Gibbs Free Energy and Enthalpy–Entropy Compensation in Protein Folding
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe studies by Benítez et al. compared the thermodynamic parameters, including melting temperature, enthalpy and Gibbs free energy, of 583 proteins obtained from the ProThermDB database to those of protein-ligand interactions. They conclude that the overall negative Gibbs free energy of protein folding is a small negative value that is equivalent to about 2 to 3 H-bond interaction caused by large entropic penalties from the loss of conformational changes. Compared with protein folding, protein-ligand interactions have much conformational changes caused entropic penalties, and the negative Gibbs free energies are therefore results from weak interaction caused enthalpy change. While I think the manuscript is well written and suit the scope of this journal, there are a few issues that need to be addressed.
The major issue comes from the dataset availability. The authors claimed that 483 protein-folding and 42 protein-ligand interactions were analyzed, from dataset and old publications, however the detailed protein and ligand names relevant to this manuscript are completely missing. Such information must be included.
Other minor things. 1) Figure 1. It would be great to include a Gibbs free energy plot with zoomed in y-axis range. 2) Figure 4. X-axis label is cropped.
Author Response
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Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe manuscript presents a very interesting topic for macromolecular science. I recommend acceptance after revisions.
-The authors mention: “EEC seems to be more important in protein-folding than in protein-ligand interactions, as deduced from the large decrease in TΔSº and heat capacity values found in the first process.” When interacting with small molecules, proteins undergo a much smaller conformational change compared to folding. This does not mean that EEC is more important in the case of folding. The authors should revise this sentence to avoid prioritizing one phenomenon over the other.
-The equations are poorly formatted. The authors should edit them using proper equation editing tools.
-In the methodology, the authors did not provide any details on how the thermodynamic data deposited in the database were obtained. It is important for readers to have this detailed in the methodology.
-The methodology does not specify which classes of proteins were extracted from the database. Were proteins requiring chaperones for folding also included? This information should be added to the manuscript.
-In Figure 1, several data points deviate significantly from the average TΔS and ΔH values for most proteins. The authors should include a discussion in the manuscript about whether these outliers correspond to specific protein functional classes or random protein classes.
-The intermediate image in Figure 3 has histograms that are difficult for readers to analyze. This figure should be improved.
-In lines 117 to 124, the authors mention intermolecular interactions in a purely descriptive manner. They could expand this discussion by including data from the literature (e.g., 10.3390/molecules28196891).
-The authors state: “ΔGº = −30.9 kJ/mol, with a standard deviation of 21 kJ/mol…” The standard deviation is relatively high. The authors should provide a justification for this possibly large value at this temperature.
-In lines 273-279, the authors discuss the hydrophobic effect. A recent publication demonstrates how the environment influences this effect, making hydrophobic interactions significant. The authors could include this discussion to incorporate current findings (10.3390/ijms252312664).
-Based on the results obtained for proteins, could the authors add an extension to the manuscript qualitatively discussing the possible effects on DNA and RNA?
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsI have reviewed your manuscript on “Gibbs Free Energy and Enthalpy-Entropy Compensation in Protein Folding” and found it to be insightful. However, to improve the clarity and depth, I suggest the following improvements:
1. The authors should provide detailed descriptions of the experimental techniques or computational simulations used. Please include parameters, tools (e.g., software for molecular docking or thermodynamic modeling), and protocols, allowing other researchers to replicate the study.
2. The authors should add a comparative analysis between wild-type proteins and their mutant forms (or other types of controls) to show how thermodynamic properties like Gibbs free energy change between different protein states. This would make the conclusions more robust. I would recommend reading this article by Govind et al and the references cited in the article: Govind Kumar, V., et al. Binding affinity estimation from restrained umbrella sampling simulations. Nat Comput Sci 3, 59–70 (2023).
3. In the discussion, consider expanding on how the understanding of Gibbs free energy and enthalpy-entropy compensation can be applied to real-world scenarios, such as predicting the stability of drug-protein interactions or designing proteins with desired folding properties to help Alzheimer's or Parkinson’s disease.
4. The authors should consider adding supplementary materials like interactive 3D models of protein folding, or online tools that allow readers to explore the thermodynamic data more deeply. This could include simulations or graphical user interfaces (GUIs) to manipulate key parameters.
5. The authors should consider providing access to the underlying datasets or computational scripts (e.g., via an online repository) so other researchers can validate or build upon your work.
6. The authors should update the references to include more of the recent studies (2020-2024).
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
Comments and Suggestions for AuthorsI accept this paper for publication
