Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study investigates the pharmacological basis of Benjalokawichian (BLW), a traditional Thai polyherbal remedy used for treating "toxic fever" (TF). The authors employ a robust integrative approach combining network pharmacology, molecular docking, and in vitro validation using LPS-induced RAW264.7 macrophages. The manuscript is well-structured and provides significant scientific evidence supporting the traditional use of BLW as an antipyretic and anti-inflammatory agent.

1. The results show that while the total BLW extract is highly potent, the individual biomarkers (perforatic acid, bergenin, etc.) generally showed weak NO inhibitory activity (IC50 > 100 μg/mL). This strongly suggests synergistic or additive effects. I recommend the authors expand the discussion to elaborate on how these minor constituents might interact to produce a potent overall effect.
2. Molecular docking revealed that obacunone exhibited the strongest binding affinity for TNF, STAT3, and NFKB1 (up to -11.1kJ/mol). However, obacunone was not among the quantified markers in the HPLC section. If possible, a brief discussion on the estimated concentration or importance of obacunone relative to the quantified chromones would be beneficial.
3. The paper highlights the phenylalanine, arachidonic acid, and tyrosine metabolism pathways. The inclusion of Figure 6 (Arachidonic acid metabolism) is excellent as it bridges traditional "heat" theories with modern biochemistry.
4. While the RAW264.7 model is a standard for anti-inflammatory screening, it only partially mimics the complex "toxic fever" microenvironment. Future in vivo studies using pyrogen-induced fever models would strengthen the conclusions regarding thermoregulatory adjustment.
5. Check for consistent terminology (e.g., "toxic fever" vs. "severe fever") to ensure the TTM terminology is clearly defined for a global audience throughout the text.
6. Ensure all units in the molecular docking table (Table 3) are consistent; the header says kcal/mol while the text refers to kJ/mol.

Author Response

Reviewer#1: This study investigates the pharmacological basis of Benjalokawichian (BLW), a traditional Thai polyherbal remedy used for treating "toxic fever" (TF). The authors employ a robust integrative approach combining network pharmacology, molecular docking, and in vitro validation using LPS-induced RAW264.7 macrophages. The manuscript is well-structured and provides significant scientific evidence supporting the traditional use of BLW as an antipyretic and anti-inflammatory agent.

Reply: We would like to thank Reviewer#1’s positive opinion about our manuscript and giving an insightful appreciation of the subject of our research. Reviewer#1’s comments and suggestions have encouraged us to commit to this complex but vital area of research which still has much more to explore.

Comments 1: The results show that while the total BLW extract is highly potent, the individual biomarkers (perforatic acid, bergenin, etc.) generally showed weak NO inhibitory activity (IC₅₀ > 100 μg/mL). This strongly suggests synergistic or additive effects. I recommend the authors expand the discussion to elaborate on how these minor constituents might interact to produce a potent overall effect.

Response 1: We sincerely appreciate your insightful observation. We agree that the high potency of the total BLW extract compared to the weaker activity of individual biomarkers points toward a synergistic or additive effect, which is a fundamental characteristic of traditional polyherbal remedies. In response to this suggestion, we have expanded the Discussion section (Page 24, Lines 585-600) to elaborate on this synergy. We have integrated our network pharmacology findings to explain how these minor constituents might interact by targeting different proteins within the inflammatory network (e.g., TNF, COX-2, STAT3, and NFKB1). This 'multi-target' mechanism explains why the crude extract, containing a complex mixture of phytochemicals, exhibits superior efficacy over isolated compounds.

Comments 2: Molecular docking revealed that obacunone exhibited the strongest binding affinity for TNF, STAT3, and NFKB1 (up to -11.1kJ/mol). However, obacunone was not among the quantified markers in the HPLC section. If possible, a brief discussion on the estimated concentration or importance of obacunone relative to the quantified chromones would be beneficial.

Response 2: We appreciate your suggestion regarding the correlation between our docking results and HPLC quantification. Following this comment, we performed an additional HPLC analysis to specifically identify and quantify obacunone in our BLW extract. However, the compound was not detected (ND) under our validated experimental conditions. To provide transparency, we have included the HPLC chromatogram of the obacunone standard compared with the BLW extract as Supplementary Material (Figure S1). Although obacunone was not detected in our current study, its high binding affinity in the docking study remains theoretically significant, suggesting it could be a potent minor constituent or a 'trace' compound that contributes to the synergy. We have now addressed this in the Results section (Page 15, Lines 275-276) and Discussion section (Page 22, Lines 530-532).

Comments 3: The paper highlights the phenylalanine, arachidonic acid, and tyrosine metabolism pathways. The inclusion of Figure 6 (Arachidonic acid metabolism) is excellent as it bridges traditional "heat" theories with modern biochemistry.

Response 3: We are grateful for your positive feedback regarding the integration of traditional 'heat' theories with metabolic pathways. We agree that Figure 6 serves as a vital bridge between Thai traditional medicine and biochemical mechanisms.

Comments 4: While the RAW264.7 model is a standard for anti-inflammatory screening, it only partially mimics the complex "toxic fever" microenvironment. Future in vivo studies using pyrogen-induced fever models would strengthen the conclusions regarding thermoregulatory adjustment.

Response 4: We completely agree with your constructive assessment. While the RAW 264.7 macrophage model is a reliable and well-established system for initial anti-inflammatory screening, we acknowledge that it cannot fully replicate the systemic thermoregulatory and neuro-endocrine responses seen in a living organism. In accordance with this suggestion, we have added a dedicated section in the Conclusion and Future Perspectives (Page 24, Lines 603-613) to highlight the necessity of in vivo validation. We aim to utilize pyrogen-induced fever models (e.g., LPS or yeast-induced models) in our next phase of research to further elucidate the thermoregulatory adjustment and systemic efficacy of the BLW formula.

Comments 5: Check for consistent terminology (e.g., "toxic fever" vs. "severe fever") to ensure the TTM terminology is clearly defined for a global audience throughout the text.

Response 5: We have now consistently used the term 'toxic fever' throughout the manuscript to describe the TTM concept of Khai Phit. Furthermore, we have added a definition in the Introduction (Page 2, Line 62) to clarify that 'toxic fever' in the TTM context correlates with severe systemic inflammation and metabolic shifts, ensuring the terminology is accessible to a global scientific audience.

Comments 6: Ensure all units in the molecular docking table (Table 3) are consistent; the header says kcal/mol while the text refers to kJ/mol.

Response 6: We have thoroughly reviewed the manuscript and Table 3 to ensure consistency in the units of binding affinity. All units have been corrected to kcal/mol throughout the text to match the values presented in Table 3. We have also double-checked all other tables and figures for unit consistency.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This study explored BLW’s antipyretic mechanisms against toxic fever via network pharmacology, molecular docking and in vitro NO inhibition. It identified 17 bioactive compounds, 4 hub genes, key metabolic pathways, and verified BLW’s potent NO inhibition with no cytotoxicity in RAW264.7 cells.

1. In Section 2.7, the spelling of O‑methyllaloptaeroxyrin is inconsistent with O‑methylalloptaeroxylin among the five biomarkers analyzed by HPLC. Please unify the standard English name of this compound.
2. The abstract and conclusion both state that BLW contains 17 potential active components, but only 15 components meeting ADME criteria were included after screening in Section 2.1. Please clarify the counting basis of the 17 components and correct the inconsistency.
3. More recent published papers related to delivery and therapeutic efficacy of traditional herbal medicine should be cited: https://doi.org/10.1016/j.jinorgbio.2025.113015.
4. The IC₅₀ of BLW extract for inhibiting NO production in vitro is 69.10 μg/mL, whereas its core markers perforic acid and apigenin‑7‑methyl ether show weak NO inhibitory activity alone (IC₅₀ > 100 μg/mL). Please add a discussion on the synergistic mechanism of multiple components in the BLW formula and explain why the whole formula is more active than single components based on network pharmacology.
5. Only the LPS‑induced RAW264.7 macrophage model was used to verify NO inhibitory activity. This model only reflects the antipyretic stage of inflammation, while toxic fever (TF) involves a complex in vivo pathological microenvironment. Please explain the correlation between this in vitro model and the in vivo pathological state of TF, and point out the limitations of the model.

Author Response

Appreciation:

This study explored BLW’s antipyretic mechanisms against toxic fever via network pharmacology, molecular docking and in vitro NO inhibition. It identified 17 bioactive compounds, 4 hub genes, key metabolic pathways, and verified BLW’s potent NO inhibition with no cytotoxicity in RAW264.7 cells.

Reply: We appreciate reviewer#2’s positive opinion of our manuscript, especially the experimental design and the results obtained. We are very grateful for your comments, which we believe will improve the quality of our paper and its readability.

Comments 1: In Section 2.7, the spelling of O‑methyllaloptaeroxyrin is inconsistent with O‑methylalloptaeroxylin among the five biomarkers analyzed by HPLC. Please unify the standard English name of this compound.

Response 1: We appreciate your comments on this point. We have now unified the spelling to O-methylalloptaeroxylin throughout the entire manuscript, including Section 2.7, Table 4, and all relevant figures and supplementary data, to adhere to the standard chemical nomenclature.

Comments 2: The abstract and conclusion both state that BLW contains 17 potential active components, but only 15 components meeting ADME criteria were included after screening in Section 2.1. Please clarify the counting basis of the 17 components and correct the inconsistency.

Response 2: We thank your meticulous observation. The correct number of potential active components identified through our ADME screening is 15, not 17. We have thoroughly reviewed the entire manuscript and corrected this inconsistency in the Abstract, Results, Discussion, and Conclusion sections to ensure that the number of active components is consistently reported as 15 throughout the paper.

Comments 3: More recent published papers related to delivery and therapeutic efficacy of traditional herbal medicine should be cited: https://doi.org/10.1016/j.jinorgbio.2025.113015.

Response 3: We sincerely appreciate your suggestion to include more recent literature. We have carefully reviewed the suggested article. However, after a thorough evaluation, we found that the primary focus of that study, which discusses inorganic metal complexes or specific delivery systems, does not directly align with the scope of our current research on the network pharmacology and in vitro nitric oxide inhibition of the Benjalokawichian (BLW) polyherbal remedy. To maintain the focus and thematic consistency of our manuscript, we have chosen not to include this specific citation.

Comments 4: The IC₅₀ of BLW extract for inhibiting NO production in vitro is 69.10 μg/mL, whereas its core markers perforic acid and apigenin‑7‑methyl ether show weak NO inhibitory activity alone (IC₅₀ > 100 μg/mL). Please add a discussion on the synergistic mechanism of multiple components in the BLW formula and explain why the whole formula is more active than single components based on network pharmacology.

Response 4: We sincerely appreciate your insightful observation. We agree that the high potency of the total BLW extract compared to the weaker activity of individual biomarkers points toward a synergistic or additive effect, which is a fundamental characteristic of traditional polyherbal remedies. In response to this suggestion, we have expanded the Discussion section (Page 24, Lines 584-599) to elaborate on this synergy. We have integrated network pharmacology findings to explain how these minor constituents might interact by targeting different proteins within the inflammatory network (e.g., TNF, COX-2, STAT3, and NFKB1). This 'multi-target' mechanism explains why the crude extract, containing a complex mixture of phytochemicals, exhibits superior efficacy over isolated compounds.

Comments 5: Only the LPS‑induced RAW264.7 macrophage model was used to verify NO inhibitory activity. This model only reflects the antipyretic stage of inflammation, while toxic fever (TF) involves a complex in vivo pathological microenvironment. Please explain the correlation between this in vitro model and the in vivo pathological state of TF, and point out the limitations of the model. 

Response 5: We appreciate your request for clarification. We have now expanded the Discussion (Page 23, Lines 538-545) to explicitly explain the correlation between in vitro results and the in vivo state of toxic fever (TF). We clarify that the LPS-induced RAW 264.7 model represents the cellular inflammatory trigger, specifically, the macrophage-mediated release of NO, which is a key component of the early stages of TF. Furthermore, we have addressed the limitations of this model, acknowledging that it does not capture the full systemic complexity of TF, such as hypothalamic thermoregulation (Page 24, Lines 600-610). This provides a more balanced perspective on our findings and justifies the need for future in vivo studies, as mentioned in our updated conclusion.

 

Author Response File: Author Response.pdf