Goat Milk Casein Peptides as Potential α-Amylase Inhibitors: A Computational and Experimental Approach

Gavriel Hagai Paulus Sumlang; Rumaisha Lale Handoyo; Marlyn Dian Laksitorini; Endang Astuti; Tri Joko Raharjo

doi:10.22146/ijc.100223

Goat Milk Casein Peptides as Potential α-Amylase Inhibitors: A Computational and Experimental Approach

https://doi.org/10.22146/ijc.100223

Gavriel Hagai Paulus Sumlang⁽¹⁾, Rumaisha Lale Handoyo⁽²⁾, Marlyn Dian Laksitorini⁽³⁾, Endang Astuti⁽⁴⁾, Tri Joko Raharjo^(5*)

(1) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(2) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(3) Department of Pharmaceutics, Faculty of Pharmacy, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(4) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(5) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(*) Corresponding Author

Abstract

Goat’s milk proteins can undergo hydrolysis during digestion, producing peptides that may inhibit α-amylase and help treat type 2 diabetes with minimal side effects. Identifying the amino acid composition of these peptides is essential for determining their inhibitory potential. Recent in silico digestion methods have been developed to generate specific peptides. This study aims to identify α-amylase inhibitory peptides from goat’s milk casein hydrolyzate using in silico digestion, followed by peptide synthesis and activity assay. Peptides were derived from goat’s milk casein hydrolyzed using in silico digestion. Molecular docking was employed to predict protein-peptide interactions utilizing the HADDOCK2.4 server, CABS-dock, and PepSite 2 server. Peptides EDVPSER and TNAIPYVR could inhibit α-amylase with IC₅₀ values of 14.16 ± 0.65 and 76.58 ± 2.13 µM, respectively. In vitro evaluation confirmed that EDVPSER from α_S1-casein exhibited α-amylase inhibitory potential. This peptide could be developed as a potential therapeutic agent for type 2 diabetes, offering a natural and targeted approach to α-amylase inhibition. Peptide EDVPSER may serve as a basis for further research and development of antidiabetic treatments derived from goat’s milk proteins.

Keywords

α-amylase; in silico digestion; molecular docking; peptide

Full Text:

Full Text PDF

References

[1] Berraquero-Garcia, C., Rivero-Pino, F., Ospina, J.L., Pѐrez-Galvez, R., Espejo-Carpio, F.J., Guadix, A., Garcia-Moreno, P.J., and Guadix, E.M., 2023, Activity, structural features and in silico digestion of antidiabetic peptides, Food Biosci., 55 (19), 102954.

[2] Khan, M.A.B., Hashim, M.J., King, J.K., Govender, R.D., Mustafa, H., and Kaabi, J.A., 2020, Epidemiology of type 2 diabetes – Global burden of disease and forecasted trends, J. Epidemiol. Global Health, 1 (10), 107–111.

[3] Chandrasekaran, P., and Weiskirchen, R., 2024, The role of obesity in type 2 diabetes mellitus – An overview, Int. J. Mol. Sci., 25 (3), 1882.

[4] Famuwagun, A.A., Alashi, A.M., Gbadamosi, O.S., Taiwo, K.A., Oyedele, D., Adebooye, O.C., and Aluko, R.E., 2021, Antioxidant and enzymes inhibitory properties of Amaranth leaf protein hydrolyzates and ultrafiltration peptide fractions, J. Food Biochem., 45 (3), e13396.

[5] Dujic, T., Causevic, A., Bego, T., Malenica, M., Velija-Asimi, Z., Pearson, E.R., and Semiz, S., 2015, Organic cation transporter 1 variants and gastrointestinal side effects of metformin in patients with type 2 diabetes, Diabetic Med., 33 (4), 511–514.

[6] Fadimu, G.J., Gill, H., Farahnaky, A., and Truong, T., 2022, Improving the enzymolysis efficiency of lupin protein by ultrasound pretreatment: Effect on antihypertensive, antidiabetic and antioxidant activities of the hydrolysates, Food Chem., 383, 132457.

[7] Singh, B.P., Paul, S., and Goel, 2024, Shotgun proteomics and molecular simulations on multifunctional bioactive peptides derived from the whey of unexplored “Gaddi” goat of Himalayas, Food Chem., 430, 137075.

[8] Martini, S., Solieri, L., Cattivelli, A., Pizzamiglio, V., and Tagliazucchi, D., 2021, An integrated peptidomics and in silico approach to identify novel anti-diabetic peptides in Parmigiano-Reggiano cheese, Biology, 10 (6), 563.

[9] Esfandi, R., Seidu, I., Willmore, W., and Tsopmo, A., 2022, Antioxidant, pancreatic lipase, and α-amylase inhibitory properties of oat bran hydrolyzed proteins and peptides, J. Food Biochem., 46 (4), e13762.

[10] Guetouache, M., Guessas, B., and Medjekal, S., 2014, Composition and nutritional value of raw milk, Biol. Sci. Pharm. Res., 10 (2), 115–122.

[11] Al Mazroea, A., Alharby, M.A., Almughatwai, A.A., Al-Remaithi, S.M., Saeed, R.M., Alharbi, A.F., and Saeed, H.M., 2018, Comparison between nutritional values in cow’s milk, and goat milk infant formulas, Int. J. Pharm. Res. Allied Sci., 4 (7), 190–195.

[12] Wang, Z., Jiang, S., Ma, C., Huo, D., Peng, Q., Shao, Y., and Zhang, J., 2018, Evaluation of the nutrition and function of cow and goat milk based on intestinal microbiota by metagenomic analysis, Food Funct., 4 (9), 2320–2327.

[13] Campos, M.I.F., Barbosa, P.P., Camargo, L.J., Pinto, L.D., Mataribu, B., Serrão, C., Marques-Santos, L.F., Lopes, J.H., Oliveira, J.M.G., Gadelha, C.A., and Santi-Gadelha, T., 2022, Characterization of goat whey proteins and their bioactivity and toxicity assay, Food Biosci., 46, 101591.

[14] Barati, M., Javanmardi, F., Jabbari, M., Mokari-Yamchi, A., Farahmand, F., Eş, I., Farhadnejad, H., Davoodi, S.H., and Khaneghah, A.M., 2020, An in silico model to predict and estimate digestion-resistant and bioactive peptide content of dairy products: A primarily study of a time-saving and affordable method for practical research purposes, LWT, 130, 109616.

[15] Kęska, P., Stadnik, J., Łupawka, A., and Michalska, A., 2023, Novel α-glucosidase inhibitory peptides identified in silico from dry-cured pork loins with probiotics through peptidomic and molecular docking analysis, Nutrients, 15 (16), 3539.

[16] Weng, G., Gao, J., Wang, Z., Wang, E., Hu, X., Yao, X., Cao, D., and Hou, T., 2020, Comprehensive evaluation of fourteen docking programs on protein–peptide complexes, J. Chem. Theory Comput., 16 (6), 3959–3969.

[17] Ciemny, M., Kurcinski, M., Kamel, K., Kolinski, A., Alam, N., Schueler-Furman, O., and Kmiecik, S., 2018, Protein–peptide docking: Opportunities and challenges, Drug Discovery Today, 23 (8), 1530–1537.

[18] Choi, S., Son, S.H., Kim, M.Y., Na, I., Uversky, V.N., and Kim, C.G., 2023, Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination, Int. J. Biol. Macromol., 252, 126526.

[19] Trabuco, L.G., Lise, S., Petsalaki, E., and Russel, R.B., 2012, PepSite: Prediction of peptide-binding sites from protein surfaces, Nucleic Acids Res., 40 (W1), W423–W427.

[20] Fadimu, G.J., Farahnaky, A., Gill, H., Olalere, O.A., Gan, C.Y., and Truong, T., 2022, In silico analysis and antidiabetic effect of α-amylase and α-glucosidase inhibitory peptides from lupin protein hydrolysate: Enzyme-peptide interaction study using molecular docking approach, Foods, 11 (21), 3375.

[21] Evaristus, N.A., Wan Abdullah, W.N., and Gan, C.Y., 2018, Extraction and identification of α-amylase inhibitor peptides from Nephelium lappacheum and Nephelium mutabile seed protein using gastro-digestive enzymes, Peptides, 102, 61–67.

[22] Huang, Y., Richardson, S.J., Brennan, C.S., and Kasapis, S., 2024, Mechanistic insights into α-amylase inhibition, binding affinity and structural changes upon interaction with gallic acid, Food Hydrocoll., 148, 109467.

[23] Mohd Rodhi, A., Yap, P.G., Olalere, O.A., and Gan, C.Y., 2024, Unveiling α-amylase inhibition: A bioinformatics perspective on peptide properties and amino acid contributions, J. Mol. Struct., 1305, 137768.

[24] Honorato, R.V., Trellet, M.E., Jiménez-García, B., Schaarschmidt, J.J., Giulini, M., Reys, V., Koukos, P.I., Rodrigues, J.P.G.L.M., Karaca, E., van Zundert, G.C.P., Roel-Touris, J., van Noort, C.W., Jandová, Z., Melquiond, A.S.J., and Bonvin, A.M.J.J., 2024, The HADDOCK2.4 web server for integrative modeling of biomolecular complexes, Nat. Protoc., 19 (11), 3219–3241.

[25] Honorato, R.V., Koukos, P.I., Jiménez-García, B., Tsaregorodtsev, A., Verlato, M., Giachetti, A., Rosato, A., and Bonvin, A.M.J.J., 2021, Structural biology in the clouds: The WeNMR-EOSC ecosystem, Front. Mol. Biosci., 8, 729513.

[26] Kurcinski, M., Jamroz, M., Blaszczyk, M., Kolinski, A., and Kmiecik, S., 2015, CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site, Nucleic Acid Res., 43 (W1), W419–W424.

[27] Benoit, S., Chaumontet, C., Violle, N., Boulier, A., Hafeez, Z., Cakir-Kiefer, C., Tomé, D., Schwarz, J., and Miclo, L., 2022, The anxiolytic-like properties of a tryptic hydrolysate of bovine α_s1 casein containing α-casozepine rely on GABA_A receptor benzodiazepine binding sites but not the vagus nerve, Nutrients, 14 (11), 2212.

[28] Shanmugam, V.P., Kapila, S., Sonfack, T.K., and Kapila, R, 2015, Antioxidative peptide derived from enzymatic digestion of buffalo casein, Int. Dairy J., 42, 1–5.

[29] Zhang, Y., Wang, N., Wang, W., Wang, J., Zhu, Z., and Li, X., 2016, Molecular mechanisms of novel peptides from silkworm pupae that inhibit α-glucosidase, Peptides, 76, 45–50.

[30] Reddi, S., Shanmugam, V.P., Tanedjeu, K.S., Kapila, S., and Kapila, R., 2018, Effect of buffalo casein-derived novel bioactive peptides on osteoblast differentiation, Eur. J. Nutr., 57 (2), 593–605.

[31] McClean, S., Beggs, L.B., and Welch, R.W., 2014, Antimicrobial activity of antihypertensive food-derived peptides and selected alanine analogues, Food Chem., 146, 443–447.

[32] Sedaghati, M., Ezzatpanah, H., Mashhadi Akbar Boojar, M., Tajabadi Ebrahimi, M., and Kobarfard, F., 2016, Isolation and identification of some antibacterial peptides in the plasmin-digest of β-casein, LWT - Food Sci. Technol., 68, 217–225.

[33] Kumar, N., Devi, S., Mada, S.B., Reddi, S., Kapila, R., and Kapila, S., 2020, Anti-apoptotic effect of buffalo milk casein derived bioactive peptide by directing Nrf2 regulation in starving fibroblasts, Food Biosci., 35, 100566.

[34] Kumar, N., Reddi, S., Devi, S., Mada, S.B., Kapila, R., and Kapila, S., 2019, Nrf2 dependent antiaging effect of milk-derived bioactive peptide in old fibroblasts, J Cell Biochem., 120 (6), 9677–9691.

[35] Plaisancié, P., Boutrou, R., Estienne, R., Henry, G., Jardin, J., Paquet, A., and Léonil, J., 2015, β-Casein(94-123)-derived peptides differently modulate production of mucins in intestinal goblet cells, J. Dairy Res., 82 (1), 36–46.

[36] Chiba, H., Tani, F., and Yoshikawa, M., 1989, Opioid antagonist peptides derived from κ-casein, J. Dairy Res., 56 (3), 363–366.

[37] Helmy, M.W., Youssef, M.H., Yamari, I., Amr, A., Moussa, F.I., El Wakil, A., Chtita, S., El-Samad, L.M., and Hassan, M.A., 2024, Repurposing of sericin combined with dactolisib or vitamin D to combat non-small lung cancer cells through computational and biological investigations, Sci. Rep., 14 (1), 27034.

[38] Chen, D., Oezguen, N., Urvil, P., Ferguson, C., Dann, S.M., and Savidge, T.C., 2016, Regulation of protein-ligand binding affinity by hydrogen bond pairing, Sci. Adv., 2 (3), e1501240.

[39] Nagy, G., and Grubmuller, H., 2021, Implementation of a Bayesian secondary structure estimation method for the SESCA circular dichroism analysis package, Comput. Phys. Commun., 266, 108022.

[40] Marella, S., 2018, Antidiabetic plant proteins/peptides as complementary and alternative medicine – Analytical perspectives, Rev. Anal. Chem., 37 (4), 20170025.

[41] Fillería, S.G., Nardo, A.E., Paulino, M., and Tironi, V., 2021, Peptides derived from the gastrointestinal digestion of amaranth 11S globulin: Structure and antioxidant functionality, Food Chem.: Mol. Sci., 3, 100053.

DOI: https://doi.org/10.22146/ijc.100223