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Comment on “Aggregation Interface and Rigid Spots Sustain the Stable Framework of a Thermophilic N-Demethylase”
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  • Daniel M. Wade
    Daniel M. Wade
    Department of Biology, Valdosta State University, Valdosta, Georgia 31698, United States
  • Walker S. Lewis
    Walker S. Lewis
    Department of Biology, Valdosta State University, Valdosta, Georgia 31698, United States
  • Jonghoon Kang*
    Jonghoon Kang
    Department of Biology, Valdosta State University, Valdosta, Georgia 31698, United States
    *(229) 333-7140, (229) 245-6585, [email protected]
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Journal of Agricultural and Food Chemistry

Cite this: J. Agric. Food Chem. 2023, 71, 49, 19900–19902
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https://doi.org/10.1021/acs.jafc.3c07043
Published December 1, 2023

Copyright © 2023 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY 4.0 .

Abstract

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The thermal properties of proteins are very important in industrial, agricultural, and food chemistry. A recent article (Li, B., et al. J. Agric. Food Chem. 2023, 71, 5614−5629) examines the thermal denaturation of enzymes TrSOX and BSOX by measuring the enthalpy change and melting temperature in the denaturation. In this work, we report the numerical values of entropy in the denaturation of proteins and show that both proteins TrSOX and BSOX exhibit enthalpy–entropy compensation in thermal denaturation, which results in a limited variation of melting temperature in both proteins. Our analysis may serve to improve our understanding of thermal properties in proteins in food chemistry.

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Copyright © 2023 The Authors. Published by American Chemical Society

In a recent publication in the Journal of Agricultural and Food Chemistry, Li et al. (1) used diverse biochemical and biophysical methods to examine the nature of the high thermostability of a N-demethylase from thermophilic Thermomicrobium roseum, compared with that from mesophilic Bacillus subtilis. The N-demethylase they examined in the paper was sarcosine oxidase; the one from T. roseum was denoted TrSOX, while that from B. subtilis was denoted BSOX. (1) The authors examined the molecular basis of the high thermostability of TrSOX using several techniques, including thermodynamic analysis of the thermal denaturation of proteins. This is notably motivating, as evidenced by the increasing prominence of thermodynamics in the field of food science, as reflected in recent scholarly publications. (2−4) One of the main results of the research is that the melting temperature (Tm) for all variants (wild type and mutants) of TrSOX was significantly higher than those of BSOX. They then discussed this phenomenon in terms of denaturation enthalpy (ΔH). Although both ΔH and Tm offer valuable insights into the thermodynamic underpinnings of the thermal stability of proteins, the original paper does not address another essential thermodynamic parameter, the entropy of denaturation (ΔS). ΔS is regarded as being crucial for comprehending the forces involved in protein denaturation. (5−10) In this Correspondence, we present our examination of their findings, aiming to elucidate the ΔS values in the thermal denaturation of the proteins, their correlation with ΔH, and the potential implications of the relationship between ΔH and ΔS within the context of the thermal stability of proteins.

Given that protein denaturation represents a phase transition from the native state to the denatured state, ΔS can be computed using the following equation:

ΔS=ΔHTm
(1)
where Tm is the melting temperature in kelvin. (11) Numerical values of both ΔH and Tm for the 55 denaturation reactions obtained from the original paper, (1) 34 for TrSOX and 21 for BSOX, were used for the calculation of ΔS using eq 1. Figure 1A displays the resulting values of ΔS and the corresponding ΔH values. The plot clearly shows three thermodynamic characteristics in the denaturation of the proteins. First, the denaturation of both TrSOX and BSOX at the melting temperature is an entropy-driven process; in other words, ΔS > 0. Second, site-directed mutagenesis decreases both ΔH and ΔS in the case of TrSOX but increases them in the case of BSOX, in most cases. Third, linear regression using eq 2 indicates a highly significant correlation between ΔH and ΔS in both proteins as the coefficients of determination (R2) are 0.9966 and 0.9992 for TrSOX and BSOX, respectively:
ΔH=TCΔS+β
(2)
where TC, the compensation temperature, is the slope of the fitting line (12) and β is the y-intercept (Figure 1A). The strong correlation between ΔH and ΔS is known as enthalpy–entropy compensation, often observed in a weakly coupled system. (13−16) Figure 1A clearly indicates that the denaturation of TrSOX and BSOX exhibits compensatory behavior, suggesting that the molecular components responsible for the denaturation of those proteins exhibit the property of a weakly coupled system. The compensation means that as ΔH increases the corresponding ΔS also increases so that the resulting differences in Tm are minimized. (10)

Figure 1

Figure 1. Statistical analysis of the thermodynamic parameters of TrSOX and BSOX. (A) Enthalpy–entropy compensation for both TrSOX and BSOX with wild types marked separately. Coefficients of variation of ΔH, ΔS, and Tm for (B) TrSOX and (C) BSOX. Average values and standard deviations of (D) ΔH, (E) ΔS, and (F) Tm for TrSOX and BSOX. SigmaPlot (version 15, Systat Software Inc., San Jose, CA) was used for graph preparation and statistical analysis.

The values of TC and its standard errors for TrSOX and BSOX are 411.6 ± 4.2 and 331.6 ± 2.1 K, respectively. A Student’s t test indicates that the difference in TC between TrSOX and BSOX is statistically significant (Table 1). In the t test, the degree of freedom (df) (17) was calculated as df = (n1 – 2) + (n2 – 2), where n1 and n2 are the number of data points of TrSOX and BSOX, respectively: n1 = 34, and n2 = 21 (Figure 1A). TC can quantitatively measure the degree of compensation between ΔH and ΔS. (12) The statistical difference in TC between TrSOX and BSOX (Table 1) strongly suggests that denaturation of each protein follows a distinct mechanism.

Table 1. Statistical Comparison of the Thermodynamic Parameters between TrSOX and BSOX
 TCΔHΔSTm
df51535353
t14.1–33.3–39.324.2
p3.4 × 10–193.4 × 10–377.3 × 10–412.5 × 10–30

The compensatory tendencies of ΔH and ΔS can be quantitatively described by comparing the coefficient of variation (CV) for each thermodynamic parameter, as determined by eq 3:

CV=sm
(3)
where s and m are the standard deviation and the mean of the samples, respectively. (17) The CVs of ΔH and ΔS are more than 5 or 33 times larger than that of Tm for TrSOX (Figure 1B) or BSOX (Figure 1C), respectively. On the basis of this result, we suggest that variations in ΔH and ΔS are local characteristics for the structural thermodynamics of proteins, while variation in Tm is a global characteristic that stays relatively constant in a weakly coupled system. This thermodynamic explanation is in line with the observations in the original paper (1) that all 20 mutants of BSOX generated with an intention to improve its thermostability showed a large variation in both ΔH and ΔS but a highly limited variation in Tm.

We also compare the thermodynamic parameters of TrSOX and BSOX to elucidate thermodynamic reasons for the high thermal stability of TrSOX. The differences in ΔH (Figure 1D), ΔS (Figure 1E), and Tm (Figure 1F) are shown to be statistically significant on the basis of the p values (Table 1). While ΔH is much smaller in TrSOX suggesting TrSOX must have a smaller value of Tm according to eq 1, ΔS is also much smaller in TrSOX, making it more stable. The much smaller value of ΔS stabilizes TrSOX compared to BSOX. In other words, the high thermal stability of TrSOX can be explained by the small value of ΔS. This is why ΔH is not sufficient in the explanation of the variation of Tm and ΔS should be included in the interpretation. The analysis introduced in this paper can be applied to other thermostable proteins such as TrLipB (18,19) to assess the contribution of small values of denaturation entropy to the thermal stability of proteins. We can conclude that the thermal denaturation of both TrSOX and BSOX exhibits enthalpy–entropy compensation. Statistical analysis suggests that ΔS is responsible for the high thermal stability of TrSOX. It will be interesting to examine whether other thermostable proteins exhibit these phenomena.

Author Information

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  • Corresponding Author
  • Authors
    • Daniel M. Wade - Department of Biology, Valdosta State University, Valdosta, Georgia 31698, United States
    • Walker S. Lewis - Department of Biology, Valdosta State University, Valdosta, Georgia 31698, United States
  • Notes
    The authors declare no competing financial interest.

References

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This article references 19 other publications.

  1. 1
    Li, B.; Sun, Y.; Zhu, X.; Qian, S.; Pu, J.; Guo, Y.; Wu, H.; Zhang, L.; Xin, Y. Aggregation interface and rigid spots sustain the stable framework of a thermophilic N-demethylase. J. Agric. Food Chem. 2023, 71, 56145629,  DOI: 10.1021/acs.jafc.3c00877
  2. 2
    Arroyo-Maya, I. J.; McClements, D. J. Application of ITC in foods: A powerful tool for understanding the gastrointestinal fate of lipophilic compounds. Biochim. Biophys. Acta, Gen. Subj. 2016, 1860, 10261035,  DOI: 10.1016/j.bbagen.2015.10.001
  3. 3
    Garvín, A.; Ibarz, R.; Ibarz, A. Kinetic and thermodynamic compensation. A current and practical review for foods. Food Res. Int. 2017, 96, 132153,  DOI: 10.1016/j.foodres.2017.03.004
  4. 4
    Lin, S. Y.; Lin, C. C. One-step real-time food quality analysis by simultaneous DSC-FTIR microspectroscopy. Crit. Rev. Food Sci. Nutr. 2016, 56, 292305,  DOI: 10.1080/10408398.2012.740523
  5. 5
    Khechinashvili, N. N.; Janin, J.; Rodier, F. Thermodynamics of the temperature-induced unfolding of globular proteins. Protein Sci. 1995, 4, 13151324,  DOI: 10.1002/pro.5560040707
  6. 6
    Tamoliu Nas, K.; Galamba, N. Protein denaturation, zero entropy temperature, and the structure of water around hydrophobic and amphiphilic solutes. J. Phys. Chem. B 2020, 124, 1099411006,  DOI: 10.1021/acs.jpcb.0c08055
  7. 7
    Pereira, R. N.; Teixeira, J. A.; Vicente, A. A. Exploring the denaturation of whey proteins upon application of moderate electric fields: a kinetic and thermodynamic study. J. Agric. Food Chem. 2011, 59, 1158911597,  DOI: 10.1021/jf201727s
  8. 8
    Helmick, H.; Turasan, H.; Yildirim, M.; Bhunia, A.; Liceaga, A.; Kokini, J. L. Cold denaturation of proteins: Where bioinformatics meets thermodynamics to offer a mechanistic understanding: Pea protein as a case study. J. Agric. Food Chem. 2021, 69, 63396350,  DOI: 10.1021/acs.jafc.0c06558
  9. 9
    Montserrat, M.; Mayayo, C.; Sánchez, L.; Calvo, M.; Pérez, M. D. Study of the thermoresistance of the allergenic Ara h1 protein from peanut (Arachis hypogaea). J. Agric. Food Chem. 2013, 61, 33353340,  DOI: 10.1021/jf305450s
  10. 10
    Kang, J.; Solis Rueda, K. A. Enthalpy–entropy compensation in the denaturation of proteins of bovine masseter and cutaneous trunci. Meat Sci. 2022, 184, 108688  DOI: 10.1016/j.meatsci.2021.108688
  11. 11
    Chang, R. Physical Chemistry for the Chemical and Biological Sciences; University Science Books: Sausalito, CA, 2000.
  12. 12
    Griessen, R.; Dam, B. Simple accurate verification of enthalpy–entropy compensation and isoequilibrium relationship. Chemphyschem. 2021, 22, 17741784,  DOI: 10.1002/cphc.202100431
  13. 13
    Haynie, D. T. Biological thermodynamics, 1st ed.; Cambridge University Press: Cambridge, U.K., 2001.
  14. 14
    Kang, J.; Auerbach, J. D. Thermodynamic characterization of dissociation rate variations of human leukocyte antigen and peptide complexes. Mol. Immunol. 2009, 46, 28732875,  DOI: 10.1016/j.molimm.2009.05.184
  15. 15
    Garvín, A.; Ibarz, R.; Ibarz, A. Kinetic and thermodynamic compensation. A current and practical review for foods. Food Res. Int. 2017, 96, 132153,  DOI: 10.1016/j.foodres.2017.03.004
  16. 16
    Fox, J. M.; Zhao, M.; Fink, M. J.; Kang, K.; Whitesides, G. M. The molecular origin of enthalpy/entropy compensation in biomolecular recognition. Annu. Rev. Biophys. 2018, 47, 223250,  DOI: 10.1146/annurev-biophys-070816-033743
  17. 17
    Fowler, J.; Cohen, L.; Jarvis, P. Practical statistics for field biology; John Wiley & Sons: Chichester, England, 2008.
  18. 18
    Fang, Y.; Zhou, Y.; Xin, Y.; Shi, Y.; Guo, Z.; Li, Y.; Gu, Z.; Ding, Z.; Shi, G.; Zhang, L. Preparation and characterization of a novel thermostable lipase from Thermomicrobium reseum. Catal. Sci. Technol. 2021, 11, 73867397,  DOI: 10.1039/D1CY01486B
  19. 19
    Fang, Y.; Liu, F.; Shi, Y.; Yang, T.; Liang, C.; Xin, Y.; Gu, Z.; Shi, G.; Zhang, L. Hotspots and mechanisms of action of the thermostable framework of a microbial thermolipase. ACS Synth. Biol. 2022, 11, 34603470,  DOI: 10.1021/acssynbio.2c00360

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  1. Gracie A. Roberson, Jonghoon Kang, . Application of statistics to Beer’s law. Journal of Microbiology and Biology Education 2025, https://doi.org/10.1128/jmbe.00234-24

Journal of Agricultural and Food Chemistry

Cite this: J. Agric. Food Chem. 2023, 71, 49, 19900–19902
Click to copy citationCitation copied!
https://doi.org/10.1021/acs.jafc.3c07043
Published December 1, 2023

Copyright © 2023 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY 4.0 .

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  • Figure 1

    Figure 1. Statistical analysis of the thermodynamic parameters of TrSOX and BSOX. (A) Enthalpy–entropy compensation for both TrSOX and BSOX with wild types marked separately. Coefficients of variation of ΔH, ΔS, and Tm for (B) TrSOX and (C) BSOX. Average values and standard deviations of (D) ΔH, (E) ΔS, and (F) Tm for TrSOX and BSOX. SigmaPlot (version 15, Systat Software Inc., San Jose, CA) was used for graph preparation and statistical analysis.

  • References


    This article references 19 other publications.

    1. 1
      Li, B.; Sun, Y.; Zhu, X.; Qian, S.; Pu, J.; Guo, Y.; Wu, H.; Zhang, L.; Xin, Y. Aggregation interface and rigid spots sustain the stable framework of a thermophilic N-demethylase. J. Agric. Food Chem. 2023, 71, 56145629,  DOI: 10.1021/acs.jafc.3c00877
    2. 2
      Arroyo-Maya, I. J.; McClements, D. J. Application of ITC in foods: A powerful tool for understanding the gastrointestinal fate of lipophilic compounds. Biochim. Biophys. Acta, Gen. Subj. 2016, 1860, 10261035,  DOI: 10.1016/j.bbagen.2015.10.001
    3. 3
      Garvín, A.; Ibarz, R.; Ibarz, A. Kinetic and thermodynamic compensation. A current and practical review for foods. Food Res. Int. 2017, 96, 132153,  DOI: 10.1016/j.foodres.2017.03.004
    4. 4
      Lin, S. Y.; Lin, C. C. One-step real-time food quality analysis by simultaneous DSC-FTIR microspectroscopy. Crit. Rev. Food Sci. Nutr. 2016, 56, 292305,  DOI: 10.1080/10408398.2012.740523
    5. 5
      Khechinashvili, N. N.; Janin, J.; Rodier, F. Thermodynamics of the temperature-induced unfolding of globular proteins. Protein Sci. 1995, 4, 13151324,  DOI: 10.1002/pro.5560040707
    6. 6
      Tamoliu Nas, K.; Galamba, N. Protein denaturation, zero entropy temperature, and the structure of water around hydrophobic and amphiphilic solutes. J. Phys. Chem. B 2020, 124, 1099411006,  DOI: 10.1021/acs.jpcb.0c08055
    7. 7
      Pereira, R. N.; Teixeira, J. A.; Vicente, A. A. Exploring the denaturation of whey proteins upon application of moderate electric fields: a kinetic and thermodynamic study. J. Agric. Food Chem. 2011, 59, 1158911597,  DOI: 10.1021/jf201727s
    8. 8
      Helmick, H.; Turasan, H.; Yildirim, M.; Bhunia, A.; Liceaga, A.; Kokini, J. L. Cold denaturation of proteins: Where bioinformatics meets thermodynamics to offer a mechanistic understanding: Pea protein as a case study. J. Agric. Food Chem. 2021, 69, 63396350,  DOI: 10.1021/acs.jafc.0c06558
    9. 9
      Montserrat, M.; Mayayo, C.; Sánchez, L.; Calvo, M.; Pérez, M. D. Study of the thermoresistance of the allergenic Ara h1 protein from peanut (Arachis hypogaea). J. Agric. Food Chem. 2013, 61, 33353340,  DOI: 10.1021/jf305450s
    10. 10
      Kang, J.; Solis Rueda, K. A. Enthalpy–entropy compensation in the denaturation of proteins of bovine masseter and cutaneous trunci. Meat Sci. 2022, 184, 108688  DOI: 10.1016/j.meatsci.2021.108688
    11. 11
      Chang, R. Physical Chemistry for the Chemical and Biological Sciences; University Science Books: Sausalito, CA, 2000.
    12. 12
      Griessen, R.; Dam, B. Simple accurate verification of enthalpy–entropy compensation and isoequilibrium relationship. Chemphyschem. 2021, 22, 17741784,  DOI: 10.1002/cphc.202100431
    13. 13
      Haynie, D. T. Biological thermodynamics, 1st ed.; Cambridge University Press: Cambridge, U.K., 2001.
    14. 14
      Kang, J.; Auerbach, J. D. Thermodynamic characterization of dissociation rate variations of human leukocyte antigen and peptide complexes. Mol. Immunol. 2009, 46, 28732875,  DOI: 10.1016/j.molimm.2009.05.184
    15. 15
      Garvín, A.; Ibarz, R.; Ibarz, A. Kinetic and thermodynamic compensation. A current and practical review for foods. Food Res. Int. 2017, 96, 132153,  DOI: 10.1016/j.foodres.2017.03.004
    16. 16
      Fox, J. M.; Zhao, M.; Fink, M. J.; Kang, K.; Whitesides, G. M. The molecular origin of enthalpy/entropy compensation in biomolecular recognition. Annu. Rev. Biophys. 2018, 47, 223250,  DOI: 10.1146/annurev-biophys-070816-033743
    17. 17
      Fowler, J.; Cohen, L.; Jarvis, P. Practical statistics for field biology; John Wiley & Sons: Chichester, England, 2008.
    18. 18
      Fang, Y.; Zhou, Y.; Xin, Y.; Shi, Y.; Guo, Z.; Li, Y.; Gu, Z.; Ding, Z.; Shi, G.; Zhang, L. Preparation and characterization of a novel thermostable lipase from Thermomicrobium reseum. Catal. Sci. Technol. 2021, 11, 73867397,  DOI: 10.1039/D1CY01486B
    19. 19
      Fang, Y.; Liu, F.; Shi, Y.; Yang, T.; Liang, C.; Xin, Y.; Gu, Z.; Shi, G.; Zhang, L. Hotspots and mechanisms of action of the thermostable framework of a microbial thermolipase. ACS Synth. Biol. 2022, 11, 34603470,  DOI: 10.1021/acssynbio.2c00360