Anticancer activity of cow, sheep, goat, mare, donkey and camel milks and their caseins and whey proteins and in silico comparison of the caseins

Document Type : Original article

Authors

Department of Biotechnology, Faculty of Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran

Abstract

The present investigation was carried out to evaluate anticancer activity of cow, goat, sheep, mare, donkey and camel milks and their casein and whey proteins against MCF7 cell line. The structure-based properties of the casein proteins were also investigated, using bioinformatics tools to find explanation for their antitumor activities. The effect of different milks and their casein and whey proteins on MCF7 proliferation was measured using MTT assay at different concentrations (0.5, 1 and 2 mg/ml). The results showed that mare, donkey, cow and camel milks and their casein and whey proteins have potent cytotoxic activity against MCF7 cells in a dose dependent manner while sheep and goat milks and their proteins did not reveal any cytotoxic activity. The in silico results demonstrated that mare, donkey and camel caseins had highest positive and negative charges. The secondary structure prediction indicated that mare and donkey caseins had the maximum percentage of α helix and camel casein had the highest percentage of extended strand. This study suggests that there is a striking correlation between anti-cancer activity of milk caseins and their physicochemical properties such as alpha helix structure and positive and negative charges. In conclusion, the results indicated that mare, camel and donkey milks might be good candidates against breast cancer cells.

Keywords

References

1. Jabbari S, Hasani R, Kafilzadeh F, Janfeshan S. Antimicrobial peptides from milk proteins: a prospectus. Ann Biol Res 2012;3:5313-5318.
2. López-Expósito I, Quirós A, Amigo L, Recio I. Casein hydrolysates as a source of antimicrobial, antioxidant and antihypertensive peptides. Lait 2007;87:241-249.
3. Bellamy W, Yamauchi K, Wakabayashi H, Takase M, Takakura N, Shimamura S, Tomita M. Antifungal properties of lactoferricin B, a peptide derived from the N‐terminal region of bovine lactoferrin. Lett Appl Microbiol 1994;18:230-233.
4. Lahov E, Regelson W. Antibacterial and immunostimulating casein-derived substances from milk: casecidin, isracidin peptides. Food Chem Toxicol 1996;34: 131-145.
5. Salami M, Moosavi-Movahedi AA, Ehsani MR, Yousefi R, Haertlé T, Chobert JM, Razavi SH, Henrich R, Balalaie S, Ebadi SA, Pourtakdoost S. Improvement of the antimicrobial and antioxidant activities of camel and bovine whey proteins by limited proteolysis. J Agric Food Chem 2010;58:3297-3302.
6. Mao X, Gu J, Sun Y, Xu S, Zhang X, Yang H, Ren F. Anti-proliferative and anti-tumour effect of active components in donkey milk on A549 human lung cancer cells. Int Dairy J 2009;19:703-708.
7. Hatzoglou A, Bakogeorgou E, Hatzoglou C, Martin PM, Castanas E. Antiproli-ferative and receptor binding properties of α-and β-casomorphins in the T47D human breast cancer cell line. Eur J Pharmacol 1996;310:217-223.
8. Herrouin M, Mollé D, Fauquant J, Ballestra F, Maubois JL, Léonil J. New genetic variants identified in donkey's milk whey proteins. J Protein Chem 2000;19:105-116.
9. Brian JP, Zakary LW and Seth JC. Dasatinib synergizes with both cytotoxic and signal transduction inhibitors in heterogeneous breast cancer cell lines: lessons for design of combination targeted therapy. Cancer Lett 2012;320:104-110.
10. Mosmann T. Rapid colorimetric assay for cellular growth and survival Application to proliferation and cytotoxicity assays. J Immunol Methods 1983;65:55-63.
11. Morgan DM. Tetrazolium (MTT) assay for cellular viability and activity. Polyamine protocols, Humana Press, Totowa, NJ, 1998:179-184.
12. Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, Söding J, Thompson JD. Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol 2011;7:1-9.
13. Garnier J, Gibrat JF, Robson B. GOR method for predicting protein secondary structure from amino acid sequence. Meth Enzymol 1996;266:540-553.
14. Costantini S, Colonna G, Facchiano AM. Amino acid propensities for secondary structures are influenced by the protein structural class. Biochem Biophys Res Commun 2006;342:441-451.
15. Lin K, Simossis VA, Taylor WR, Heringa J. A simple and fast secondary structure prediction method using hidden neural networks. Bioinformatics 2005;21:152-159.
16. Gasteiger E, Hoogland C, Gattiker A, Duvaud SE, Wilkins MR, Appel RD, Bairoch A. Protein identification and analysis tools on the ExPASy server. Humana Press; 2005. 571-607.
17. Petersen B, Petersen TN, Andersen P, Nielsen M, Lundegaard C. A generic method for assignment of reliability scores applied to solvent accessibility predictions. BMC Struct Biol 2009;9:51-61.
18. Rahmat A, Rosli R, Tan MH, Umar-Tsafe N, Ali AM, Bakar A, Fadzelly M. Comparative evaluation of cytotoxic effects of milk from various species on leukemia cell lines. Malays J Med Health Sci 2006;2:1-10.
19. Huang R, Mendis E, Rajapakse N, Kim SK. Strong electronic charge as an important factor for anticancer activity of chitooligosaccharides (COS). Life Sci 2006;78:2399-2408.
20. Huang Y, Feng QI, Yan Q, Hao X, Chen Y. Alpha-helical cationic anticancer peptides: a promising candidate for novel anticancer drugs. Mini Rev Med Chem 2015;15:73-81.

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