General response:

We sincerely thank the reviewer for their constructive comments and positive assessment of our manuscript. We have addressed each point in detail, clarifying methodological aspects, improving figures and tables, and ensuring consistency throughout the manuscript. All modifications made in response to the reviewer’s comments have been highlighted in yellow in the revised manuscript. Specific responses to each comment are provided below.

Reviewer 1:

1. Graphical abstract

The graphical abstract is clear but would benefit from additional quantitative detail. I recommend that the authors indicate the number of compounds at key stages of the workflow (initial library, post-docking/ADMET filtering, and final hits) directly in the figure. Adding these counts will improve transparency of the screening process and help readers quickly understand the scale and progression of the study from raw phytochemicals to proposed lead candidates.

1. Author response: We have updated the graphical abstract to indicate the number of compounds at each stage: initial library (121 compounds), post-docking filtering (37 compounds), post-ADMET filtering (6 compounds), and final hits (2 compounds). This provides a clear overview of the screening process.

2. Rationale for target selection (NA and F)

In the Introduction, the rationale for selecting neuraminidase (NA) and HMPV fusion protein (F) as targets—particularly in the context of the authors’ prior work on hemagglutinin (HA) and SARS-CoV-2 Mpro—is not fully articulated. The authors should expand the relevant paragraph to: (i) explain how targeting NA and F complements or extends the previous HA/Mpro findings, (ii) justify these proteins as logical choices for a broad-spectrum antiviral strategy, and (iii) clarify how they address distinct, non-redundant steps in the viral life cycle (entry/fusion vs. release). This will strengthen the conceptual framework of the study.

2. Author response: We have expanded the Introduction to justify our target selection. Specifically, we explain that NA and F target distinct steps (viral release and entry/fusion, respectively) and complement our previous work on HA and Mpro. This strengthens the rationale for pursuing a broad-spectrum antiviral strategy.

3. Ligand preparation: optimization details

The Methods state that “for the ligands, the MMFF94 force field and the gradient descent algorithm implemented in Avogadro were applied.” To enhance reproducibility, the authors should specify the convergence criteria used for ligand geometry optimization (e.g., energy or gradient threshold, maximum number of steps, and any stopping conditions). These details are important for others wishing to replicate the ligand preparation workflow.

3. Author response: We thank the reviewer for this valuable comment. To improve reproducibility, the Methods section has been revised to include the detailed ligand geometry optimization parameters used during structure preparation. Specifically, ligand geometry optimization and energy minimization were performed in Avogadro using the MMFF94 force field and the conjugate gradient algorithm with a simple line-search method. The convergence criterion was set to an energy threshold of 10_−⁴ with a maximum of 2500 optimization steps. Following optimization, ligands were prepared in AutoDockTools by assigning Gasteiger charges and adding polar hydrogen atoms. These details have now been incorporated into the revised manuscript to ensure better transparency and reproducibility of the ligand preparation workflow.

4. ADMET: definition of “optimal water solubility”

In the ADMET section, the phrase “all the compounds studied… have optimal water solubility” is vague. The term “optimal” should be replaced or explicitly mapped to the solubility categories used in Table 4 (e.g., soluble, moderately soluble, partially soluble). I suggest that the authors (i) state how many compounds fall into each category and (ii) clearly describe the exceptions (C11, E59, M22) using the same terminology as in Table 4, to ensure consistency between text and table.

4. Author response: We thank the reviewer for this valuable comment. The text now defines solubility categories (soluble, moderately soluble, poorly soluble) as in Table 4. Exceptions (C11, E59, M22) are explicitly described using this terminology.

5. Justification for retaining C11, C5, and M274

The conclusion that “compounds C11, C5, and M274 are generally considered acceptable… justifying their inclusion in the list of candidates for further exploration” is reasonable but should be made more explicit. I recommend that the authors:

• Restate the specific toxicity issues for each compound (C11 and C5: only LD50 < 1000 mg/kg; M274: only a carcinogenicity flag, with other endpoints inactive).

• Clearly indicate that these are in silico leads for further investigation, not ready drug candidates, given the presence of these safety flags.

• Optionally note that their overall ADME/T profiles are more favorable than some discarded molecules and at least one reference drug, which supports their retention as exploratory leads.

These clarifications will make the selection criteria more transparent.

5. Author response: We thank the reviewer for this valuable comment. The revised manuscript now provides a clearer justification for retaining compounds C11, C5, and M274 as exploratory in silico leads for further investigation, based on their overall favorable ADME/T profiles relative to several discarded compounds and reference drugs.

6. ProTox-II outputs: “active/inactive” and probability

In Table 5, ProTox-II results are reported only as “active” or “inactive” for each toxicity endpoint (neurotoxicity, cytotoxicity, carcinogenicity, mutagenicity, hepatotoxicity), without explanation. The authors should:

• Clarify in the Methods or a table footnote that “active” denotes a positive toxicity prediction for that endpoint and “inactive” denotes a negative prediction.

• Include the ProTox-II prediction probabilities (or accuracy/confidence scores) for these calls, at least for key candidate compounds, and specify the probability threshold considered meaningful (e.g., >0.70).

Reporting and interpreting these probabilities will help readers assess the robustness of the toxicity predictions.

6. Author response: We now clarify that “active” denotes a positive toxicity prediction, “inactive” a negative prediction. For key candidate compounds, ProTox-II probabilities are included, with a threshold of >0.70 considered meaningful.

7. Figure 3a: missing legends

In Figure 3a (RMSD of 7sej complexes), some curves appear to lack corresponding entries in the legend, which makes it difficult to identify each protein–ligand trajectory. The authors should ensure that every RMSD curve is clearly assigned to a ligand in the legend (or directly annotated) and that the legend matches the ligands discussed in the Results.

7. Author response: All RMSD curves are now clearly labeled in the legend and annotated in the figure to match the ligands discussed in Results.

Reviewer 2:

Introduction

1. For the paragraph starting with “Viral respiratory infections remain a global public health problem. Influenza A virus and human metapneumovirus (HMPV) are …antiviral therapeutic strategies”. This section appears wordy with repetition (e.g., "high mortality and morbidity"; "epidemiological impact"). Sentences such as "...influenza A, in particular, has been known..." appear fragmented, with comma splices. Another sentence, "...leading to high mortality... particularly among vulnerable individuals such as children and the elderly..." appears awkwardly phrased. The overall section may require rewording for improved readability and originality.

1. Author response: We thank the reviewer for this insightful comment. The paragraph has been revised to improve clarity, readability, and overall flow by removing redundancies, correcting sentence structure issues, and enhancing the academic writing style.

2. For “Neuraminidase (NA) is an enzyme and a well-known viral target, having been the subject of extensive research and development of treatments for influenza A, such as oseltamivir and zanamivir. “The original sentence appears long, dense, and wordy. Phrases like "well-known viral target" are common. Rephrasing the sentence by replacing "well-known" with "key" would add to originality.

2. Author response: We thank the reviewer for this helpful suggestion. The sentence has been revised to improve clarity and conciseness, and the phrase “well-known viral target” has been replaced with “key viral target” to enhance originality and readability.

Material and methods

1. Provide a clear flow of how the phytochemicals were screened. Kindly provide a list of databases used for shortlisting and screening the phytochemicals. Also mention the total number of phytochemicals/phytoconstituents that were used for the purpose of screening.

1. Author response: We thank the reviewer for this valuable comment. The manuscript has been revised to provide a clearer description of the phytochemical screening workflow. Specifically, we have clarified the flow of compound selection and included the databases used for phytochemical retrieval and shortlisting. In addition, the total number of phytochemicals used for virtual screening has now been explicitly stated in the revised manuscript.

2. Since Neuraminidase and fusion proteins are common targets, provide a clear rationale or criteria for selecting them over other target receptors.

2. Author response: We thank the reviewer for this valuable comment. The manuscript has been revised to include a clearer rationale for selecting neuraminidase and the HMPV fusion protein as target receptors. These targets were chosen due to their essential roles in distinct stages of the viral life cycle (viral entry/fusion and viral release), their established relevance as antiviral drug targets (in the case of neuraminidase), and the structural and functional importance of the HMPV fusion protein, which currently lacks approved therapeutics. The revised section also clarifies the multi-target strategy adopted in this study and its relevance for evaluating potential broad-spectrum antiviral phytoconstituents.

3. Kindly note the nomenclature style for PDB entries. Although all capitals are not mandatory, uppercase is the standard convention.

3. Author response: We thank the reviewer for this helpful comment. The manuscript has been revised to ensure consistency in the nomenclature of Protein Data Bank (PDB) entries, and all PDB identifiers have been formatted according to the standard convention in uppercase throughout the manuscript.

4. Both structures of neuraminidase and fusion protein have a resolution of more than 2.5 Angstroms. Please check for structures with better resolution.

4. Author response: We acknowledge the reviewer’s comment regarding the resolution of the PDB structures. Although the structures used—2HT7 for influenza A neuraminidase (2.60 Å) and 7SEJ for HMPV fusion protein (2.51 Å)—have resolutions slightly above 2.5 Å, they represent the highest-resolution experimentally determined structures currently available for these specific targets. Both structures have been widely employed in published studies for molecular docking and molecular dynamics simulations, demonstrating their reliability for computational analyses. Given these factors, these structures were deemed appropriate and scientifically valid for the present study.

5. Were both the proteins subject to energy minimization before docking? If so, then kindly mention that in the methods

5. Author response: We thank the reviewer for this comment. Ligand structures were geometry-optimized and energy-minimized prior to docking using the MMFF94 force field implemented in Avogadro. In contrast, protein structures were not subjected to energy minimization before docking. Only standard protein preparation steps were performed using AutoDockTools, including removal of water molecules and co-crystallized ligands, addition of hydrogen atoms, and assignment of Kollman charges. The Materials and Methods section, specifically subsection 2.2 (Dataset Preparation), including 2.2.1 (Ligands and Protein Preparation), has been revised accordingly to clarify the ligand preparation procedure and to explicitly state that no energy minimization was performed on the protein structures prior to docking.

6. Kindly check for spacing. In section 2.2.2. “Autodocktools “

6. Author response: We thank the reviewer for this helpful comment. The manuscript has been carefully proofread and corrected to fix spacing and formatting issues throughout the text, including the term “AutoDockTools” in section 2.2.2, to ensure consistency and adherence to proper nomenclature.

7. For Figure 2 B, it would be recommended to modify the image of the protein to highlight the binding residues better. Also mention (a) and (b) in the figure.

7. Author response: We thank the reviewer for this helpful suggestion. Figure 2 has been revised to improve the visualization of the binding sites, with better highlighting of the interacting residues to enhance clarity. In addition, the figure has been updated to include panel labels (a) and (b) to better distinguish the two protein structures.

8. In section 2.5, please check the position of the charges. They need to be superscripted. Kindly check the entire manuscript for the same and maintain consistency. “Na+ and Cl− ions “

8. Author response: We thank the reviewer for this helpful comment. The manuscript has been carefully revised to correct the formatting of ionic charges, and all charges (e.g., Na⁺ and Cl−) have been superscripted consistently throughout the text.

Results

1. Figures of the protein-ligand docked complexes need to be shown. And the molecular docking results need to be discussed with more clarity.

1. Author response: We thank the reviewer for this valuable suggestion. In response, representative 2D interaction diagrams of the best multitarget docked complexes, along with the reference compounds, have been added to the revised manuscript (Figure 3). These figures illustrate the binding modes and key interactions established within the active sites of both NA and HMPV-F proteins. In addition, the molecular docking section has been revised to provide a clearer discussion of the docking results and ligand–protein interactions. The updated discussion now highlights the main interaction types involved in complex stabilization, including hydrogen bonding, hydrophobic contacts, π-interactions, and electrostatic interactions, as well as the key amino acid residues participating in ligand binding. Furthermore, the superior binding affinities of compounds such as E51 and M110 relative to the reference drugs are now discussed in greater detail to better support their potential multitarget antiviral activity.

2. The RMSD graphs appear to have been made using Microsoft Excel. The graphs need to be more refined and clearer. Kindly use Discovery Studio for better high-resolution and sharper images for the graphs.

2. Author response: We thank the reviewer for this helpful suggestion. The RMSD plots have been revised to improve clarity and overall visual presentation, including refined formatting and enhanced readability. The underlying RMSD data remain unchanged.

Attachments

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Submitted filename: Rebutal letter.docx

Response to the Reviewers

We sincerely thank the Editor and the Reviewers for their careful evaluation of our manuscript and for their valuable comments and constructive suggestions. We greatly appreciate the time and effort devoted to reviewing our work. Their insightful recommendations have helped us improve the quality, clarity, and scientific rigor of the manuscript. All comments have been carefully addressed, and the manuscript has been revised accordingly. The modifications introduced in the revised version are highlighted in yellow to facilitate their identification. A detailed, point-by-point response to each comment is provided below.

Comments and suggestions to the author

1. The abstract can be refined further.

Response: Thank you for your comment. The abstract has been revised to improve its clarity, conciseness, and overall readability while preserving the scientific content.

2. In the introduction, sentences like "Phytoconstituents are an in... these phytoconstituents" can be refined

Response: Thank you for your suggestion. The indicated sentences have been revised to improve clarity, readability, and overall language flow in the Introduction.

3. In section 2.1.2, “F currently lacks approved therapeutics…” needs to be revised. Although the second fusion protein has been identified as F, starting a sentence directly with F is not correct. Kindly consider changing to “furthermore, protein F…” or “Moreover, protein F…” for better readability.

Response: Thank you for your suggestion. The sentence has been revised by replacing “F” with “Moreover, protein F…” to improve readability and sentence structure.

4. In section 2.2.1, kindly check the format and font style of “10⁻⁴ units”. It appears inconsistent.

Response: Thank you for pointing this out. The formatting and font style of “10⁻⁴ units” have been corrected to ensure consistency throughout the manuscript.

5. In section 2.2.1, kindly maintain a consistent language style of either American English or British English as instructed by the journal guidelines. Also, perform a spell check.

“… geometry optimization and energy minimisation were performed in Avocadro using”

Response: Thank you for your comment. The manuscript has been thoroughly proofread, and the language has been revised to ensure consistent American English usage throughout, in accordance with the journal guidelines. Spelling and terminology have also been corrected where necessary.

6. In section 2.2.2, kindly change …” deduced using Discovery Studio 2021” to “…deduced using Discovery Studio, 2021

Response: Thank you for your suggestion. The sentence has been revised to read “deduced using Discovery Studio, 2021” as recommended.

Reviewer #3: Major Comments:

1. The novelty of the study is not clearly established. The work primarily involves selecting a subset of phytoconstituents from an existing database followed by molecular docking, which does not sufficiently demonstrate innovation. Experimental validation through in vitro antiviral assays is necessary to support the proposed therapeutic potential of the identified compounds.

Response: We sincerely thank the reviewer for this constructive comment. We agree that the novelty of the study should be stated more explicitly. Accordingly, the Introduction and Section 2.1.2 (Biological Target) were revised to better emphasize the innovative aspects of our study, and the Conclusion was updated to further clarify the originality of the proposed computational strategy and the scope of the findings (highlighted in yellow in the revised manuscript).

The novelty of this study does not reside in the use of previously reported phytoconstituents alone, but rather in the integrated computational strategy applied to identify broad-spectrum antiviral candidates. Specifically, our work simultaneously investigates two distinct respiratory viruses, influenza A virus and human metapneumovirus (HMPV), by targeting two key viral proteins involved in different stages of the viral life cycle, namely neuraminidase (NA) and the fusion protein (F). To the best of our knowledge, computational studies combining these two unrelated viral targets within a single screening workflow remain limited.

In addition, our study extends beyond conventional molecular docking by integrating successive filtering through drug-likeness assessment, comprehensive ADMET and toxicity prediction, followed by molecular dynamics simulations and MM-PBSA binding free-energy calculations to evaluate the stability of the selected protein–ligand complexes. This sequential workflow enabled the rational prioritization of the most promising candidates rather than relying solely on docking scores.

Regarding the request for experimental validation, we fully agree that in vitro antiviral assays are essential to confirm the computational predictions. However, the present work was designed as an in silico screening study aimed at identifying and prioritizing promising lead compounds for future experimental investigations. We have therefore revised the Conclusion to emphasize that the proposed compounds should be considered computational lead candidates requiring subsequent experimental validation, particularly through in vitro antiviral assays, followed by in vivo investigations, before any therapeutic conclusions can be drawn.

2. The claim that several phytochemicals outperform oseltamivir and ribavirin is based primarily on docking scores. Since docking energy alone does not reliably predict biological potency, additional binding free-energy calculations or experimental validation are needed.

Response: We sincerely thank the reviewer for this valuable comment. We agree that molecular docking scores alone are not sufficient to predict biological potency and should not be interpreted as evidence of superior antiviral activity. Accordingly, we have revised the manuscript to avoid overinterpretation of the docking results. Throughout the manuscript (Abstract, Results, and Conclusion), statements suggesting that the selected phytoconstituents "outperformed" the reference drugs have been replaced with more appropriate wording indicating more favorable predicted binding energies.

In response to the reviewer's recommendation, we performed MM-PBSA binding free-energy calculations as an additional validation step. The corresponding methodology and results have been incorporated into the revised manuscript (Sections 2.5 and 3.3.4, Table 7). The MM-PBSA analysis provided an independent energetic assessment of the selected protein–ligand complexes and further supported the molecular docking and molecular dynamics findings, reinforcing the prioritization of M294 and C11 as the most promising broad-spectrum antiviral lead compounds.

Furthermore, we clarified that the prioritization of the selected compounds was not based solely on docking scores but on an integrated computational workflow combining molecular docking, drug-likeness evaluation, ADMET and toxicity profiling, molecular dynamics simulations, and MM-PBSA binding free-energy calculations to improve the reliability of candidate selection.

Regarding the reviewer's recommendation for experimental validation, we fully agree that in vitro and in vivo studies are essential to confirm the computational predictions. However, the present study was designed as an in silico screening study for lead identification. Therefore, we have revised the Conclusion to explicitly state that the identified compounds should be considered computational lead candidates whose predicted antiviral potential requires experimental validation, particularly through in vitro antiviral assays followed by in vivo investigations.

3. The rationale for selecting the final lead compounds (M294 and C11) should be presented more systematically by integrating docking, ADMET, toxicity, and molecular dynamics results into a clear ranking or scoring framework.

Response: We sincerely thank the reviewer for this valuable suggestion. We agree that the rationale for selecting the final lead compounds should be presented more systematically. Accordingly, we have revised the manuscript to clarify the sequential prioritization strategy adopted throughout the study.

Specifically, we have added a summary table entitled "Sequential prioritization framework for the selection of the final broad-spectrum antiviral lead compounds (Table 8. )", which integrates the successive selection criteria, including molecular docking, drug-likeness evaluation, ADMET and toxicity profiling, molecular dynamics analyses and MM-PBSA binding free-energy calculations. This framework clearly illustrates how the initial library of phytoconstituents was progressively narrowed down to the final lead compounds.

In addition, the end of the Molecular Dynamics section has been revised to explicitly explain that M294 and C11 were prioritized because they consistently fulfilled all selection criteria by combining favorable multi-target docking performance, acceptable predicted pharmacokinetic and toxicological profiles, and the most stable interactions with both viral targets during the molecular dynamics simulations.

4. The molecular dynamics analysis mainly reports RMSD, RMSF, and interaction profiles, but lacks complementary analyses such as MM-PBSA/MM-GBSA binding free-energy calculations.

Response: Thank you for this valuable suggestion. In response to the reviewer's comment, we performed MM-PBSA binding free-energy calculations as a complementary analysis to the molecular dynamics simulations. The MM-PBSA results have been incorporated into the revised manuscript and provide a quantitative estimation of the binding free energies of the selected protein–ligand complexes. These calculations further support the stability and binding affinity observed from the RMSD, RMSF, and protein–ligand interaction analyses, reinforcing the prioritization of M294 and C11 as the most promising broad-spectrum antiviral candidates. The corresponding methodology, results, and discussion have been added to the revised manuscript (Section 3.3.4 , Table 7).

5. The manuscript does not adequately discuss the limitations of using predicted ADMET and toxicity data, which should be interpreted cautiously.

Response: We sincerely thank the reviewer for this valuable comment. We agree that computational ADMET and toxicity predictions should be interpreted with appropriate caution, as they are based on predictive models and cannot fully reflect the complexity of in vivo pharmacokinetic and toxicological behavior.

Accordingly, we have revised Section 3.2.2 (Evaluation of pharmacokinetics and toxicity properties) to explicitly acknowledge the limitations of these computational predictions. The revised manuscript has been updated to clarify that the predicted ADMET and toxicity profiles provide preliminary estimates that are valuable for early-stage compound prioritization but cannot replace experimental pharmacokinetic and toxicological evaluations. We also emphasize that the selected compounds should be considered exploratory in silico lead candidates requiring further experimental validation before any definitive conclusions regarding their safety or therapeutic potential can be drawn.

6. Although two viral proteins were investigated, the manuscript provides limited discussion on the conservation of the selected binding sites across different influenza A and HMPV strains.

Response: We sincerely thank the reviewer for this valuable comment. We agree that the conservation of the selected binding sites across different influenza A and HMPV strains deserved further clarification. Accordingly, we have revised Section 2.1.2 (Biological Target) to better justify the selection of the two crystallographic structures used in this study. Specifically, we added a discussion highlighting that the catalytic site of influenza A neuraminidase is highly conserved among the major influenza A subtypes, whereas the HMPV fusion (F) protein contains conserved functional regions across the principal HMPV genotypes. These characteristics support the use of PDB structures 2HT7 and 7SEJ as biologically relevant models for the computational identification of potential broad-spectrum antiviral candidates. We believe that this addition clarifies the rationale for target selection and strengthens the biological relevance of our computational approach.

Minor Comments:

1. The manuscript contains several grammatical errors and awkward sentence constructions that require careful English language editing to improve readability.

Response: We sincerely thank the reviewer for this valuable comment. The entire manuscript has been carefully revised to improve the quality of the English language, sentence structure, and overall readability. Grammatical errors, awkward sentence constructions, and stylistic inconsistencies were corrected throughout the text. In addition, the manuscript was thoroughly edited to ensure consistent use of American English spelling and terminology, thereby improving its clarity and readability.

2. The Introduction is longer than necessary and includes repeated discussion of previous studies, which could be condensed to improve focus on the objectives of the current work.

Response: We sincerely thank the reviewer for this constructive suggestion. The Introduction has been revised to improve its conciseness and focus. Repetitive background information, particularly regarding the clinical presentation of respiratory viral infections and the discussion of our previous studies, has been condensed or removed. The revised Introduction now places greater emphasis on the scientific rationale, the novelty of the proposed multi-target computational strategy, and the objectives of the present study.

3. The docking interaction figures would benefit from clearer labeling of interacting residues and improved annotation of key hydrogen bonds, hydrophobic contacts, and electrostatic interactions.

Response: We sincerely thank the reviewer for this helpful suggestion. The molecular docking interaction figures have been revised to improve their clarity and readability. The labeling of interacting amino acid residues has been enhanced, and the key hydrogen bonds, hydrophobic interactions, and electrostatic interactions have been more clearly annotated. These improvements facilitate the interpretation of the protein–ligand binding modes and highlight the principal interactions responsible for ligand stabilization within the binding sites.

Attachments

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Dear Editor

We would like to emphasize that these comments have already been addressed in our previous round of revisions. We have carefully responded to each point raised by the reviewer and incorporated the corresponding modifications into the revised manuscript. For the Editor's and Reviewer's convenience, we provide our responses below once again.

Best regards

Response to the Reviewers

We sincerely thank the Editor and the Reviewers for their careful evaluation of our manuscript and for their valuable comments and constructive suggestions. We greatly appreciate the time and effort devoted to reviewing our work. Their insightful recommendations have helped us improve the quality, clarity, and scientific rigor of the manuscript. All comments have been carefully addressed, and the manuscript has been revised accordingly. The modifications introduced in the revised version are highlighted in yellow to facilitate their identification. A detailed, point-by-point response to each comment is provided below.

Comments and suggestions to the author

1. The abstract can be refined further.

Response: Thank you for your comment. The abstract has been revised to improve its clarity, conciseness, and overall readability while preserving the scientific content.

2. In the introduction, sentences like "Phytoconstituents are an in... these phytoconstituents" can be refined

Response: Thank you for your suggestion. The indicated sentences have been revised to improve clarity, readability, and overall language flow in the Introduction.

3. In section 2.1.2, “F currently lacks approved therapeutics…” needs to be revised. Although the second fusion protein has been identified as F, starting a sentence directly with F is not correct. Kindly consider changing to “furthermore, protein F…” or “Moreover, protein F…” for better readability.

Response: Thank you for your suggestion. The sentence has been revised by replacing “F” with “Moreover, protein F…” to improve readability and sentence structure.

4. In section 2.2.1, kindly check the format and font style of “10⁻⁴ units”. It appears inconsistent.

Response: Thank you for pointing this out. The formatting and font style of “10⁻⁴ units” have been corrected to ensure consistency throughout the manuscript.

5. In section 2.2.1, kindly maintain a consistent language style of either American English or British English as instructed by the journal guidelines. Also, perform a spell check.

“… geometry optimization and energy minimisation were performed in Avocadro using”

Response: Thank you for your comment. The manuscript has been thoroughly proofread, and the language has been revised to ensure consistent American English usage throughout, in accordance with the journal guidelines. Spelling and terminology have also been corrected where necessary.

6. In section 2.2.2, kindly change …” deduced using Discovery Studio 2021” to “…deduced using Discovery Studio, 2021

Response: Thank you for your suggestion. The sentence has been revised to read “deduced using Discovery Studio, 2021” as recommended.

Attachments

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Submitted filename: Responses to reviewers.docx