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Cited by 3Protein Structure and DynamicsMetalloenzymes and iron-sulfur proteinsEnzyme Structure and Function

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The N-terminal order-disorder transition is a critical determinant for a metamorphosis of IscU

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Na, Jongbum, Heo, Joongyu, Jeong, Minchan, Kim, Beom Soo, Ji, Sangho, Ko, Young Ho, Shafiei, Alaleh, Baldir, Nilufer, DeMirci, Hasan, Yu, Wookyung, Kim, Jin Hae·2025·International Journal of Biological Macromolecules
DOI 10.1016/j.ijbiomac.2025.146969

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Abstract

IscU, a key scaffold protein mediating the biogenesis of iron‑sulfur (FeS) clusters, exhibits metamorphic characteristics crucial for its versatile and efficient function. Previous studies have demonstrated that IscU has two interconverting conformations: the structured state (S-state) and the disordered state (D-state), each contributing to its distinct functionality and interaction network. Despite its physiological importance, the precise mechanism underpinning the maintenance of IscU's unique structural heterogeneity has remained elusive. In this study, we used computational, spectroscopic, and biochemical approaches to reveal that the N-terminal order-disorder plays a critical role in the metamorphic modulation of Escherichia coli IscU. With computational analysis, we found that the N-terminal region displays greater structural plasticity, which is linked to other regions of IscU through coevolutionary relationships. We also used site-directed mutagenesis, size-exclusion chromatography, circular dichroism, isothermal titration calorimetry, and nuclear magnetic resonance spectroscopic techniques to demonstrate that the degree of orderliness in the N-terminal region correlates positively with the stabilization of IscU's S-state and negatively with its affinity for HscA. Finally, we also showed that the peptide mimicking the N-terminal motif can modulate IscU's metamorphic properties. Our data indicate that the flexibility in the N-terminal region is finely tuned to optimize IscU's physiological efficiency and efficacy. Moreover, our study showcases important evidence suggesting a novel therapeutic potential of the N-terminus-like peptide for related pathogenic processes.

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Research works printed but not linked: 59

  1. Hirling, 1994, Mutational analysis of the [4Fe-4S]-cluster converting iron regulatory factor from its RNA-binding form to cytoplasmic aconitase, EMBO J., 13, 453, 10.1002/j.1460-2075.1994.tb06280.x · DOI
  2. Ren, 2023, The Fe-S cluster assembly protein IscU2 increases alpha-ketoglutarate catabolism and DNA 5mC to promote tumor growth, Cell Discov., 9, 76, 10.1038/s41421-023-00558-8 · DOI
  3. Lill, 2009, Function and biogenesis of iron–sulfur proteins, Nature, 460, 831, 10.1038/nature08301 · DOI · Paper page
  4. Braymer, 2021, Mechanistic concepts of iron-sulfur protein biogenesis in biology, Biochim. Biophys. Acta, Mol. Cell Res., 1868, 10.1016/j.bbamcr.2020.118863 · DOI
  5. Kim, 2012, Three-dimensional structure and determinants of stability of the iron-sulfur cluster scaffold protein IscU from Escherichia coli, Biochemistry, 51, 5557, 10.1021/bi300579p · DOI
  6. Hoff, 2000, Interaction of the iron-sulfur cluster assembly protein IscU with the Hsc66/Hsc20 molecular chaperone system of Escherichia coli, Proc. Natl. Acad. Sci. U. S. A., 97, 7790, 10.1073/pnas.130201997 · DOI
  7. Ramelot, 2004, Solution NMR structure of the iron-sulfur cluster assembly protein U (IscU) with zinc bound at the active site, J. Mol. Biol., 344, 567, 10.1016/j.jmb.2004.08.038 · DOI
  8. Shi, 2010, Structural basis for Fe–S cluster assembly and tRNA thiolation mediated by IscS protein–protein interactions, PLoS Biol., 8, 10.1371/journal.pbio.1000354 · DOI
  9. Kunichika, 2021, The structure of the dimeric state of IscU harboring two adjacent [2Fe-2S] clusters provides mechanistic insights into cluster conversion to [4Fe-4S], Biochemistry, 60, 1569, 10.1021/acs.biochem.1c00112 · DOI
  10. Marinoni, 2012, (IscS-IscU)₂ complex structures provide insights into Fe₂S₂ biogenesis and transfer, Angew. Chem. Int. Ed., 51, 5439, 10.1002/anie.201201708 · DOI
  11. Boniecki, 2017, Structure and functional dynamics of the mitochondrial Fe/S cluster synthesis complex, Nat. Commun., 8, 1287, 10.1038/s41467-017-01497-1 · DOI
  12. Tanaka, 2019, Identification of IscU residues critical for de novo iron-sulfur cluster assembly, Mol. Microbiol., 112, 1769, 10.1111/mmi.14392 · DOI
  13. Freibert, 2021, N-terminal tyrosine of ISCU2 triggers [2Fe-2S] cluster synthesis by ISCU2 dimerization, Nat. Commun., 12, 6902, 10.1038/s41467-021-27122-w · DOI
  14. The UniProt Consortium, 2023, UniProt: the universal protein knowledgebase in 2023, Nucleic Acids Res., 51, D523, 10.1093/nar/gkac1052 · DOI · Paper page
  15. Sievers, 2018, Clustal omega for making accurate alignments of many protein sequences, Protein Sci., 27, 135, 10.1002/pro.3290 · DOI · Paper page
  16. Walsh, 2012, ESpritz: accurate and fast prediction of protein disorder, Bioinformatics, 28, 503, 10.1093/bioinformatics/btr682 · DOI
  17. Ishida, 2007, PrDOS: prediction of disordered protein regions from amino acid sequence, Nucleic Acids Res., 35, W460, 10.1093/nar/gkm363 · DOI
  18. Sievers, 2011, Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal omega, Mol. Syst. Biol., 7, 539, 10.1038/msb.2011.75 · DOI
  19. Halabi, 2009, Protein sectors: evolutionary units of three-dimensional structure, Cell, 138, 774, 10.1016/j.cell.2009.07.038 · DOI
  20. Lockless, 1999, Evolutionarily conserved pathways of energetic connectivity in protein families, Science, 286, 295, 10.1126/science.286.5438.295 · DOI
  21. Teşileanu, 2015, Protein sectors: statistical coupling analysis versus conservation, PLoS Comput. Biol., 11, 10.1371/journal.pcbi.1004091 · DOI
  22. Pedregosa, 2011, Scikit-learn: machine learning in Python, J. Mach. Learn. Res., 12, 2825
  23. Meng, 2023, Tools for structure building and analysis, Protein Sci., 32, 10.1002/pro.4792 · DOI
  24. Harris, 2020, Array programming with NumPy, Nature, 585, 357, 10.1038/s41586-020-2649-2 · DOI · Paper page
  25. McKinney, 2010, Data structures for statistical computing in Python, Proc. Python Sci. Conf., 92, 56, 10.25080/Majora-92bf1922-00a · DOI
  26. Cock, 2009, Biopython: freely available Python tools for computational molecular biology and bioinformatics, Bioinformatics, 25, 1422, 10.1093/bioinformatics/btp163 · DOI · Paper page
  27. Hunter, 2007, Matplotlib: a 2D graphics environment, Comput. Sci. Eng., 9, 90, 10.1109/MCSE.2007.55 · DOI · Paper page
  28. Waskom, 2021, Seaborn: statistical data visualization, J. Open Source Softw., 6, 10.21105/joss.03021 · DOI · Paper page
  29. Case, 2023, AmberTools, J. Chem. Inf. Model., 63, 6183, 10.1021/acs.jcim.3c01153 · DOI
  30. Tian, 2020, ff19SB: amino-acid-specific protein backbone parameters trained against quantum mechanics energy surfaces in solution, J. Chem. Theory Comput., 16, 528, 10.1021/acs.jctc.9b00591 · DOI
  31. Jorgensen, 1983, Comparison of simple potential functions for simulating liquid water, J. Chem. Phys., 79, 926, 10.1063/1.445869 · DOI
  32. Ciccotti, 1986, Molecular-dynamics simulation of rigid molecules, Comput. Phys. Rep., 4, 345, 10.1016/0167-7977(86)90022-5 · DOI
  33. Darden, 1993, Particle mesh Ewald: an n.log(N) method for Ewald sums in large systems, J. Chem. Phys., 98, 10089, 10.1063/1.464397 · DOI
  34. Davidchack, 2009, Langevin thermostat for rigid body dynamics, J. Chem. Phys., 130, 10.1063/1.3149788 · DOI
  35. van der Maaten, 2008, Visualizing data using t-SNE, J. Mach. Learn. Res., 9, 2579
  36. 2010, M9 minimal medium (standard), Cold Spring Harb. Protoc., 2010
  37. Kim, 2012, Specialized Hsp70 chaperone (HscA) binds preferentially to the disordered form, whereas J-protein (HscB) binds preferentially to the structured form of the iron-sulfur cluster scaffold protein (IscU), J. Biol. Chem., 287, 31406, 10.1074/jbc.M112.352617 · DOI
  38. Bai, 2019, Isothermal analysis of ThermoFluor data can readily provide quantitative binding affinities, Sci. Rep., 9, 2650, 10.1038/s41598-018-37072-x · DOI
  39. Micsonai, 2015, Accurate secondary structure prediction and fold recognition for circular dichroism spectroscopy, Proc. Natl. Acad. Sci. U. S. A., 112, E3095, 10.1073/pnas.1500851112 · DOI
  40. Lee, 2021, POKY: a software suite for multidimensional NMR and 3D structure calculation of biomolecules, Bioinformatics, 37, 3041, 10.1093/bioinformatics/btab180 · DOI
  41. Wishart, 1995, 1H, 13C, and 15N random coil NMR chemical shifts of the common amino acids. I. Investigations of nearest-neighbor effects, J. Biomol. NMR, 5, 67, 10.1007/BF00227471 · DOI
  42. Wang, 2006, Probabilistic approach to determining unbiased random-coil carbon-13 chemical shift values from the protein chemical shift database, J. Biomol. NMR, 35, 155, 10.1007/s10858-006-9022-0 · DOI
  43. Shen, 2015, Protein structural information derived from NMR chemical shift with the neural network program TALOS-N, Methods Mol. Biol., 1260, 17, 10.1007/978-1-4939-2239-0_2 · DOI
  44. Hermanson, 2013, Chapter 3 – the reactions of bioconjugation, Methods Mol. Biol.
  45. Yang, 2017, Chemical recognition of active oxygen species on the surface of oxygen evolution reaction electrocatalysts, Angew. Chem. Int. Ed., 56, 8652, 10.1002/anie.201701984 · DOI
  46. Cotts, 1989, Pulsed field gradient stimulated echo methods for improved NMR diffusion measurements in heterogeneous systems, J. Magn. Reson., 83, 252
  47. Janowska, 2016, Intermolecular paramagnetic relaxation enhancement (PRE) studies of transient complexes in intrinsically disordered proteins, Methods Mol. Biol., 1345, 45, 10.1007/978-1-4939-2978-8_3 · DOI
  48. Battiste, 2000, Utilization of site-directed spin labeling and high-resolution heteronuclear nuclear magnetic resonance for global fold determination of large proteins with limited nuclear Overhauser effect data, Biochemistry, 39, 5355, 10.1021/bi000060h · DOI
  49. Chandramouli, 2006, HscA and HscB stimulate [2Fe-2S] cluster transfer from IscU to apoferredoxin in an ATP-dependent reaction, Biochemistry, 45, 11087, 10.1021/bi061237w · DOI
  50. Hoff, 2003, Contributions of the LPPVK motif of the iron-sulfur template protein IscU to interactions with the Hsc66-Hsc20 chaperone system, J. Biol. Chem., 278, 37582, 10.1074/jbc.M305292200 · DOI
  51. Kim, 2014, Role of IscX in iron–sulfur cluster biogenesis in Escherichia coli, J. Am. Chem. Soc., 136, 7933, 10.1021/ja501260h · DOI
  52. Kim, 2012, Disordered form of the scaffold protein IscU is the substrate for iron-sulfur cluster assembly on cysteine desulfurase, Proc. Natl. Acad. Sci. U. S. A., 109, 454, 10.1073/pnas.1114372109 · DOI
  53. Cubuk, 2024, The disordered N-terminal tail of SARS-CoV-2 nucleocapsid protein forms a dynamic complex with RNA, Nucleic Acids Res., 52, 2609, 10.1093/nar/gkad1215 · DOI
  54. Murthy, 2021, Molecular interactions contributing to FUS SYGQ LC-RGG phase separation and co-partitioning with RNA polymerase II heptads, Nat. Struct. Mol. Biol., 28, 923, 10.1038/s41594-021-00677-4 · DOI
  55. Kim, 2009, Structure and dynamics of the iron−sulfur cluster assembly scaffold protein IscU and its interaction with the cochaperone HscB, Biochemistry, 48, 6062, 10.1021/bi9002277 · DOI
  56. Cai, 2018, ISCU(M108I) and ISCU(D39V) differ from wild-type ISCU in their failure to form cysteine desulfurase complexes containing both frataxin and ferredoxin, Biochemistry, 57, 1491, 10.1021/acs.biochem.7b01234 · DOI
  57. Saha, 2014, The presence of multiple cellular defects associated with a novel G50E iron-sulfur cluster scaffold protein (IscU) mutation leads to development of mitochondrial myopathy, J. Biol. Chem., 289, 10359, 10.1074/jbc.M113.526665 · DOI
  58. Xiao, 2025, Advance in peptide-based drug development: delivery platforms, therapeutics and vaccines, Signal Transduct. Target. Ther., 10, 74, 10.1038/s41392-024-02107-5 · DOI · Paper page
  59. Wang, 2022, Therapeutic peptides: current applications and future directions, Signal Transduct. Target. Ther., 7, 48, 10.1038/s41392-022-00904-4 · DOI · Paper page

Metadata

Authors
Na, J., Heo, J., Jeong, M., Kim, B. S., Ji, S., Ko, Y. H., Shafiei, A., Baldir, N., DeMirci, H., Yu, W., & Kim, J. H.
Affiliations
  • Daegu Gyeongbuk Institute of Science and Technology (KR)
  • Institute for Basic Science (KR)
  • Koç University (TR)
Corresponding author
  • Yu, Wookyung
  • Kim, Jin Hae
ORCID
Venue
International Journal of Biological Macromolecules
Publisher
Elsevier BV
Published
2025-09
Volume
323
Issue
Pt 1
Pages
146969
ISSN
0141-8130 (ISSN-L)
DOI
10.1016/j.ijbiomac.2025.146969
OpenAlex
W4413326568
Cited by
3
References
3
Citations by year
2026: 2 · 2025: 1
FWCI
0.91
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Biological Macromolecules (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Institute for Basic Science (IBS-R034-D1)
  • Ministry of Environment (RS-2023-00230402)
  • Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (221N005, NRF-2021K2A9A1A06096295)
  • National Research Foundation of Korea (NRF-2020R1I1A2074335, NRF-2023R1A2C1006248)
  • Korea Basic Science Institute
  • Ministry of Science and ICT, South Korea (RS-2024-00440614)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Metalloenzymes and iron-sulfur proteins
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
Keywords
IscU, iron-sulfur cluster assembly, intrinsically disordered proteins, protein conformational heterogeneity, protein-peptide interactions, Escherichia coli, protein coevolution, structural plasticity
MeSH terms
Escherichia coli, Iron-Sulfur Proteins, Models, Molecular, Protein Conformation, Escherichia coli Proteins

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