The Binding Prediction Model of The Iron-responsive Element Binding Protein and Iron-responsive Elements


Arli Aditya Parikesit
Kevin Nathanael Ramanto


Iron is essential to fulfilling an indispensable role in the biological process in human physiology. Various proteins were known involved in iron metabolism. One of the proteins called iron-responsive element binding protein (IRP)which acts as master iron of cellular iron homeostasis. There are two IRP known to date, which is: IRP1 and IRP2. Previous studies showed IRP bind to iron-responsive elements (IRE) located in 5’-UTR of the transferrin receptor 1. The interaction of IRP/IRE is well studied through many years to find a better treatment for the cellular disorder in iron metabolism. However, the structural differences of both IRP and the binding prediction model of IRP/IRE remain unclear. This study provides a better understanding of the IRP structure and the IRP/IRE2 binding prediction model in a healthy condition. Several bioinformatic analyses were implemented in this study, such as molecular docking simulation, domain prediction, and structural similarity analysis. Structural analysis of IRP demonstrates a low root mean square deviation score that indicates both of IRP have high similarity in structure with different characteristics, such as binding site, and metabolic pathway.  Interestingly, molecular docking simulation showed IRP has a preferably binding site when targeting specific IRE. Thus, this information could be beneficial in developing a drug for an iron-related disease.


How to Cite
Parikesit, A. A. and Ramanto, K. N. (2020) “The Binding Prediction Model of The Iron-responsive Element Binding Protein and Iron-responsive Elements”, Bioinformatics and Biomedical Research Journal, 2(1), pp. 12–20. Available at: (Accessed: 11December2023).


  1. Crielaard, B. J., Lammers, T. & Rivella, S. (2017). Targeting iron metabolism in drug discovery and delivery. Nature Reviews Drug Discovery,16 (6):400-423.
  2. Thomson, A. M., Rogers, J. T. & Leedman, P. J. (1999). Iron-regulatory proteins, iron-responsive elements, and ferritin mRNA translation. The International Journal of Biochemistry & Cell Biology,31 (10):1139-1152.
  3. Leamon, C. P. & Low, P. S. (2005). Receptor-Mediated Drug Delivery. Drug Delivery,167-187.
  4. Khan, M. A., Ma, J., Walden, W. E., Merrick, W. C., Theil, E. C & Goss, D. J. (2014). Rapid kinetics of iron-responsive element
  5. (IRE) RNA/iron regulatory protein 1 and IRE-RNA/eIF4F complexes respond differently to metal ions. Nucleic Acids Research,42 (10), 6567-6577.
  6. Haile, D. J., Hentze, M. W., Rouault, T. A., Harford, J. B. & Klausner, R. D. (1989). Regulation of the interac-tion of the iron-responsive element binding protein with iron-responsive RNA elements. Molecular and Cellular Biology,9 (11), 5055-5061.
  7. Khan, M. A., Walden, W. E., Theil, E. C. & Goss, D. J. (2017). Thermodynamic and Kinetic Analyses of Iron Response Element (IRE)-mRNA Binding to Iron Regu-latory Protein, IRP1. Scientific Reports,7 (1).
  8. Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N. & Sternberg, M. J. E. (2015). The Phyre2 web portal for protein modeling, prediction, and analysis. Nature Pro-tocols, 10:845.
  9. Campillos, M., Cases, I., Hentze, M. W. & Sanchez, M. (2010). SIREs: Searching for iron-responsive ele-ments. Nucleic Acids Research,38 (Web Server).
  10. Lorenz, R., Bernhart, S. H., Siederdissen, C. H., Tafer, H., Flamm, C., Stadler, P. F. & Hofacker, I. L. (2011). ViennaRNA Package 2.0. Algorithms for Molecular Bi-ology,6 (1).
  11. Boniecki, M. J., Lach, G., Dawson, W. K., Tomala, K., Lukasz, P., Soltysinski, T., … Bujnicki, J. M. (2015). SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction. Nucleic Acids Research, 44 (7).
  12. Apweiler, R. (2001). The InterPro database, an integrat-ed documentation resource for protein families, do-mains, and functional sites. Nucleic Acids Research,29 (1):37-40.
  13. Pejaver, V., Hsu, W-L., Xin, F., Dunker, A. K., Uversky, V. N., & Radivojac, P. The structural and functional signatures of proteins that undergo multiple events of post-translational modification Protein Sci-ence. 23(8):1077-1093.
  14. Gelly, J., Joseph, A. P., Srinivasan, N. & Brevern, A. G. (2011). IPBA: A tool for protein structure comparison using sequence alignment strategies. Nucleic Acids Re-search, 39 (Suppl_2).
  15. Yan, J. & Kurgan, L. (2017). DRNApred, fast se-quence-based method that accurately predicts and dis-criminates DNA- and RNA-binding residues. Nucleic Acids Research.
  16. Szklarczyk, D., Morris, J. H., Cook, H., Kuhn, M., Wy-der, S., Simonovic, M., . . . Von Mering, C. (2016). The STRING database in 2017: Quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Research,45 (D1).
  17. Schneidman-Duhovny, D., Inbar, Y., Nussinov, R. & Wolfson, H. J. (2005). PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Research, 33 (Web Server).
  18. Huang, S.-Y. (2014). Search strategies and evaluation in protein–protein docking: principles, advances and chal-lenges. Drug Discovery Today, 19 (8), 1081–1096.
  19. Laskowski, R. A., Jabłońska, J., Pravda, L., Vařeková, R. S. & Thornton, J. M. (2017). PDBsum: Structural summaries of PDB entries. Protein Science, 27 (1), 129–134.
  20. Pérez-Cano, L., Jiménez-García, B. & Fernández-Recio, J. (2012). A protein-RNA docking benchmark (II): Ex-tended set from experimental and homology modeling data. Proteins: Structure, Function, and Bioinformatics.
  21. Nithin, C., Mukherjee, S. & Bahadur, R. P. (2016). A non-redundant protein-RNA docking benchmark ver-sion 2.0. Proteins: Structure, Function, and Bioinformat-ics, 85 (2), 256–267.
  22. Huang, S. Y.& Zou, X. (2012). A nonredundant struc-ture dataset for benchmarking protein-RNA computa-tional docking. Journal of Computational Chemistry, 3 (4), 311–318.
  23. Henderson, B. R. (1966). Iron Regulatory Proteins 1 and 2. Bio Essays, 18 (8), 739–749.
  24. Casey, J. L., M. W. Hentze, D. M. Koelier, S. W. Caughman, T. A. Rouault, R. D. Klausner, & J. B. Harford. 1988. Iron-responsive elements: regulatory RNA sequences that control mRNA levels and translation. Science 240:924-928.
  25. Lushchak, O. V., Piroddi, M., Galli, F. & Lushchak, V. I. (2013). Aconitase post-translational modification as a key in linkage between Krebs cycle, iron homeostasis, redox signal-ing, and metabolism of reactive oxygen species. Redox Re-port, 19 (1), 8–15.
  26. Gruer, M. J., Artymiuk, P. J. & Guest, J. R. (1997). The aco-nitase family: Three structural variations on a common theme. Trends in Biochemical Sciences,22 (1):3-6.
  27. Audagnotto, M. & Peraro, M. D. (2017). Protein post-translational modifications: In silico prediction tools and mo-lecular modeling. Computational and Structural Biotechnolo-gy Journal, 15, 307–319.
  28. Piccinelli, P. & Samuelsson, T. (2007). Evolution of the iron-responsive element. Rna, 13 (7), 952–966.
  29. Ramanto, Kevin Nathanael; Parikesit, Arli Ad-itya (2020), “The Binding Prediction Model of The Iron-responsive Element Binding Protein and Iron-responsive El-ements”, Mendeley Data, v1.
  30. Kim, H., Jeong, E., Lee, S.-W. & Han, K. (2003). Computa-tional analysis of hydrogen bonds in protein-RNA complexes for interaction patterns. FEBS Letters, 552 (2-3), 231–239.
  31. Recalcati, S., Minotti, G. & Cairo, G. (2010). Iron Regulatory Proteins: From Molecular Mechanisms to Drug Develop-ment. Antioxidants & Redox Signaling, 13 (10), 1593–1616. doi: 10.1089/ars.2009.2983.
  32. Zhou, Z. D. & Tan, E. (2017). Iron regulatory protein (IRP)-iron responsive element (IRE) signaling pathway in human neurodegenerative diseases. Molecular Neurodegeneration,12 (1).
  33. Canzoneri, J. C. & Oyelere, A. K. (2008). Interaction of anthracyclines with iron responsive element mRNAs. Nucleic Acids Research, 36(21), 6825–6834. doi: 10.1093/nar/gkn774