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Communication
Peer-Review Record

Using In Silico Methods to Identify Protein Tyrosine Kinase A (PtkA) Homolog in Non-Tuberculous Mycobacteria (NTM)

Kinases Phosphatases 2024, 2(4), 340-345; https://doi.org/10.3390/kinasesphosphatases2040022
by Swati Jaiswal 1,* and Sanjay Kumar 2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Kinases Phosphatases 2024, 2(4), 340-345; https://doi.org/10.3390/kinasesphosphatases2040022
Submission received: 7 October 2024 / Revised: 8 November 2024 / Accepted: 22 November 2024 / Published: 30 November 2024

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

In this communication, the authors checked for PtkA homologs across different bacterial species by in silico methods. These kinase homologs should be the subject of further studies to understand their role in pathogenic species and their possible implementation in therapeutic strategies.

The aim of the report sounds interesting but a few paragraphs are not fully clear, for example the section in which the authors generate protein homology models and predict possible protein-protein interaction. A few typos should also be addressed.

My detailed comments are the following:

-maybe in the title it's more correct to use "methods" and "homologs" 

-line 44: it is not clear the sentence "the downregulation of Wag31 (identical to Ag 84) Rv2145c and Ag 85c (Rv0129c)". Are you mentioning protein homologs? 

-line 68-69: the sentence seems incomplete. When you write [Model] do you mean Alpha Fold model? In this case maybe you can write [AF model]. Generally, it is not clear what experimental and predicted models are. In line 69 you reported PDB codes for Rv2234 and Rv0153c but in the caption of Figure 2 you wrote that they are AF predicted models. Please better specify how you obtained the protein structures.

-Figure 2 caption: what indicate red regions on the proteins? Please specify in the caption. pTM is an AF parameter to assess structure prediction quality please mention it somewhere.

-Table 2: please mention in the caption the software used to predict interaction probability

Author Response

In this communication, the authors checked for PtkA homologs across different bacterial species by in silico methods. These kinase homologs should be the subject of further studies to understand their role in pathogenic species and their possible implementation in therapeutic strategies.

The aim of the report sounds interesting, but a few paragraphs are not fully clear, for example the section in which the authors generate protein homology models and predict possible protein-protein interaction. A few typos should also be addressed.

 

My detailed comments are the following:

-maybe in the title it's more correct to use "methods" and "homologs" 

Author’s response: Thanks for the suggestion. We have revised the title and use 'methods' but keeping homolog as singular,

-line 44: it is not clear the sentence "the downregulation of Wag31 (identical to Ag 84) Rv2145c and Ag 85c (Rv0129c)". Are you mentioning protein homologs? 

Author’s response: We have revised the sentence to make it more clear for the readers. These are examples suggesting the role of PtkA-mediated phosphorylation in mycobacteria.

-line 68-69: the sentence seems incomplete. When you write [Model] do you mean Alpha Fold model? In this case, maybe you can write [AF model]. Generally, it is not clear what experimental and predicted models are.

Author’s response: Thanks for the suggestion, same updated on the revised manuscript.

In line 69 you reported PDB codes for Rv2234 and Rv0153c but in the caption of Figure 2 you wrote that they are AF predicted models. Please better specify how you obtained the protein structures.

Author’s response: Thank you for your suggestion. Previously similar homologs PDB names were used but later we updated with alpha fold /AF models those are pretty accurate models compared to PDBs, but we forgot to update on manuscript. We have revised the manuscript accordingly. 

-Figure 2 caption: what indicates red regions on the proteins? Please specify in the caption. pTM is an AF parameter to assess structure prediction quality please mention it somewhere.

Author’s response: We use three color combinations for presenting the secondary structure of proteins. Helices in Yellow, Sheets in Red, and coils/loops in Cyan color. The predicted AF model score is mentioned in the figure 2 caption.

-Table 2: please mention in the caption the software used to predict interaction probability.

Author’s response: We used InterProScan online program for predicting protein-protein interactions. Thanks, we have revised the manuscript accordingly.

Reviewer 2 Report

Comments and Suggestions for Authors

 

The study under review delves into this complexity by investigating the presence of PtkA, a protein tyrosine kinase crucial for Mtb's growth, stress response, and virulence, and assesses whether similar homologs exist in NTM species. Through in silico methods, including sequence alignment, structural modeling, and functional prediction, the authors leverage computational tools such as BLAST and pYMOL (?) to identify potential PtkA homologs in NTM genomes. This approach aims to know  the molecular basis of NTM virulence and resistance, offering a valuable starting point for future laboratory validation and potentially guiding therapeutic strategies. This review will critically assess the methodologies, findings, and implications of this research, situating it within the broader context of NTM pathogenicity and the ongoing quest for effective interventions.

 

Problem is that pYMOL was mentioned in the abstract but did not appear again in the methodology or other parts of the paper. If the software was used, the process should be included in the methodology. If another software was used instead, the abstract should be amended.

Hence, this reviewer reject this paper but permit to authors to resubmit to kinase and phosphatse

Comments on the Quality of English Language

recheck it

Author Response

The study under review delves into this complexity by investigating the presence of PtkA, a protein tyrosine kinase crucial for Mtb's growth, stress response, and virulence, and assesses whether similar homologs exist in NTM species. Through in silico methods, including sequence alignment, structural modeling, and functional prediction, the authors leverage computational tools such as BLAST and pYMOL (?) to identify potential PtkA homologs in NTM genomes. This approach aims to know the molecular basis of NTM virulence and resistance, offering a valuable starting point for future laboratory validation and potentially guiding therapeutic strategies. This review will critically assess the methodologies, findings, and implications of this research, situating it within the broader context of NTM pathogenicity and the ongoing quest for effective interventions.

 

Problem is that pYMOL was mentioned in the abstract but did not appear again in the methodology or other parts of the paper. If the software was used, the process should be included in the methodology. If another software was used instead, the abstract should be amended.

Author’s response: Thanks for your feedback and pointing out the mistake. We have revised the abstract.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Authors replied correctly to comments

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