion whether the ligand-based drug design is suitable in this task.
3) It is not clear why the authors chose Autodock 1.5.6 for molecular docking.
'no comment', please see "1. Basic reporting" field
Dear authors,
you have presented the results regarding the search for the potential ACE2 receptor inhibitors as the potential compounds for treatment COVID-19. Despite the fact, that in general, the idea is interesting, I'd recommend you to provide the answers to the comments given in the "1. Basic reporting" section. In particular, the main question is why the authors decided to model the ACE2 receptor and to find its inhibitors. What are the advantages of such a method? Some more comments are provided in the "1. Basic reporting" and "2. Experimental design" sections, I've copied and pasted it below for the convenience:
1) The authors do not provide any rationale under the necessity to inhibit the ACE2 receptor to fight COVID-19. Are ACE2 receptor inhibitors safe? Why inhibition of ACE2 is preferred in comparison with inhibition of SARS-CoV-2? It is not clear from the text of the manuscript.
2) The authors prepared the models of protein (ACE2 receptor), then they prepared the molecular docking and molecular dynamics of the complex protein-inhibitor. So if there is a low resolution of the model, therefore, the results of molecular docking and molecular dynamics are not characterized by high accuracy. I think the better strategy is, to use ligand-based methods, or at least to try to obtain the training set of known ACE2 receptors inhibitors and to make a conclusion whether the ligand-based drug design is suitable in this task.
3) It is not clear why the authors chose Autodock 1.5.6 for molecular docking.
4) The paper has many typos and unclear phrases:
"Coronavirus contains a genome of approximately 30kb and consists of a 5' cap structure and 3' poly(A) tail that allows it to act as an mRNA for the translation of the
replicase polyproteins. At the beginning of each structural or accessory gene, there is the
presence of transcriptional regulatory sequences (TRSs) which are essential for the expression of each of these genes." Is this phase related to the general idea of the text?
"The available 2D & 3D structures of compounds were retrieved from the PubChem database (Ref)" Is it correct reference here?
"(Palmitoyl Oleoyl Phasphatidyl chlorine" - there is a typo
I suggest that the authors either (i) choose another target for designing the potential drugs for the treatment of COVID-19 or (ii) provide the rationale of the usage of the ACE2 receptor as a target. Then, I suggest that the authors consider ligand-based drug design if there are inhibitors of the ACE2 receptor (or another chosen target) instead of 3D modeling methods, in case, when the 3D structure of the protein target is unknown.
Sincerely.
The present study explores the potential of human Angiotensin-converting enzyme 2 (ACE2) receptor as the target for the designing of the drug against the deadly virus and marks an attempt to identify novel therapeutic inhibitor against novel SARS-CoV-2 using the Insilico drug discovery approach
1. Basic reporting
a. There is scope for improvement in Introduction, Discussion and Conclusion
b. Structure conforms to PeerJ quality; however, results, discussion and conclusion needs to be separated for better understanding of the international audience.
c. Figures are relevant and labelled. Authors need to highlight relevant figures in text (Section-Results/discussion wherever applicable) because they refer only Fig 3, Fig 4, and Fig 5 only in the text. Interestingly there are 11 figures in total in support of their findings.
Methods described in detail and information with possibility of replication
a. All underlying data have been provided; they are robust & controlled.
b. The conclusion is weak and very much limited supporting results.
a. Your introduction needs to be improved. I suggest that you add more relevant citation in support of your claims from lines 65-74; 78-79.
b. Highlight the text with suitable Figure or Table to familiarize or to engage audience/readers in lines from 75-130.
c. Fix typo errors thirty (Line 54); Ref? (Line 156); photochemical (line 252; phytochemical)
d. Line 39-In the present study; Line 55-proteins; 55-56 sentence needs to rephrase; Line 65-74-this statement needs to be supported with more references; Line 78-79 reference missing for claim; Line 131-141support with references; Line 188-Results. English language needs to be improvised
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