In silico analysis of freshwater fish major histocompatibility complex class II alpha
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Published:
Apr 26, 2017
Keywords:
Freshwater fish MHC IIα physicochemical characterisation protein structure.
Main Article Content
Abstract
Major histocompatibility complex (MHC) plays important roles in the immune system of vertebrates. This current study aimed to clearly understand the properties and structures of the MHC class II alpha (MHC IIα) proteins selected from freshwater fish species using in silico analysis. The MHC IIα of Ctenopharyngodon idella, Oreochromis niloticus, Cyprinus carpio, Danio rerio, Oncorhynchus mykiss, and Ictalurus punctatus were used. The molecular weight of MHC IIα of fish species was arranged from 17,054.5 to 26,358.9 Da. The three domains: “Class II histocompatibility antigen, alpha domain” (MHC_II_alpha), “Immunoglobulin C-Type” (IGc1) and “Transmembrane region” were found in the proteins. Physicochemical characterisation showed theoretical isoelectric point (pI: 4.31~5.3), total number of positive and negative residues (+R/-R: 19~32/13~20), extinction coefficient (EC: 18,910~29,910/19,410~30,410 M-1.cm-1, assuming that all pairs of cysteine residues form cysteines/all cysteines are reduced), instability index (II: 27.1~41.4), aliphatic index (AI: 73.3~93.3) and Grand average of hydropathicity (GRAVY: -0.240~0.156). Cysteine residues and disulphide bonds were determined from the proteins. In secondary structure prediction, excepting for the protein of common carp (extended strand was dominated), all proteins were composed of random coils as predominant, followed by extended strands, alpha helix and beta turn. Three dimensional structures of proteins were predicted performing SWISS-MODEL server. All models were evaluated being accepted and reliable based on structural evaluation and stereochemical analyses. This study provides knowledge of the physiochemical characterisations, structure features and functions of MHC IIα from freshwater fishes that is useful for further researches on the field of immune-related study of aquatic animals in future.
Article Details
How to Cite
Tuan, T. N., & Duc, P. M. (2017). In silico analysis of freshwater fish major histocompatibility complex class II alpha. Asia-Pacific Journal of Science and Technology, 21(4), APST–21. https://doi.org/10.14456/apst.2016.18
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Research Articles
References
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[35] Hogg, P.J., 2003. Disulfide bonds as switches for protein function. Trends in Biochemical Sciences 28, 210-214.
[36] Cai, S., Singh, B.R., 1999. Identification of beta-turn and random coil amide III infrared bands for secondary structure estimation of proteins. Biophysical Chemistry 80, 7-20.
[37] Banerjee, A.K., Arora, N., Murty, U., 2012. Analyzing a potential drug target N-Myristoyltransferase of Plasmodium falciparum through in silico approaches. Journal of Global Infectious Diseases 4, 43-54.
[38] Sippl, M.J., 1993. Recognition of errors in three-dimensional structures of proteins. Proteins: Structure, Function, and Genetics 17, 355-362.
[39] Yadav, N.K., Shukla, P., Pareek, S., Singh, R., 2013. Structure prediction and functional characterization of matrix protein of Human Metapneumovirus (strain can97-83) (hMPV). International Journal of Advanced Life Sciences 6, 538-548.
[2] Lohm, J., Grahn, M., Langefors, Å., Andersen, Ø., Storset, A., Schantz, T. von, 2002. Experimental evidence for major histocompatibility complex–allele–specific resistance to a bacterial infection. Proceedings of the Royal Society of London B: Biological Sciences 269, 2029–2033.
[3] Barribeau, S.M., Villinger, J., Waldman, B., 2008. Major histocompatibility complex based resistance to a common bacterial pathogen of amphibians. PLoS ONE 3, e2692.
[4] Klein, J., Figueroa, F., 1985. Evolution of the major histocompatibility complex. Critical Reviews in Immunology 6, 295-386.
[5] Xu, T., Sun, Y., Shi, G., Cheng, Y., Wang, R., 2011. Characterization of the major histocompatibility complex class II genes in miiuy croaker. PloS One 6, e23823.
[6] Dixon, B., van Erp, S.H.M., Rodrigues, P.N.S., Egberts, E., Stet, R.M., 1995. Fish major histocompatibility complex genes: An expansion. Developmental & Comparative Immunology 19, 109–133.
[7] Yaneva, R., Schneeweiss, C., Zacharias, M., Springer, S., 2010. Peptide binding to MHC class I and II proteins: New avenues from new methods. Molecular Immunology 47, 649-657.
[8] Rothbard, J., Gefter, M.L., 1991. Interactions between immunogenic peptides and MHC proteins. Annual Review of Immunology 9, 527-565.
[9] König, R., Huang, L.Y., Germain, R.N., 1992. MHC class II interaction with CD4 mediated by a region analogous to the MHC class I binding site for CD8. Nature 356, 796–798.
[10] Piertney, S., Oliver, M., 2006. The evolutionary ecology of the major histocompatibility complex. Heredity 96, 7-21.
[11] Pang, J.-C., Gao, F.-Y., Lu, M.-X., Ye, X., Zhu, H.-P., Ke, X.-L., 2013. Major histocompatibility complex class IIA and IIB genes of Nile tilapia Oreochromis niloticus: Genomic structure, molecular polymorphism and expression patterns. Fish & Shellfish Immunology 34, 486-496.
[12] Zhang, Y.-X., Chen, S.-L., 2006. Molecular identification, polymorphism, and expression analysis of major histocompatibility complex class IIA and B genes of turbot (Scophthalmus maximus). Marine Biotechnology 8, 611-623.
[13] Xu, T.-J., Chen, S.-L., Ji, X.-S., Sha, Z.-X., 2009. Molecular cloning, genomic structure, polymorphism and expression analysis of major histocompatibility complex class IIA and IIB genes of half-smooth tongue sole (Cynoglossus semilaevis). Fish & Shellfish Immunology 27, 192-201.
[14] Yu, S., Ao, J., Chen, X., 2010. Molecular characterization and expression analysis of MHC class II alpha and beta genes in large yellow croaker (Pseudosciaena crocea). Mol Biol Rep 37, 1295–1307.
[15] Luo, W., Zhang, J., Wen, J-F., Liu, H., Wang, W-M., Gao, Z-X., 2014. Molecular cloning and expression analysis of major histocompatibility complex class I, IIA and IIB genes of blunt snout bream (Megalobrama amblycephala). Developmental & Comparative Immunology 42, 169-173.
[16] Pradeep, N., Anupama, A., Vidyashree, K., Lakshmi, P., 2012. In silico characterization of industrial important cellulases using computational tools. Advances in Life Science and Technology, 48-14.
[17] Verma, N.K., Singh, B., 2013. Insight from the structural molecular model of cytidylate kinase from Mycobacterium tuberculosis. Bioinformation 9, 680-684.
[18] Munir, F., Naqvi, S.M.S., Mahmood, T., 2013. In vitro and in silico characterization of Solanum lycopersicum wound-inducible proteinase inhibitor-II gene. Turkish Journal of Biology 37, 1-10.
[19] Vidhya, V., Upgade, A., Bhaskar, A., Deb, D., 2012. In silico characterization of bovine (Bos taurus) antiapoptotic proteins. Journal of Proteins & Proteomics 3, 187-196.
[20] Hossain, M.M., 2012. Fish antifreeze proteins: Computational analysis and physicochemical characterization. International Current Pharmaceutical Journal 1, 18-26.
[21] Goel, C., Barat, A., Pande, V., Sahoo, P., 2013. Comparative in silico analysis of Mbl homologues of teleosts. World Journal of Fish and Marine Sciences 5, 426-429.
[22] Tuan, T.N., Wei-Min, W., 2015. Freshwater fish myeloid differentiation primary response protein MyD88: Characterisation and homology modelling by using computational tools. Asian Fisheries Science 28, 1-14.
[23] Tuan, T.N., Wei-Min, W., Duc, P.M., 2015. Characterisation and homology modelling of finfish NF-Kappa B inhibitor alpha using in silico analysis. Journal of Sciences and Development 13, 216-225.
[24] Tran, N.T., Liu, H., Jakovlić, I., Wang, W.-M., 2015. Blunt Snout Bream (Megalobrama amblycephala) MyD88 and TRAF6: Characterisation, Comparative Homology Modelling and Expression. International Journal of Molecular Sciences 16, 7077–7097.
[25] Tran, N.T., Jakovlić, I., Wang, W.-M., 2015. In silico characterisation, homology modelling and structure-based functional annotation of blunt snout bream (Megalobrama amblycephala) Hsp70 and Hsc70 proteins. Journal of Animal Science and Technology 57, 44.
[26] Tamura, K., Stecher, G., Peterson, D., Filipski, A., Kumar, S., 2013. MEGA6: Molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution 30, 2725-2729.
[27] Fiser, A., 2004. Template-based protein structure modeling. D Fenyo. Computational Biology: Humana Press.
[28] Laskowski, R.A., Rullmann, J.A.C., MacArthur, M.W., Kaptein, R., Thornton, J.M., 1996. AQUA and PROCHECK-NMR: Programs for checking the quality of protein structures solved by NMR. Journal of Biomolecular NMR 8, 477-486.
[29] Ramachandran, G., Ramakrishnan, C., Sasisekharan, V., 1963 Stereochemistry of polypeptide chain configurations. Journal of Molecular Biology 7, 95-99.
[30] Wallner, B., Elofsson, A., 2003. Can correct protein models be identified? Protein Science 12, 1073-1086.
[31] Wiederstein, M., Sippl, M.J., 2007. ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Research 35, 407-410.
[32] Guruprasad, K., Reddy, B.B., Pandit, M.W., 1990. Correlation between stability of a protein and its dipeptide composition: A novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Engineering 4, 155-161.
[33] Ikai, A., 1980. Thermostability and aliphatic index of globular proteins. Journal of Biochemistry 88, 1895-1898.
[34] Kyte, J., Doolittle, R.F., 1982. A simple method for displaying the hydropathic character of a protein. Journal of Molecular Biology 157, 105-132.
[35] Hogg, P.J., 2003. Disulfide bonds as switches for protein function. Trends in Biochemical Sciences 28, 210-214.
[36] Cai, S., Singh, B.R., 1999. Identification of beta-turn and random coil amide III infrared bands for secondary structure estimation of proteins. Biophysical Chemistry 80, 7-20.
[37] Banerjee, A.K., Arora, N., Murty, U., 2012. Analyzing a potential drug target N-Myristoyltransferase of Plasmodium falciparum through in silico approaches. Journal of Global Infectious Diseases 4, 43-54.
[38] Sippl, M.J., 1993. Recognition of errors in three-dimensional structures of proteins. Proteins: Structure, Function, and Genetics 17, 355-362.
[39] Yadav, N.K., Shukla, P., Pareek, S., Singh, R., 2013. Structure prediction and functional characterization of matrix protein of Human Metapneumovirus (strain can97-83) (hMPV). International Journal of Advanced Life Sciences 6, 538-548.