nature.com

Extreme disorder in an ultrahigh-affinity protein complex - Nature

  • ️Schuler, Benjamin
  • ️Wed Feb 21 2018

References

  1. Wright, P. E. & Dyson, H. J. Linking folding and binding. Curr. Opin. Struct. Biol. 19, 31–38 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Habchi, J., Tompa, P., Longhi, S. & Uversky, V. N. Introducing protein intrinsic disorder. Chem. Rev. 114, 6561–6588 (2014)

    Article  CAS  PubMed  Google Scholar 

  3. Tompa, P. & Fuxreiter, M. Fuzzy complexes: polymorphism and structural disorder in protein–protein interactions. Trends Biochem. Sci. 33, 2–8 (2008)

    Article  CAS  PubMed  Google Scholar 

  4. Baker, J. M. et al. CFTR regulatory region interacts with NBD1 predominantly via multiple transient helices. Nat. Struct. Mol. Biol. 14, 738–745 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Mittag, T. et al. Dynamic equilibrium engagement of a polyvalent ligand with a single-site receptor. Proc. Natl Acad. Sci. USA 105, 17772–17777 (2008)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  6. Hendus-Altenburger, R. et al. The human Na+/H+ exchanger 1 is a membrane scaffold protein for extracellular signal-regulated kinase 2. BMC Biol. 14, 31 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Milles, S. et al. Plasticity of an ultrafast interaction between nucleoporins and nuclear transport receptors. Cell 163, 734–745 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Csizmok, V., Follis, A. V., Kriwacki, R. W. & Forman-Kay, J. D. Dynamic protein interaction networks and new structural paradigms in signaling. Chem. Rev. 116, 6424–6462 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Banani, S. F., Lee, H. O., Hyman, A. A. & Rosen, M. K. Biomolecular condensates: organizers of cellular biochemistry. Nat. Rev. Mol. Cell Biol. 18, 285–298 (2017)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Robinson, P. J. & Rhodes, D. Structure of the ‘30 nm’ chromatin fibre: a key role for the linker histone. Curr. Opin. Struct. Biol. 16, 336–343 (2006)

    Article  CAS  PubMed  Google Scholar 

  11. Hergeth, S. P. & Schneider, R. The H1 linker histones: multifunctional proteins beyond the nucleosomal core particle. EMBO Rep. 16, 1439–1453 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hansen, J. C., Lu, X., Ross, E. D. & Woody, R. W. Intrinsic protein disorder, amino acid composition, and histone terminal domains. J. Biol. Chem. 281, 1853–1856 (2006)

    Article  CAS  PubMed  Google Scholar 

  13. Gast, K. et al. Prothymosin α: a biologically active protein with random coil conformation. Biochemistry 34, 13211–13218 (1995)

    Article  CAS  PubMed  Google Scholar 

  14. Uversky, V. N. et al. Natively unfolded human prothymosin α adopts partially folded collapsed conformation at acidic pH. Biochemistry 38, 15009–15016 (1999)

    Article  CAS  PubMed  Google Scholar 

  15. Gómez-Márquez, J. & Rodríguez, P. Prothymosin α is a chromatin-remodelling protein in mammalian cells. Biochem. J. 333, 1–3 (1998)

    Article  PubMed  PubMed Central  Google Scholar 

  16. Mosoian, A. Intracellular and extracellular cytokine-like functions of prothymosin α: implications for the development of immunotherapies. Future Med. Chem. 3, 1199–1208 (2011)

    Article  CAS  PubMed  Google Scholar 

  17. George, E. M. & Brown, D. T. Prothymosin α is a component of a linker histone chaperone. FEBS Lett. 584, 2833–2836 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Papamarcaki, T. & Tsolas, O. Prothymosin α binds to histone H1 in vitro. FEBS Lett. 345, 71–75 (1994)

    Article  CAS  PubMed  Google Scholar 

  19. Barbero, J. L., Franco, L., Montero, F. & Morán, F. Structural studies on histones H1. Circular dichroism and difference spectroscopy of the histones H1 and their trypsin-resistant cores from calf thymus and from the fruit fly Ceratitis capitata. Biochemistry 19, 4080–4087 (1980)

    Article  CAS  PubMed  Google Scholar 

  20. Ramakrishnan, V., Finch, J. T., Graziano, V., Lee, P. L. & Sweet, R. M. Crystal structure of globular domain of histone H5 and its implications for nucleosome binding. Nature 362, 219–223 (1993)

    Article  CAS  ADS  PubMed  Google Scholar 

  21. Yi, S., Brickenden, A. & Choy, W. Y. A new protocol for high-yield purification of recombinant human prothymosin α expressed in Escherichia coli for NMR studies. Protein Expr. Purif. 57, 1–8 (2008)

    Article  CAS  PubMed  Google Scholar 

  22. Khan, H. et al. Fuzzy complex formation between the intrinsically disordered prothymosin α and the Kelch domain of Keap1 involved in the oxidative stress response. J. Mol. Biol. 425, 1011–1027 (2013)

    Article  CAS  PubMed  Google Scholar 

  23. Zhou, B. R. et al. Structural insights into the histone H1–nucleosome complex. Proc. Natl Acad. Sci. USA 110, 19390–19395 (2013)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  24. Zarbock, J., Clore, G. M. & Gronenborn, A. M. Nuclear magnetic resonance study of the globular domain of chicken histone H5: resonance assignment and secondary structure. Proc. Natl Acad. Sci. USA 83, 7628–7632 (1986)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  25. Kjaergaard, M., Brander, S. & Poulsen, F. M. Random coil chemical shift for intrinsically disordered proteins: effects of temperature and pH. J. Biomol. NMR 49, 139–149 (2011)

    Article  CAS  PubMed  Google Scholar 

  26. Bae, S. H., Dyson, H. J. & Wright, P. E. Prediction of the rotational tumbling time for proteins with disordered segments. J. Am. Chem. Soc. 131, 6814–6821 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Schuler, B., Soranno, A., Hofmann, H. & Nettels, D. Single-molecule FRET spectroscopy and the polymer physics of unfolded and intrinsically disordered proteins. Annu. Rev. Biophys. 45, 207–231 (2016)

    Article  CAS  PubMed  Google Scholar 

  28. Sisamakis, E., Valeri, A., Kalinin, S., Rothwell, P. J. & Seidel, C. A. M. Accurate single-molecule FRET studies using multiparameter fluorescence detection. Methods Enzymol. 475, 455–514 (2010)

    Article  CAS  PubMed  Google Scholar 

  29. Müller-Späth, S. et al. Charge interactions can dominate the dimensions of intrinsically disordered proteins. Proc. Natl Acad. Sci. USA 107, 14609–14614 (2010)

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  30. Hofmann, H. et al. Polymer scaling laws of unfolded and intrinsically disordered proteins quantified with single-molecule spectroscopy. Proc. Natl Acad. Sci. USA 109, 16155–16160 (2012)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  31. White, A. E., Hieb, A. R. & Luger, K. A quantitative investigation of linker histone interactions with nucleosomes and chromatin. Sci. Rep. 6, 19122 (2016)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  32. Pak, C. W. et al. Sequence determinants of intracellular phase separation by complex coacervation of a disordered protein. Mol. Cell 63, 72–85 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Chung, H. S., Louis, J. M. & Gopich, I. V. Analysis of fluorescence lifetime and energy transfer efficiency in single-molecule photon trajectories of fast-folding proteins. J. Phys. Chem. B 120, 680–699 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Soranno, A. et al. Quantifying internal friction in unfolded and intrinsically disordered proteins with single-molecule spectroscopy. Proc. Natl Acad. Sci. USA 109, 17800–17806 (2012)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  35. Nettels, D., Gopich, I. V., Hoffmann, A. & Schuler, B. Ultrafast dynamics of protein collapse from single-molecule photon statistics. Proc. Natl Acad. Sci. USA 104, 2655–2660 (2007)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  36. Soranno, A. et al. Integrated view of internal friction in unfolded proteins from single-molecule FRET, contact quenching, theory, and simulations. Proc. Natl Acad. Sci. USA 114, E1833–E1839 (2017)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Creigthon, T. E. Proteins: Structures and Molecular Properties 2nd edn (W. H. Freeman and Co., 1993)

  38. Karanicolas, J. & Brooks, C. L. III . The origins of asymmetry in the folding transition states of protein L and protein G. Protein Sci. 11, 2351–2361 (2002)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Shoemaker, B. A., Portman, J. J. & Wolynes, P. G. Speeding molecular recognition by using the folding funnel: the fly-casting mechanism. Proc. Natl Acad. Sci. USA 97, 8868–8873 (2000)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  40. Schreiber, G., Haran, G. & Zhou, H. X. Fundamental aspects of protein–protein association kinetics. Chem. Rev. 109, 839–860 (2009)

    Article  CAS  PubMed  Google Scholar 

  41. Borg, M. et al. Polyelectrostatic interactions of disordered ligands suggest a physical basis for ultrasensitivity. Proc. Natl Acad. Sci. USA 104, 9650–9655 (2007)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  42. Srivastava, S. & Tirrell, M. V. in Advances in Chemical Physics (eds Rice, S. A . & Dinner, A. R. ) Ch. 7, 499–544 (John Wiley & Sons, 2016)

    Google Scholar 

  43. Ahmad, A. et al. Heat shock protein 70 kDa chaperone/DnaJ cochaperone complex employs an unusual dynamic interface. Proc. Natl Acad. Sci. USA 108, 18966–18971 (2011)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  44. Freeman Rosenzweig, E. S. et al. The eukaryotic CO2-concentrating organelle is liquid-like and exhibits dynamic reorganization. Cell 171, 148–162.e119 (2017)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Nott, T. J. et al. Phase transition of a disordered nuage protein generates environmentally responsive membraneless organelles. Mol. Cell 57, 936–947 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Peng, B. & Muthukumar, M. Modeling competitive substitution in a polyelectrolyte complex. J. Chem. Phys. 143, 243133 (2015)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  47. Berlow, R. B., Dyson, H. J. & Wright, P. E. Hypersensitive termination of the hypoxic response by a disordered protein switch. Nature 543, 447–451 (2017)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  48. Wang, D. et al. Acetylation-regulated interaction between p53 and SET reveals a widespread regulatory mode. Nature 538, 118–122 (2016)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  49. Dosztányi, Z., Csizmok, V., Tompa, P. & Simon, I. IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics 21, 3433–3434 (2005)

    Article  CAS  PubMed  Google Scholar 

  50. Record, M. T. Jr, Anderson, C. F. & Lohman, T. M. Thermodynamic analysis of ion effects on the binding and conformational equilibria of proteins and nucleic acids: the roles of ion association or release, screening, and ion effects on water activity. Q. Rev. Biophys. 11, 103–178 (1978)

    Article  CAS  PubMed  Google Scholar 

  51. Scott, K. A., Steward, A., Fowler, S. B. & Clarke, J. Titin: a multidomain protein that behaves as the sum of its parts. J. Mol. Biol. 315, 819–829 (2002)

    Article  CAS  PubMed  Google Scholar 

  52. Delaglio, F. et al. NMRPipe: a multidimensional spectral processing system based on UNIX pipes. J. Biomol. NMR 6, 277–293 (1995)

    Article  CAS  PubMed  Google Scholar 

  53. Vranken, W. F. et al. The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins 59, 687–696 (2005)

    Article  CAS  PubMed  Google Scholar 

  54. Orekhov, V. Y. & Jaravine, V. A. Analysis of non-uniformly sampled spectra with multi-dimensional decomposition. Prog. Nucl. Magn. Reson. Spectrosc. 59, 271–292 (2011)

    Article  CAS  PubMed  Google Scholar 

  55. Fedyukina, D. V. et al. Contribution of long-range interactions to the secondary structure of an unfolded globin. Biophys. J. 99, L37–L39 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Gibbs, S. J. & Johnson, C. S. Jr. A PFG NMR experiment for accurate diffusion and flow studies in the presence of eddy currents. J. Magn. Reson. 93, 395–402 (1991)

    ADS  Google Scholar 

  57. Farrow, N. A. et al. Backbone dynamics of a free and phosphopeptide-complexed Src homology 2 domain studied by 15N NMR relaxation. Biochemistry 33, 5984–6003 (1994)

    Article  CAS  PubMed  Google Scholar 

  58. Benke, S. et al. The assembly dynamics of the cytolytic pore toxin ClyA. Nat. Commun. 6, 6198 (2015)

    Article  CAS  ADS  PubMed  Google Scholar 

  59. Müller, B. K., Zaychikov, E., Bräuchle, C. & Lamb, D. C. Pulsed interleaved excitation. Biophys. J. 89, 3508–3522 (2005)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Rasnik, I., McKinney, S. A. & Ha, T. Nonblinking and long-lasting single-molecule fluorescence imaging. Nat. Methods 3, 891–893 (2006)

    Article  CAS  PubMed  Google Scholar 

  61. Schuler, B. Application of single molecule Förster resonance energy transfer to protein folding. Methods Mol. Biol. 350, 115–138 (2007)

    CAS  PubMed  Google Scholar 

  62. Kellner, R. et al. Single-molecule spectroscopy reveals chaperone-mediated expansion of substrate protein. Proc. Natl Acad. Sci. USA 111, 13355–13360 (2014)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  63. Förster, T. Zwischenmolekulare Energiewanderung und Fluoreszenz. Ann. Phys. 437, 55–75 (1948)

    Article  MATH  Google Scholar 

  64. Gopich, I. V., Nettels, D., Schuler, B. & Szabo, A. Protein dynamics from single-molecule fluorescence intensity correlation functions. J. Chem. Phys. 131, 095102 (2009)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  65. Borgia, A. et al. Consistent view of polypeptide chain expansion in chemical denaturants from multiple experimental methods. J. Am. Chem. Soc. 138, 11714–11726 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Dertinger, T. et al. Two-focus fluorescence correlation spectroscopy: a new tool for accurate and absolute diffusion measurements. ChemPhysChem 8, 433–443 (2007)

    Article  CAS  PubMed  Google Scholar 

  67. Kim, Y. C. & Hummer, G. Coarse-grained models for simulations of multiprotein complexes: application to ubiquitin binding. J. Mol. Biol. 375, 1416–1433 (2008)

    Article  CAS  PubMed  Google Scholar 

  68. Kumar, S., Bouzida, D., Swendsen, R. H., Kollman, P. A. & Rosenberg, J. M. The weighted histogram analysis method for free-energy calculations on biomolecules. I. The method. J. Comput. Chem. 13, 1011–1021 (1992)

    Article  CAS  Google Scholar 

  69. Rodriguez, A. & Laio, A. Machine learning. Clustering by fast search and find of density peaks. Science 344, 1492–1496 (2014)

    CAS  PubMed  Google Scholar 

  70. Flyvbjerg, H. & Petersen, H. G. Error estimates on averages of correlated data. J. Chem. Phys. 91, 461–466 (1989)

    Article  CAS  ADS  MathSciNet  Google Scholar 

  71. Kapanidis, A. N. et al. Alternating-laser excitation of single molecules. Acc. Chem. Res. 38, 523–533 (2005)

    Article  CAS  PubMed  Google Scholar 

  72. Hoffmann, A. et al. Mapping protein collapse with single-molecule fluorescence and kinetic synchrotron radiation circular dichroism spectroscopy. Proc. Natl Acad. Sci. USA 104, 105–110 (2007)

    Article  CAS  ADS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank S. A. Sjørup and J. H. Martinsen for purification assistance, I. König for a sample of wild-type ProTα, A. Prestel and M. B. Kunze for NMR advice, E. Holmstrom for help with data analysis, D. Mercadante for assistance with electrostatics calculations, R. Sobrino for help with experiments in the early stages of the project, J. Forman-Kay, M. Blackledge, R. Pappu and A. Holehouse for discussions and the Functional Genomics Center Zurich for performing mass spectrometry. This work was supported by the Swiss National Science Foundation (B.S.), the Danish Council for Independent Research (# 4181-00344, B.B.K.), the Novo Nordisk Foundation (B.B.K. and P.O.H.), the Carlsberg Foundation (P.O.H.), and the Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health (R.B.B.). This work used the computational resources of the NIH HPC Biowulf cluster (http://hpc.nih.gov).

Author information

Author notes

  1. Alessandro Borgia, Madeleine B. Borgia and Katrine Bugge: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Biochemistry, University of Zurich, Zurich, 8057, Switzerland

    Alessandro Borgia, Madeleine B. Borgia, Vera M. Kissling, Pétur O. Heidarsson, Andrea Sottini, Andrea Soranno, Karin J. Buholzer, Daniel Nettels & Benjamin Schuler

  2. Department of Biology University of Copenhagen, Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science and Integrative Structural Biology at University of Copenhagen (ISBUC), University of Copenhagen, Copenhagen N, 2200, Denmark

    Katrine Bugge, Catarina B. Fernandes & Birthe B. Kragelund

  3. Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, 63110, Missouri, USA

    Andrea Soranno

  4. Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, 20892-0520, Maryland, USA

    Robert B. Best

  5. Department of Physics, University of Zurich, Zurich, 8057, Switzerland

    Benjamin Schuler

Authors

  1. Alessandro Borgia

    You can also search for this author in PubMed Google Scholar

  2. Madeleine B. Borgia

    You can also search for this author in PubMed Google Scholar

  3. Katrine Bugge

    You can also search for this author in PubMed Google Scholar

  4. Vera M. Kissling

    You can also search for this author in PubMed Google Scholar

  5. Catarina B. Fernandes

    You can also search for this author in PubMed Google Scholar

  6. Andrea Sottini

    You can also search for this author in PubMed Google Scholar

  7. Andrea Soranno

    You can also search for this author in PubMed Google Scholar

  8. Karin J. Buholzer

    You can also search for this author in PubMed Google Scholar

  9. Daniel Nettels

    You can also search for this author in PubMed Google Scholar

  10. Birthe B. Kragelund

    You can also search for this author in PubMed Google Scholar

  11. Robert B. Best

    You can also search for this author in PubMed Google Scholar

  12. Benjamin Schuler

    You can also search for this author in PubMed Google Scholar

Contributions

A.B., M.B.B., K.B., B.B.K., R.B.B. and B.S. designed research; M.B.B., A.B., V.M.K. and A.Sot. produced and labelled fluorescent protein variants; A.B. and M.B.B. performed single-molecule experiments; A.B., M.B.B., A.Sor. and D.N. analysed single-molecule data; D.N. developed single-molecule instrumentation and data analysis tools; A.Sot. and A.B. carried out stopped-flow measurements, A.B., M.B.B., K.J.B. and A.Sot. established experimental conditions for single-molecule measurements; C.B.F. and P.O.H. produced protein samples for NMR; K.B. and C.B.F. performed and analysed NMR measurements; A.Sor. carried out the bioinformatics analysis; R.B.B. conducted and analysed simulations; A.B., B.B.K. and C.B.F. carried out circular dichroism experiments; B.B.K., R.B.B. and B.S. supervised research; B.S., A.B., R.B.B., B.B.K. and K.B. wrote the paper with help from all authors.

Corresponding authors

Correspondence to Alessandro Borgia, Birthe B. Kragelund, Robert B. Best or Benjamin Schuler.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks E. Zuiderweg and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Figure 1 Titrations of ProTα and H1 globular domain.

a, Titration of 15N-ProTα with zero to sevenfold molar addition of the H1 globular domain followed by 1H–15N HSQC spectra; n = 2 repeats of this measurement yielded consistent results. b, Peak intensity ratios for assigned residues of ProTα relative to the free state induced by zero to 1.7-fold molar addition of the H1 globular domain (n = 2). c, Weighted backbone CSPs per residue of ProTα induced by zero to sevenfold molar addition of the H1 globular domain (n = 2). For comparison, CSPs of ProTα with equimolar addition of H1 are shown in grey (n = 5). In a–c, ‘colour key 1’ applies; grey stars, prolines and unassigned residues. d, ProTα CSPs plotted against concentration and times excess of the H1 globular domain relative to the free state for residues 46–106 upon zero to sevenfold molar addition of the H1 globular domain. Curves corresponding to individual residues are shown in different colours for clarity. e, Far-UV circular dichroism spectrum of the H1 globular domain. f, Thermal denaturation of the H1 globular domain followed by the change in ellipticity at 222 nm (Tm = 320.5 ± 0.3 K, ΔHm = −44 ± 2 kcal mol−1). Inset in f shows fraction of unfolded H1 globular domain (fu) as a function of temperature. g, Titration of 100 μM 13C–15N- H1 globular domain with zero to sevenfold molar addition of ProTα followed by 1H–15N HSQC spectra. Peak intensities gradually decrease during the titration. At 3.5- and 7-fold molar excess ProTα, natural abundance peaks of free ProTα appear. 1H–15N HSQC spectrum of 15N-ProTα is shown in grey for comparison. h, Weighted backbone CSPs of the H1 globular domain plotted against concentration and times excess of ProTα relative to the free state on zero to sevenfold molar addition of ProTα. A total of 66 (unassigned) amide backbone peaks were followed and grouped according to the standard deviation (STD) of the CSPs (1 s.d. = 0.0254 p.p.m.). Of these, 55% had CSPs larger than 1 STD.

Extended Data Figure 2 Titration of 15N-ProTα with H1.

a, 1H–15N HSQC spectrum of 11 μM free 15N-ProTα with assigned residues labelled (left) and titrated with zero to fourfold molar addition of H1 (right); n = 5 individual repeats of this measurement yielded consistent results. b, Weighted backbone CSPs of ProTα (residues 46–106) relative to the free state on zero to fourfold molar addition of H1, plotted against concentration and times excess of H1. Curves corresponding to individual residues are shown in different colours for clarity. c, d, CSPs (c) and peak intensity ratios (d) for assigned residues of ProTα induced by zero to fourfold molar addition of H1 (bar colours correspond to key); n = 5 for both. e, T115N relaxation times of free (red) and H1-bound (purple) 15N-ProTα. 〈T1〉 = 610 ms (free) and 636 ms (complex); n = 2 individual repeats of this measurement yielded consistent results. f , T215N relaxation times of free (red) and H1-bound (purple) 15N-ProTα. 〈T2〉 = 302 ms (free) and 217 ms (complex). In c–f, light grey stars, prolines and unassigned residues; dark grey stars, overlap and/or insufficient data quality. Circles in e and f are mean values from n = 3 consecutive data acquisitions on the same samples, errors are s.d.

Extended Data Figure 3 Titration of 13C–15N-H1 with ProTα.

a, 1H–15N HSQC spectra of the free 13C–15N-H1 globular domain (dark green) and free 13C–15N-H1 (orange). The majority of the amide peaks of the H1 globular domain overlap with the more dispersed peaks from H1, indicating the similarity in structure of the H1 globular domain in isolation and within H1. b, Titration followed by 1H–15N HSQC spectra of 13C–15N-H1 with zero to fourfold molar addition of ProTα. Data acquired on His6-tagged H1; n = 2 individual repeats of this measurement yielded consistent results. c, CSPs relative to free H1 of 11 traceable H1 amide backbone peaks from the intrinsically disordered region (based on overlay with 1H–15N HSQC spectra of the H1 globular domain (in a)) on zero to fourfold molar addition of ProTα plotted against concentration and times excess. Curves corresponding to individual residues are shown in different colours for clarity. d, CSPs plotted against peak intensity ratios relative to the free state of H1 of the 11 H1 amides at 1× excess of ProTα. Colours correspond to those in c. e, Overlay of the Cα–Hα region from 1H–13C HSQC spectra of free 13C–15N-H1 (blue) and the 13C–15N-H1 globular domain (green). The H1 1H–13C HSQC spectrum is dominated by intense clusters of peaks not present in the H1 globular domain spectrum, consistent with the large fraction of residue repeats in the H1 disordered regions. f, Cα–Hα region of 13C–15N-H1 on titration with ProTα. The lack of detectable changes in Cα–Hα resonances is consistent with the absence of secondary structure induction in the disordered regions of H1 on binding.

Extended Data Figure 4 Hydrodynamic radii and stoichiometry of the H1–ProTα complex.

a, RH of free and bound 15N-ProTα (100 μM) determined with pulsed-field gradient NMR at 283 K. The signal decays of free 15N-ProTα (red), with H1 at a 1:1 molar ratio (purple) and with the H1 globular domain at a 1:7 molar ratio (green) as a function of gradient strength, together with corresponding fits and a table of the diffusion coefficients and resulting RH values. b, RH measured by two-focus fluorescence correlation spectroscopy at 295 K. Lines show the mean RH from n = 2 independent measurements of H10 (blue) and ProTα2 (red) labelled with Alexa 594 in the absence of the binding partner. Symbols represent the mean RH from n = 2 independent measurements of labelled ProTα (5 nM) in the presence of equimolar concentrations of unlabelled ProTα and unlabelled H1. Error bars or shaded bands, s.d. c, Stoichiometry ratio71 versus transfer efficiency plots from intermolecular single-molecule FRET measurements of ProTα2 + H1194 (top), ProTα56 + H1194 (middle), and ProTα110 + H1194 (bottom); pictograms in panels indicate labelling locations. A stoichiometry ratio of 0.5 indicates a 1:1 complex. The peaks at E ≈ 0 originate from molecules or complexes that lack an acceptor dye and remain after filtering for donor-only fluorescence bursts based on pulsed-interleaved excitation. d, e, Transfer efficiency changes at a large excess of unlabelled binding partner for FRET-labelled ProTα56/110 (d) and H1104/194 (e). See Methods for further information on statistics.

Extended Data Figure 5 Fluorescence lifetime analysis.

a–f, Plots of the fluorescence lifetimes of Alexa 488 donor () and Alexa 594 acceptor () normalized by the intrinsic donor lifetime () versus the ratiometric transfer efficiency E (calculated from the number of donor and acceptor photon counts), as a diagnostic for the presence of a broad distance distribution rapidly sampled during the time of a fluorescence burst28,33,34. If fluctuations in transfer efficiency occur on a timescale between the donor fluorescence lifetime (∼4 ns) and the burst duration (∼1 ms), the normalized donor lifetimes cluster above—and the acceptor lifetimes below—the solid diagonal line expected for a single fixed distance, as previously observed for intrinsically disordered proteins34,72. The large deviation from the diagonal observed for both unbound and bound ProTα and H1 supports the presence of broad and rapidly sampled distance distributions. a, ProTα56/110; b, ProTα56/110 + unlabelled H1; c, H10/113; d, H10/113 + unlabelled ProTα; e, ProTα2 + H1194; and f, ProTα110 + H1194. All variants labelled with Alexa 488 (green) and/or Alexa 594 (red) as indicated by the pictograms in the figure panels.

Extended Data Figure 6 Simulation results.

a, Decision graph using the Rodriguez–Laio clustering algorithm69, showing only a single density maximum distant from other density maxima (that is, a single distinct cluster). b, Free energy of association from simulation for ProTα and H1 along the distance between their centres of mass, RPH, yielding a Kd of 7 fM (black curve). Blue and red curves are the free energies for addition of a second H1 or a second ProTα, respectively, to an existing H1–ProTα complex. c, Principal component vectors shown as contact maps. Colours indicate the increase or decrease in each pair distance for that principal component, relative to the other distances. ProTα and H1 residue numbers are indicated in red and blue, respectively. Each principal component describes a feature of the chain arrangement: principal component 1, for example, captures the presence or absence of interactions between the ProTα N terminus and H1. d, Intramolecular (top row) and intermolecular (bottom three rows) distributions of distances corresponding to FRET labelling sites, within the H1–ProTα complex. P and H numbers refer to ProTα and H1 residues, respectively. Filled distributions, simulations without explicit chromophores; green lines, simulations with explicit chromophores.

Extended Data Figure 7 Kinetics of H1–ProTα binding measured by stopped flow.

FRET-labelled ProTα56/110 was mixed rapidly with unlabelled H1 in TBS buffer, and the resulting increase in acceptor fluorescence was monitored. Inset, example at 10 nM H1 with single-exponential fit and residuals shown above (see Methods for details). Decay rates were obtained from single-exponential fits, with an instrument dead time of 3 ms. Standard errors for each H1 concentration were obtained using bootstrapping. The observed rate, kobs, is shown as a function of H1 concentration (cH1); for H1 concentrations between 10 and 100 nM—for which pseudo-first order conditions apply (ProTα concentration after mixing was 2 nM)—the observed rates were fit with kobs = koncH1 + koff = koncH1 + konKd, using the independently determined Kd of 2.1 pM (Extended Data Table 2). The fit yields a bimolecular association rate coefficient of kon = 3.1 ± 0.1 × 109 M−1 s−1 and an apparent dissociation rate coefficient of koff = 6.5 ± 3.1 × 10−3 s−1. The grey area represents the 95% confidence band.

Extended Data Figure 8 Example of the quality of the H1 preparation.

Electrospray ionization mass spectrum of H1(T161C) labelled with Alexa 488 (calculated mass 21,800 Da) and preparative reversed-phase HPLC (Vydac C4) chromatogram (inset) showing absorption at 280 nm (red) and 488 nm (blue) and the elution gradient from solvent A (H2O + 0.1% TFA) to solvent B (100% acetonitrile) (black), illustrating the high purity of the sample. The peak at approximately 5.5 min corresponds to free Alexa 488, and the peak at approximately 16.8 min to H1(T161C) labelled with Alexa 488.

Extended Data Table 1 Sequences of protein constructs and fluorescently labelled variants of H1 and ProTα

Full size table

Extended Data Table 2 Binding affinities, molecular dimensions and reconfiguration times of fluorescently labelled H1 and ProTα

Full size table

Supplementary information

Life Sciences Reporting Summary (PDF 126 kb)

Supplementary Data

This file contains histograms data for source data Extended Data table 2. (XLSX 39 kb)

Coarse-grained simulations of the disordered complex of ProT⍺-H1

A short fragment of the coarse-grained simulation of the ProT⍺-H1 complex. ProT⍺ and H1 are shown in red and blue, respectively. The disordered regions are displayed as stick representation with the folded domain of H1 shown as a smoothed surface. The N-terminal C⍺ carbon of each protein is indicated by a sphere. The duration of the trajectory is approximately 5 times the typical autocorrelation time for pair distances within the complex. The total length of the simulation used for FRET calculations was ∼103 times longer than the fragment shown in the video. (MP4 23668 kb)

PowerPoint slides

Source data

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Borgia, A., Borgia, M., Bugge, K. et al. Extreme disorder in an ultrahigh-affinity protein complex. Nature 555, 61–66 (2018). https://doi.org/10.1038/nature25762

Download citation

  • Received: 04 August 2017

  • Accepted: 17 January 2018

  • Published: 21 February 2018

  • Issue Date: 01 March 2018

  • DOI: https://doi.org/10.1038/nature25762