HOMOLOGY MODELING EPITOP ISOCITRATE DEHYDROGENASE TIPE 1 (R132H) MENGGUNAKAN MODELLER, I-TASSER DAN (PS)2 UNTUK VAKSIN GLIOMA
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Issue
Vol. 4 No. 1 (2017)
Vol. 4 No. 1 (2017)
Submitted
February 21, 2017
February 21, 2017
Published
April 29, 2017
April 29, 2017
Keywords:
Abstract
Glioma is a type of primary malignant brain tumor. The presence of gliomas can be characterized by a mutation R132H of isocitrate dehydrogenase type 1 (IDH1). IDH1 (R132H) contains specific immunogenic epitopes to the tumor. It is appropriate to be used as a gliomas vaccine. Therefore, it was necessary to do homology modeling for IDH1 (R132H) epitopes. TMHMM, MEMSAT-SVM and MEMSAT3 were used to predict transmembrane topology of IDH1 (R132H). Analysis of IDH1 (R132H) epitopes was performed using NetMHCII and IEDB®. The antigenicity of epitopes were predicted using VaxiJen to obtained 91 epitopes. Homology modeling using Modeller, I-TASSER and (PS)2 was established for the epitopes that have probability as tumor antigen. The results of homology modeling of IDH1 (R132H) epitopes were validated by MolProbity, ProSA-web dan QMEAN. A 3D stucture model of the epitopes was selected from three models from the homology modeling based on the validation results. Refinement was established on the epitopes using GalaxyRefine and GROMACS for energy minimization.
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References
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Wang, P., Sidney, J., Kim, Y., Sette, A., Lund, O., dan Nielsen, M., Peters, B., 2010. Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinformatics 11, 568-579
Wiederstein, M. dan 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
Yang, B., Zhong, C., Peng, Y., Lai, Z., dan Ding, J., 2010. Molecular mechanisms of "off-on switch” of activities of human IDH1 by tumor-associated mutation R132H. Cell Research 20, 1188-1200
Yang, J., Yan, R., Roy, A., Xu, D., Poisson, J., dan Zhang, Y., 2015. The I-TASSER suite: Protein structure and function prediction. Nature Methods 12, 7-18
Zahroh, H., Ma'rup, A., Tambunan, U. S. F., dan Parikesit, A. A., 2016. Immunoinformatics Approach in Designing Epitope-based Vaccine Against Meningitis-inducing Bacteria (Streptococcus pneumoniae, Neisseria meningitidis, and Haemophilus influenzae Type b). Drug Target Insights 10, 19-29
Zhang, Y., 2008. I-TASSER server for protein 3D structure prediction. BMC Bioinformatics 9, 40-47
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Andreatta, M., Schafer-Nielsen, C., Lund, O., Buus, S., Nielsen, M., 2011. NNAlign: A Web-Based Prediction Method Allowing Non-Expert End-User Discovery of Sequence Motifs in Quantitative Peptide Data. PLoS ONE, 61-11
Arita, H., Narita, Y., Yoshida, A., Hashimoto, N., Yoshimine, T., Ichimura K., 2015. IDH1/2 Mutation Detection in Gliomas. Brain Tumor Pathol 32, 79-89
Balss, J., Meyer, J., Mueller, W., Korshunov, A., Hartmann, C., Deimling, A., 2008. Analysis of The IDH1 Codon 132 Mutation in Brain Tumors. Acta Neuropathol 116, 597-602
Benkert, P., Biasini, M., Schwede, T., 2011. Toward The Estimation of The Absolute Quality of Individual Protein Structure Models. Original Paper 27, 343-350
Benkert, P., Kunzli, M., Schwede, T., 2009. QMEAN Server for Protein Model Quality Estimation. Nucleic Acids Research 37, 510-514
Bleeker, F. E., Atai, N. A., Lamba, S., Jonker, A., Rijkeboer, D., Bosch, K. S. Tigchelaar, W., Troost, D., Vandertop, W. P., Bardelli, A., Noorden C. J. F. V., 2010. The Prognostic IDH1 R132 Mutation is Associated with Reduced NADP+-Dependent IDH Activity in Glioblastoma. Acta Neuropathol 119, 487-494
Chen, C., Hwang, J., Yang, J., 2006. (PS)2: Protein Structure Prediction Server. Nucleic Acids Research 34, 152-157
Chen, C., Hwang, J., Yang, J., 2009. (PS)2-v2: Template-Based Protein Structure Prediction Server. BMC Bioinformatics 10, 366-378
Chen, V. B., W. Arendall, B., Headd, J. J., Keedy D. A., Immormino R. M., Kapral, G. J., Murray L. W., Richardson, J. S., Richardson, D. C., 2010. MolProbity: All-Atom Structure Validation for Macromolecular Crystallography. Acta Crystallographica 66, 12-21
Cherryholmes, G. A., Stanton, S. E., Disis, M. L., 2015. Current Methods of Epitope Identification for Cancer Vaccine Design. Vaccine, 1-7
Davis, I. W., Murray, L. W., Richardson, J. S., Richardson, D. C., 2004. MOLPROBITY: Structure Validation and All-Atom Contact Analysis for Nucleic Acids and Their Complexes. Nucleic Acids Research 32, 615-619
Doytchinova, I. A., Flower, D. R., 2007. VaxiJen: A Server for Prediction of Protective Antigens, Tumour Antigens and Subunit Vaccines. BMC Bioinformatics 8, 4-10
Fiser, A., Do, R. K., Sali, A., 2000. Modeling of Loops in Protein Structures. Protein Science 9, 1753-1773
Fooladi, A. A. I., Hosseini, H. M., Amani, J., 2015. An In Silico Chimeric Vaccine Targeting Breast Cancer Containing Inherent Adjuvant. Iran J Cancer Prevent 8, 1- 8
Heiny, A. T., Miotto, O., Srinivasan, K. N., Khan, A. M., Zhang, G. L., Brusic, V., Tan, T. W., August, T., 2007. Evolutionarily Conserved Protein Sequences of Influenza A Viruses, Avian and Human, as Vaccine Targets. PLoS ONE 2, 1-14
Heo, L., Par, H., Seok, C., 2013. GalaxyRefine: Protein Structure Refinement Driven by Side-Chain Repacking. Nucleic Acids Research 41, 384-388
John, B., Sali, A., 2003. Comparative Protein Structure Modeling by Iterative Alignment, Model Building and Model Assessment. Nucleic Acids Research 31, 3982-3992
Kandasamy, S., Hassan, S., Gopalaswamya, R., Narayanana, S., 2014. Homology Modelling, Docking, Pharmacophore and Site Directed mutagenesis Analysis to Identify The Critical Amino Acid Residue of PknI from Mycobacterium Tuberculosis. Journal of Molecular Graphics and Modelling 52, 11-19
Khan, A. M., Miotto, O., Heiny, A.T., Salmon, J., Srinivasan, K.N., dan Eduardo, 2006. A Systematic Bioinformatics Approach for Selection of Epitope Based Vaccine Targets. Cell Immunol 244, 141-147
Khan, A. M., Miotto, O., Nascimento, E. J. M., Srinivasan, K. N., Heiny, A. T., Zhang, G. L., Marques E. T., Tan, T. W., Brusic, V., Salmon, J., dan August, T., 2008. Conservation and Variability of Dengue Virus Proteins: Implications for Vaccine Design. PLoS Negl Trop Dis 2, 1-15
Khoury, G. A., Smadbeck, J., Kieslich, C. A., dan Floudas, C. A., 2014. Protein folding and de novo protein design for biotechnological applications. Trends in Biotechnology 32, 99-109
Ko, J., Park, H., Heo, L., Seok C., 2012a. GalaxyWEB Server for Protein Structure Prediction and Refinement. Nucleic Acids Research 40, 294-297
Ko, J., Park, H., Seok, C., 2012b. GalaxyTBM: Template-Based Modeling by Building A Reliable Core and Refining Unreliable Local Regions. BMC Bioinformatics 13, 198-205
Komite Nasional Penanggulangan Kanker. 2015. Panduan Nasional Penanganan Tumor Otak. Kementerian Kesehatan Republik Indonesia. Jakarta. Halm 1-5
Krieger, E., Nabuurs, S. B., dan Vriend, G., 2003. Homology modeling. Wiley-Liss Inc., 507-521
Krogh, A., Larsson, B., Heijne G., Sonhammer, E.L.L., 2001. Predicting Transmembrane Protein Topology with A Hidden Markov Model: Application to Complete Genomes. J.Mol.Biol 305, 567-580
Labussiere, M., Sanson, M., Idbaih, A., Delattre, J. Y., 2010. IDH1 Gene Mutations: A New Paradigm in Glioma, Prognosis and Therapy?. The Oncologist 15, 196-199
Lee, G. R., Heo, L., Seok, C., 2015. Effective Protein Model Structure Refinement by Loop Modeling and Overall Relaxation. Proteins, 1-9
Lindorff-Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J. L., Dror, R. O., Shaw, D. E., 2010. Improved Side-Chain Torsion Potentials for The Amber ff99SB Protein Force Field. Proteins 78, 1950–1958
Melo, F., Sanchez, R., Sali, A., 2002. Statistical Potentials for Fold Assessment. Protein Science 11, 430-448
Nielsen, M., Lundegaard, C., Lund, O., 2007. Prediction of MHC Class II Binding Affinity Using SMM-Align, A Novel Stabilization Matrix Alignment Method. BMC Bioinformatics 8, 238-249
Nugent, T., Jones, D. T., 2009. Transmembrane Protein Topology Prediction Using Support Vector Machines. BMC Bioinformatics 10, 159-169
Pitman, M. R. dan Menz R. I., 2006. Methods for protein homology modelling. Applied Mycology and Biotechnology 6, 37-59
Roy, A., Kucukural, A., Zhang, Y., 2010. I-TASSER: A unified platform for automated protein structure and function prediction. Nature Protocols 5, 725-738
Sali, A. dan Blundell, T.L., 1993. Comparative protein modelling by satisfaction of spatial restraints. JMB 234, 779-815
Schumacher, T., Bunse, L., Pusch, S., Sahm, F., Wiestler, B., Quandt, J., Menn, O., Osswald, M., Oezen, I., Ott, M., Keil, M., BalíŸ, J., Rauschenbach, K., Grabowska, A. K., Vogler, I., Diekmann, J., Trautwein, N., Eichmuller, S. B., Okun, J., Stevanovic, S., Riemer, A. B., Sahin, U., Friese, M. A., Beckhove, P., Deimling, A., Wick, W., dan Platten, M., 2014. Avaccine targeting mutant IDH1 induces antitumour immunity. Nature, 1-17
Schumacher, T., Bunse, L., Wick W., dan Platten, M., 2014. Mutant IDH1: An immunotherapeutic target in tumors. OncoImmunology 3, 1-2
Shen, M. dan Sali, A., 2006. Statistical potential for assessment and prediction of protein structures. Protein Sci 15, 2507-2524
Summa, C. M. and Levitt, M., 2006. Near-native structure refinement using in vacuo energy minimization. PNAS 104, 3177–3182
Tambunan, U. S. F., Parikesit, A. A., Hendra, Taufik, R. I., Amelia, F., dan Syamsudin, 2009. In Silico Analysis of Envelope Dengue Virus-2 and Envelope Dengue Virus-3 Protein as the Backbone of Dengue Virus Tetravalent Vaccine by Using Homology Modeling Method. OnLine Journal of Biological Sciences 9, 6-16
Tambunan, U. S. F., Parikesit, A. A., Tochary, T. A., dan Sugiono, D., 2007. Computational Study of Post Translation Modification in Chimeric Virus Like Particles Vaccine of Human Papilloma Virus with Virion Capsid L1. Makara Seri Sains 11, 56-62
Tambunan, U. S. F., Sipahutar, F. R. P., Parikesit, A. A., dan Kerami, D., 2016. Vaccine Design for H5N1 Based on B- and T-cell Epitope Predictions. Bioinformatics and Biology Insights 10, 27-35
Turcan, S., Rohle, D., Goenka, A., Walsh, L. A., Fang, F., Yilmaz, E., Campos, C., Fabius, A. W. M., Lu, C., Ward, P. S., Thompson, C. B. Kaufman, A., Guryanova, O., Levine, R., Heguy, A., Viale, A., Morris L. G. T., Huse, J. T., Mellinghoff, I. K., dan Chan, T. A., 2012. IDH1 mutation is sufficient to establish the glioma hypermethylator phenotype. Nature 483, 479-483
Wang, P., Sidney, J., Dow, C., Mothe, B., Sette, A., dan Peter, S. B., 2008. A systematic assessment of MHC class II peptide binding predictions and evaluation of aconsensus approach. PLoS Comput Biol 4, 1-10
Wang, P., Sidney, J., Kim, Y., Sette, A., Lund, O., dan Nielsen, M., Peters, B., 2010. Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinformatics 11, 568-579
Wiederstein, M. dan 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
Yang, B., Zhong, C., Peng, Y., Lai, Z., dan Ding, J., 2010. Molecular mechanisms of "off-on switch” of activities of human IDH1 by tumor-associated mutation R132H. Cell Research 20, 1188-1200
Yang, J., Yan, R., Roy, A., Xu, D., Poisson, J., dan Zhang, Y., 2015. The I-TASSER suite: Protein structure and function prediction. Nature Methods 12, 7-18
Zahroh, H., Ma'rup, A., Tambunan, U. S. F., dan Parikesit, A. A., 2016. Immunoinformatics Approach in Designing Epitope-based Vaccine Against Meningitis-inducing Bacteria (Streptococcus pneumoniae, Neisseria meningitidis, and Haemophilus influenzae Type b). Drug Target Insights 10, 19-29
Zhang, Y., 2008. I-TASSER server for protein 3D structure prediction. BMC Bioinformatics 9, 40-47
Authors
Yeni, Y. and Tjahjono, D. H. (2017) “HOMOLOGY MODELING EPITOP ISOCITRATE DEHYDROGENASE TIPE 1 (R132H) MENGGUNAKAN MODELLER, I-TASSER DAN (PS)2 UNTUK VAKSIN GLIOMA”, Farmasains : Jurnal Ilmiah Ilmu Kefarmasian, 4(1), pp. 21–32. doi: 10.22236/farmasains.v4i1.189.
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