foodmetaFOOD METAENGINEERINGFOOD METAENGINEERING2949-6497All-Russian Dairy Research Institute10.37442/fme.2025.1.79foodmeta-79Research ArticleОригинальное эмпирическое исследованиеOriginal Empirical ResearchБиоинформатический анализ изменений пептидного профиля молочных белков при храненииBioinformatic Analysis of Changes in the Peptide Profile of Dairy Proteins During Storagehttps://orcid.org/0000-0002-7529-2007СолтанОсама И.А.SoltanOsama I.A.usama.soultan@mu.edu.egУниверситет МиниаЕгипетMinia UniversityEgypt202525032025311732Copyright © Солтан О.И., 20252025Солтан О.И.Soltan O.I.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.fme-journal.org/jour/article/view/79Введение

Введение: Ферментативные процессы, происходящие в молочных продуктах при хранении, могут приводить к изменениям белкового состава, что влияет на их качество. Ключевую роль в этих изменениях играют как эндогенные ферменты, такие как плазмин, так и бактериальные протеазы. Применение биоинформатических методов позволяет моделировать гидролиз белков и прогнозировать образование пептидов со специфическими свойствами (с конкретными органолептическими характеристиками, биологической активностью, молекулярной массой, аминокислотной последовательностью и др.).

Цель

Цель: Оценить изменения пептидного профиля казеинов β-CN, αs1-CN, αs2-CN и κ-CN при моделировании их гидролиза плазмином и термостабильной бактериальной протеазой Pseudomonas LBSA1.

Материалы и методы

Материалы и методы: Анализ последовательностей казеинов проводили с использованием базы данных UniProt. Гидролиз моделировали в BIOPEP-UWM (для плазмина) и с помощью регулярных выражений в RStudio (для Pseudomonas LBSA1). Степень гидролиза (DH) рассчитывали на основе количества разорванных пептидных связей в отношении к общему числу возможных связей в белковой молекуле. Для анализа пептидных последовательностей применяли библиотеку “stringr” в RStudio. Горькие и антиоксидантные пептиды выявляли с использованием базы данных BIOPEP-UWM. Данные о молекулярной массе и изоэлектрической точке полученных пептидов извлекали с помощью библиотеки “Peptides” в RStudio.

Результаты

Результаты: Результаты 2D-диаграмм показали различия в распределении пептидов по молекулярной массе и изоэлектрической точке в зависимости от специфичности ферментов. В комбинированной модели гидролиза идентифицировано 4 горьких пептида и 3 вида горьких аминокислот, а также 6 антиоксидантных пептидов.

Выводы

Выводы: Биоинформатическое моделирование позволяет прогнозировать ферментативные изменения белков в молочных продуктах, их влияние на качество, а также повышать эффективность проводимых в этом поле экспериментов. Полученные данные могут использоваться для разработки подходов к оценке хранения молочных продуктов и идентификации маркеров качества.

Introduction

Introduction: Enzymatic processes occurring in dairy products during storage can lead to changes in protein composition, affecting products’ quality. Key players in these changes include endogenous enzymes, such as plasmin, and bacterial proteases like the heat stable protease from Pseudomonas LBSA1. The application of bioinformatic methods enables the modeling of protein hydrolysis and prediction of peptide formation with specific properties (e.g., organoleptic characteristics, bioactivity, molecular weight, amino acid sequence).

Purpose

Purpose: To evaluate changes in the peptide profiles of β-CN, αs1-CN, αs2-CN, and κ-CN caseins during simulated hydrolysis by plasmin and the heat stable bacterial protease Pseudomonas LBSA1.

Materials and Methods

Materials and Methods: Casein sequences were analyzed using the UniProt database. Hydrolysis was modeled using BIOPEP-UWM (for plasmin) and regular expressions in RStudio (for Pseudomonas LBSA1). The degree of hydrolysis (DH) was calculated as the ratio of cleaved peptide bonds to the total possible bonds in the protein. Peptide sequences were analyzed using the “stringr” library in RStudio. Bitter and antioxidant peptides were identified using the BIOPEP-UWM database. Molecular weight and isoelectric point data were obtained via the “Peptides” library in RStudio.

Results

Results: 2D diagrams revealed distinct distributions of peptides based on molecular weight and isoelectric point, dependent on enzyme specificity. In the combined hydrolysis model, 4 bitter peptides, 3 types of bitter amino acids, and 6 antioxidant peptides were identified.

Conclusion

Conclusion: Bioinformatic modeling enables the prediction of enzymatic changes in milk proteins during storage, their impact on quality, and enhances the efficiency of related experiments. These findings may support the development of approaches for assessing dairy product storage conditions and identifying quality markers.

биоинформатикамолочные белкипептидный профильхранение молочных продуктовферментативная порчаbioinformaticsmilk proteinspeptide profilestorage of dairy productsenzymatic spoilageReferencesBarati, F., Hosseini, F., Vafaee, R., Sabouri, Z., Ghadam, P., Arab, S. S., Shadfar, N., & Piroozmand, F. (2024). In silico approaches to investigate enzyme immobilization: A comprehensive systematic review. Physical Chemistry Chemical Physics, 26(7), 5744–5761. https://doi.org/10.1039/D3CP03989GBarati, F., Hosseini, F., Vafaee, R., Sabouri, Z., Ghadam, P., Arab, S. S., Shadfar, N., & Piroozmand, F. (2024). In silico approaches to investigate enzyme immobilization: A comprehensive systematic review. Physical Chemistry Chemical Physics, 26(7), 5744–5761. https://doi.org/10.1039/D3CP03989GBaur, C., Krewinkel, M., Kranz, B., Von Neubeck, M., Wenning, M., Scherer, S., Stoeckel, M., Hinrichs, J., Stressler, T., & Fischer, L. (2015). Quantification of the proteolytic and lipolytic activity of microorganisms isolated from raw milk. International Dairy Journal, 49, 23–29. https://doi.org/10.1016/j.idairyj.2015.04.005Baur, C., Krewinkel, M., Kranz, B., Von Neubeck, M., Wenning, M., Scherer, S., Stoeckel, M., Hinrichs, J., Stressler, T., & Fischer, L. (2015). Quantification of the proteolytic and lipolytic activity of microorganisms isolated from raw milk. International Dairy Journal, 49, 23–29. https://doi.org/10.1016/j.idairyj.2015.04.005Chavan, R. S., Chavan, S. R., Khedkar, C. D., & Jana, A. H. (2011). UHT Milk Processing and Effect of Plasmin Activity on Shelf Life: A Review. Comprehensive Reviews in Food Science and Food Safety, 10(5), 251–268. https://doi.org/10.1111/j.1541-4337.2011.00157.xChavan, R. S., Chavan, S. R., Khedkar, C. D., & Jana, A. H. (2011). UHT Milk Processing and Effect of Plasmin Activity on Shelf Life: A Review. Comprehensive Reviews in Food Science and Food Safety, 10(5), 251–268. https://doi.org/10.1111/j.1541-4337.2011.00157.xClass, L.-C., Kuhnen, G., Schmid, J., Rohn, S., & Kuballa, J. (2024). Marker Peptides for Indicating the Spoilage of Milk—Sample Preparation and Chemometric Approaches for Yielding Potential Peptides in a Raw Milk Model. Foods, 13(20), 3315. https://doi.org/10.3390/foods13203315Class, L.-C., Kuhnen, G., Schmid, J., Rohn, S., & Kuballa, J. (2024). Marker Peptides for Indicating the Spoilage of Milk—Sample Preparation and Chemometric Approaches for Yielding Potential Peptides in a Raw Milk Model. Foods, 13(20), 3315. https://doi.org/10.3390/foods13203315Crudden, A., Afoufa-Bastien, D., Fox, P. F., Brisson, G., & Kelly, A. L. (2005). Effect of hydrolysis of casein by plasmin on the heat stability of milk. International Dairy Journal, 15(10), 1017–1025. https://doi.org/10.1016/j.idairyj.2004.11.001Crudden, A., Afoufa-Bastien, D., Fox, P. F., Brisson, G., & Kelly, A. L. (2005). Effect of hydrolysis of casein by plasmin on the heat stability of milk. International Dairy Journal, 15(10), 1017–1025. https://doi.org/10.1016/j.idairyj.2004.11.001Dalabasmaz, S., Dittrich, D., Kellner, I., Drewello, T., & Pischetsrieder, M. (2019). Identification of peptides reflecting the storage of UHT milk by MALDI-TOF-MS peptide profiling. Journal of Proteomics, 207, 103444. https://doi.org/10.1016/j.jprot.2019.103444Dalabasmaz, S., Dittrich, D., Kellner, I., Drewello, T., & Pischetsrieder, M. (2019). Identification of peptides reflecting the storage of UHT milk by MALDI-TOF-MS peptide profiling. Journal of Proteomics, 207, 103444. https://doi.org/10.1016/j.jprot.2019.103444Dellafiora, L., Galaverna, G., Reverberi, M., & Dall’Asta, C. (2017). Degradation of Aflatoxins by Means of Laccases from Trametes versicolor: An In Silico Insight. Toxins, 9(1), 17. https://doi.org/10.3390/toxins9010017Dellafiora, L., Galaverna, G., Reverberi, M., & Dall’Asta, C. (2017). Degradation of Aflatoxins by Means of Laccases from Trametes versicolor: An In Silico Insight. Toxins, 9(1), 17. https://doi.org/10.3390/toxins9010017Du, L., Lu, W., Zhang, Y., Gao, B., & Yu, L. (2020). Detection of milk powder in liquid whole milk using hydrolyzed peptide and intact protein mass spectral fingerprints coupled with data fusion technologies. Food Science & Nutrition, 8(3), 1471–1479. https://doi.org/10.1002/fsn3.1430Du, L., Lu, W., Zhang, Y., Gao, B., & Yu, L. (2020). Detection of milk powder in liquid whole milk using hydrolyzed peptide and intact protein mass spectral fingerprints coupled with data fusion technologies. Food Science & Nutrition, 8(3), 1471–1479. https://doi.org/10.1002/fsn3.1430Fan, X., Wang, C., Cheng, M., Wei, H., Gao, X., Ma, M., Wang, X., & Li, Z. (2023). Markers and Mechanisms of Deterioration Reactions in Dairy Products. Food Engineering Reviews, 15(2), 230–241. https://doi.org/10.1007/s12393-023-09331-9Fan, X., Wang, C., Cheng, M., Wei, H., Gao, X., Ma, M., Wang, X., & Li, Z. (2023). Markers and Mechanisms of Deterioration Reactions in Dairy Products. Food Engineering Reviews, 15(2), 230–241. https://doi.org/10.1007/s12393-023-09331-9Fox, P. F., Uniacke-Lowe, T., McSweeney, P. L. H., & O’Mahony, J. A. (2015). Heat-Induced Changes in Milk. В P. F. Fox, T. Uniacke-Lowe, P. L. H. McSweeney, & J. A. O’Mahony, Dairy Chemistry and Biochemistry (сс. 345–375). Springer International Publishing. https://doi.org/10.1007/978-3-319-14892-2_9Fox, P. F., Uniacke-Lowe, T., McSweeney, P. L. H., & O’Mahony, J. A. (2015). Heat-Induced Changes in Milk. В P. F. Fox, T. Uniacke-Lowe, P. L. H. McSweeney, & J. A. O’Mahony, Dairy Chemistry and Biochemistry (сс. 345–375). Springer International Publishing. https://doi.org/10.1007/978-3-319-14892-2_9France, T. C., O’Mahony, J. A., & Kelly, A. L. (2021). The Plasmin System in Milk and Dairy Products. В A. L. Kelly & L. B. Larsen (Ред.), Agents of Change (сс. 11–55). Springer International Publishing. https://doi.org/10.1007/978-3-030-55482-8_2France, T. C., O’Mahony, J. A., & Kelly, A. L. (2021). The Plasmin System in Milk and Dairy Products. В A. L. Kelly & L. B. Larsen (Ред.), Agents of Change (сс. 11–55). Springer International Publishing. https://doi.org/10.1007/978-3-030-55482-8_2Gupta, A., Mann, B., Kumar, R., & Sangwan, R. B. (2010). Identification of antioxidant peptides in cheddar cheese made with adjunct culture Lactobacillus casei ssp. casei 300. Milchwissenschaft, 65(4), 396-399.Gupta, A., Mann, B., Kumar, R., & Sangwan, R. B. (2010). Identification of antioxidant peptides in cheddar cheese made with adjunct culture Lactobacillus casei ssp. casei 300. Milchwissenschaft, 65(4), 396-399.Iram, D., Sansi, M. S., Zanab, S., Vij, S., Ashutosh, & Meena, S. (2022). In silico identification of antidiabetic and hypotensive potential bioactive peptides from the sheep milk proteins—A molecular docking study. Journal of Food Biochemistry, 46(11). https://doi.org/10.1111/jfbc.14137Iram, D., Sansi, M. S., Zanab, S., Vij, S., Ashutosh, & Meena, S. (2022). In silico identification of antidiabetic and hypotensive potential bioactive peptides from the sheep milk proteins—A molecular docking study. Journal of Food Biochemistry, 46(11). https://doi.org/10.1111/jfbc.14137Kartal, C., Kaplan Türköz, B., & Otles, S. (2020). Prediction, identification and evaluation of bioactive peptides from tomato seed proteins using in silico approach. Journal of Food Measurement and Characterization, 14(4), 1865–1883. https://doi.org/10.1007/s11694-020-00434-zKartal, C., Kaplan Türköz, B., & Otles, S. (2020). Prediction, identification and evaluation of bioactive peptides from tomato seed proteins using in silico approach. Journal of Food Measurement and Characterization, 14(4), 1865–1883. https://doi.org/10.1007/s11694-020-00434-zKruchinin, A., & Bolshakova, E. (2022). Hybrid Strategy of Bioinformatics Modeling (in silico): Biologically Active Peptides of Milk Protein. Food Processing: Techniques and Technology, 46–57. https://doi.org/10.21603/2074-9414-2022-1-46-57Kruchinin, A., & Bolshakova, E. (2022). Hybrid Strategy of Bioinformatics Modeling (in silico): Biologically Active Peptides of Milk Protein. Food Processing: Techniques and Technology, 46–57. https://doi.org/10.21603/2074-9414-2022-1-46-57Kruchinin, A. G., Bolshakova, E. I., & Barkovskaya, I. A. (2023). Bioinformatic Modeling (In Silico) of Obtaining Bioactive Peptides from the Protein Matrix of Various Types of Milk Whey. Fermentation, 9(4), 380. https://doi.org/10.3390/fermentation9040380Kruchinin, A. G., Bolshakova, E. I., & Barkovskaya, I. A. (2023). Bioinformatic Modeling (In Silico) of Obtaining Bioactive Peptides from the Protein Matrix of Various Types of Milk Whey. Fermentation, 9(4), 380. https://doi.org/10.3390/fermentation9040380Lu, M., & Wang, N. S. (2017). Spoilage of Milk and Dairy Products. В The Microbiological Quality of Food (сс. 151–178). Elsevier. https://doi.org/10.1016/B978-0-08-100502-6.00010-8Lu, M., & Wang, N. S. (2017). Spoilage of Milk and Dairy Products. В The Microbiological Quality of Food (сс. 151–178). Elsevier. https://doi.org/10.1016/B978-0-08-100502-6.00010-8Matéos, A., Guyard-Nicodème, M., Baglinière, F., Jardin, J., Gaucheron, F., Dary, A., Humbert, G., & Gaillard, J.-L. (2015). Proteolysis of milk proteins by AprX, an extracellular protease identified in Pseudomonas LBSA1 isolated from bulk raw milk, and implications for the stability of UHT milk. International Dairy Journal, 49, 78–88. https://doi.org/10.1016/j.idairyj.2015.04.008Matéos, A., Guyard-Nicodème, M., Baglinière, F., Jardin, J., Gaucheron, F., Dary, A., Humbert, G., & Gaillard, J.-L. (2015). Proteolysis of milk proteins by AprX, an extracellular protease identified in Pseudomonas LBSA1 isolated from bulk raw milk, and implications for the stability of UHT milk. International Dairy Journal, 49, 78–88. https://doi.org/10.1016/j.idairyj.2015.04.008Meltretter, J., Schmidt, A., Humeny, A., Becker, C.-M., & Pischetsrieder, M. (2008). Analysis of the Peptide Profile of Milk and Its Changes during Thermal Treatment and Storage. Journal of Agricultural and Food Chemistry, 56(9), 2899–2906. https://doi.org/10.1021/jf073479oMeltretter, J., Schmidt, A., Humeny, A., Becker, C.-M., & Pischetsrieder, M. (2008). Analysis of the Peptide Profile of Milk and Its Changes during Thermal Treatment and Storage. Journal of Agricultural and Food Chemistry, 56(9), 2899–2906. https://doi.org/10.1021/jf073479oMinkiewicz, P., Iwaniak, A., & Darewicz, M. (2019). BIOPEP-UWM Database of Bioactive Peptides: Current Opportunities. International Journal of Molecular Sciences, 20(23), 5978. https://doi.org/10.3390/ijms20235978Minkiewicz, P., Iwaniak, A., & Darewicz, M. (2019). BIOPEP-UWM Database of Bioactive Peptides: Current Opportunities. International Journal of Molecular Sciences, 20(23), 5978. https://doi.org/10.3390/ijms20235978Muir, D. D. (2011). The stability and shelf life of milk and milk products. В Food and Beverage Stability and Shelf Life (сс. 755–778). Elsevier. https://doi.org/10.1533/9780857092540.3.755Muir, D. D. (2011). The stability and shelf life of milk and milk products. В Food and Beverage Stability and Shelf Life (сс. 755–778). Elsevier. https://doi.org/10.1533/9780857092540.3.755Nath, A., Eren, B. A., Zinia Zaukuu, J.-L., Koris, A., Pásztorné-Huszár, K., Szerdahelyi, E., & Kovacs, Z. (2022). Detecting the Bitterness of Milk-Protein-Derived Peptides Using an Electronic Tongue. Chemosensors, 10(6), 215. https://doi.org/10.3390/chemosensors10060215Nath, A., Eren, B. A., Zinia Zaukuu, J.-L., Koris, A., Pásztorné-Huszár, K., Szerdahelyi, E., & Kovacs, Z. (2022). Detecting the Bitterness of Milk-Protein-Derived Peptides Using an Electronic Tongue. Chemosensors, 10(6), 215. https://doi.org/10.3390/chemosensors10060215Panjaitan, F. C. A., Gomez, H. L. R., & Chang, Y.-W. (2018). In Silico Analysis of Bioactive Peptides Released from Giant Grouper (Epinephelus lanceolatus) Roe Proteins Identified by Proteomics Approach. Molecules, 23(11), 2910. https://doi.org/10.3390/molecules23112910Panjaitan, F. C. A., Gomez, H. L. R., & Chang, Y.-W. (2018). In Silico Analysis of Bioactive Peptides Released from Giant Grouper (Epinephelus lanceolatus) Roe Proteins Identified by Proteomics Approach. Molecules, 23(11), 2910. https://doi.org/10.3390/molecules23112910Pooja, K., Rani, S., Kanwate, B., & Pal, G. K. (2017). Physico-chemical, Sensory and Toxicity Characteristics of Dipeptidyl Peptidase-IV Inhibitory Peptides from Rice Bran-derived Globulin Using Computational Approaches. International Journal of Peptide Research and Therapeutics, 23(4), 519–529. https://doi.org/10.1007/s10989-017-9586-4Pooja, K., Rani, S., Kanwate, B., & Pal, G. K. (2017). Physico-chemical, Sensory and Toxicity Characteristics of Dipeptidyl Peptidase-IV Inhibitory Peptides from Rice Bran-derived Globulin Using Computational Approaches. International Journal of Peptide Research and Therapeutics, 23(4), 519–529. https://doi.org/10.1007/s10989-017-9586-4Quintieri, L., Caputo, L., Brasca, M., & Fanelli, F. (2021). Recent Advances in the Mechanisms and Regulation of QS in Dairy Spoilage by Pseudomonas spp. Foods, 10(12), 3088. https://doi.org/10.3390/foods10123088Quintieri, L., Caputo, L., Brasca, M., & Fanelli, F. (2021). Recent Advances in the Mechanisms and Regulation of QS in Dairy Spoilage by Pseudomonas spp. Foods, 10(12), 3088. https://doi.org/10.3390/foods10123088Remenant, B., Jaffrès, E., Dousset, X., Pilet, M.-F., & Zagorec, M. (2015). Bacterial spoilers of food: Behavior, fitness and functional properties. Food Microbiology, 45, 45–53. https://doi.org/10.1016/j.fm.2014.03.009Remenant, B., Jaffrès, E., Dousset, X., Pilet, M.-F., & Zagorec, M. (2015). Bacterial spoilers of food: Behavior, fitness and functional properties. Food Microbiology, 45, 45–53. https://doi.org/10.1016/j.fm.2014.03.009Sedaghati, M., Ezzatpanah, H., Mashhadi Akbar Boojar, M., Tajabadi Ebrahimi, M., & Kobarfard, F. (2016). Isolation and identification of some antibacterial peptides in the plasmin-digest of β-casein. LWT - Food Science and Technology, 68, 217–225. https://doi.org/10.1016/j.lwt.2015.12.019Sedaghati, M., Ezzatpanah, H., Mashhadi Akbar Boojar, M., Tajabadi Ebrahimi, M., & Kobarfard, F. (2016). Isolation and identification of some antibacterial peptides in the plasmin-digest of β-casein. LWT - Food Science and Technology, 68, 217–225. https://doi.org/10.1016/j.lwt.2015.12.019Stuknytė, M., Decimo, M., Colzani, M., Silvetti, T., Brasca, M., Cattaneo, S., Aldini, G., & De Noni, I. (2016). Extracellular thermostable proteolytic activity of the milk spoilage bacterium Pseudomonas fluorescens PS19 on bovine caseins. Journal of Dairy Science, 99(6), 4188–4195. https://doi.org/10.3168/jds.2016-10894Stuknytė, M., Decimo, M., Colzani, M., Silvetti, T., Brasca, M., Cattaneo, S., Aldini, G., & De Noni, I. (2016). Extracellular thermostable proteolytic activity of the milk spoilage bacterium Pseudomonas fluorescens PS19 on bovine caseins. Journal of Dairy Science, 99(6), 4188–4195. https://doi.org/10.3168/jds.2016-10894Thesbjerg, M. N., Nielsen, S. D.-H., Sundekilde, U. K., Poulsen, N. A., & Larsen, L. B. (2023). Fingerprinting of Proteases, Protease Inhibitors and Indigenous Peptides in Human Milk. Nutrients, 15(19), 4169. https://doi.org/10.3390/nu15194169Thesbjerg, M. N., Nielsen, S. D.-H., Sundekilde, U. K., Poulsen, N. A., & Larsen, L. B. (2023). Fingerprinting of Proteases, Protease Inhibitors and Indigenous Peptides in Human Milk. Nutrients, 15(19), 4169. https://doi.org/10.3390/nu15194169Van Asselt, A. J., Sweere, A. P. J., Rollema, H. S., & De Jong, P. (2008). Extreme high-temperature treatment of milk with respect to plasmin inactivation. International Dairy Journal, 18(5), 531–538. https://doi.org/10.1016/j.idairyj.2007.11.019Van Asselt, A. J., Sweere, A. P. J., Rollema, H. S., & De Jong, P. (2008). Extreme high-temperature treatment of milk with respect to plasmin inactivation. International Dairy Journal, 18(5), 531–538. https://doi.org/10.1016/j.idairyj.2007.11.019Verhegghe, M., De Block, J., Heyndrickx, M., Van Coillie, E., Van Poucke, C., & Duquenne, B. (2021). Application of LC‐HRMS identified marker peptides in an LC‐MS/MS method for detection and quantification of heat‐resistant proteolytic activity in raw milk. International Journal of Dairy Technology, 74(2), 286–296. https://doi.org/10.1111/1471-0307.12754Verhegghe, M., De Block, J., Heyndrickx, M., Van Coillie, E., Van Poucke, C., & Duquenne, B. (2021). Application of LC‐HRMS identified marker peptides in an LC‐MS/MS method for detection and quantification of heat‐resistant proteolytic activity in raw milk. International Journal of Dairy Technology, 74(2), 286–296. https://doi.org/10.1111/1471-0307.12754Xiong, Z., He, Y., Guan, W., Lv, X., Chen, J., & Ma, D. (2024). Investigating the impact of common migration substances found in milk packaging on proteases: A multispectral and molecular docking approach. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 318, 124517. https://doi.org/10.1016/j.saa.2024.124517Xiong, Z., He, Y., Guan, W., Lv, X., Chen, J., & Ma, D. (2024). Investigating the impact of common migration substances found in milk packaging on proteases: A multispectral and molecular docking approach. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 318, 124517. https://doi.org/10.1016/j.saa.2024.124517Yan, L., Langlois, B. E., O’Leary, J., & Hicks, C. L. (1985). Purification and Characterization of Four Extracellular Proteases Isolated from Raw Milk Psychrotrophs. Journal of Dairy Science, 68(6), 1323–1336. https://doi.org/10.3168/jds.S0022-0302(85)80968-1Yan, L., Langlois, B. E., O’Leary, J., & Hicks, C. L. (1985). Purification and Characterization of Four Extracellular Proteases Isolated from Raw Milk Psychrotrophs. Journal of Dairy Science, 68(6), 1323–1336. https://doi.org/10.3168/jds.S0022-0302(85)80968-1Zhang, Y., Aryee, A. N., & Simpson, B. K. (2020). Current role of in silico approaches for food enzymes. Current Opinion in Food Science, 31, 63–70. https://doi.org/10.1016/j.cofs.2019.11.003Zhang, Y., Aryee, A. N., & Simpson, B. K. (2020). Current role of in silico approaches for food enzymes. Current Opinion in Food Science, 31, 63–70. https://doi.org/10.1016/j.cofs.2019.11.003

The authors declare that there are no conflicts of interest present.