Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Dynamic allostery can drive cold adaptation in enzymes

Abstract

Adaptation of organisms to environmental niches is a hallmark of evolution. One prevalent example is that of thermal adaptation, in which two descendants evolve at different temperature extremes1,2. Underlying the physiological differences between such organisms are changes in enzymes that catalyse essential reactions3, with orthologues from each organism undergoing adaptive mutations that preserve similar catalytic rates at their respective physiological temperatures4,5. The sequence changes responsible for these adaptive differences, however, are often at surface-exposed sites distant from the substrate-binding site, leaving the active site of the enzyme structurally unperturbed6,7. How such changes are allosterically propagated to the active site, to modulate activity, is not known. Here we show that entropy-tuning changes can be engineered into distal sites of Escherichia coli adenylate kinase, allowing us to quantitatively assess the role of dynamics in determining affinity, turnover and the role in driving adaptation. The results not only reveal a dynamics-based allosteric tuning mechanism, but also uncover a spatial separation of the control of key enzymatic parameters. Fluctuations in one mobile domain (the LID) control substrate affinity, whereas dynamic attenuation in the other domain (the AMP-binding domain) affects rate-limiting conformational changes that govern enzyme turnover. Dynamics-based regulation may thus represent an elegant, widespread and previously unrealized evolutionary adaptation mechanism that fine-tunes biological function without altering the ground state structure. Furthermore, because rigid-body conformational changes in both domains were thought to be rate limiting for turnover8,9, these adaptation studies reveal a new model for understanding the relationship between dynamics and turnover in adenylate kinase.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Domain structure of E. coli adenylate kinase and sites of allosteric entropy-tuning mutations.
Fig. 2: Thermodynamics of conformational fluctuations in LID and AMPbd entropy-enhancing mutants.
Fig. 3: NMR relaxation-dispersion dynamics and enzyme activity of LID and AMPbd are independent.
Fig. 4: Eyring plots of enzyme activity.
Fig. 5: Spatially segregated tunability of cold adaptation.

References

  1. 1.

    Beers, J. M. & Jayasundara, N. Antarctic notothenioid fish: what are the future consequences of ‘losses’ and ‘gains’ acquired during long-term evolution at cold and stable temperatures? J. Exp. Biol. 218, 1834–1845 (2015).

    Article  PubMed  Google Scholar 

  2. 2.

    Tattersall, G. J. et al. Coping with thermal challenges: physiological adaptations to environmental temperatures. Compr. Physiol. 2, 2151–2202 (2012).

    PubMed  Google Scholar 

  3. 3.

    Fersht, A. R. Enzyme Structure and Mechanism (WH Freeman, New York, 1977).

  4. 4.

    Elias, M., Wieczorek, G., Rosenne, S. & Tawfik, D. S. The universality of enzymatic rate-temperature dependency. Trends Biochem. Sci. 39, 1–7 (2014).

    Article  PubMed  CAS  Google Scholar 

  5. 5.

    Somero, G. N. Adaptation of enzymes to temperature: searching for basic “strategies”. Comp. Biochem. Physiol. B Biochem. Mol. Biol. 139, 321–333 (2004).

    Article  PubMed  CAS  Google Scholar 

  6. 6.

    Fields, P. A. & Somero, G. N. Hot spots in cold adaptation: localized increases in conformational flexibility in lactate dehydrogenase A4 orthologs of Antarctic notothenioid fishes. Proc. Natl Acad. Sci. USA 95, 11476–11481 (1998).

    ADS  Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. 7.

    Fields, P. A., Dong, Y., Meng, X. & Somero, G. N. Adaptations of protein structure and function to temperature: there is more than one way to ‘skin a cat’. J. Exp. Biol. 218, 1801–1811 (2015).

    Article  PubMed  Google Scholar 

  8. 8.

    Henzler-Wildman, K. A. et al. Intrinsic motions along an enzymatic reaction trajectory. Nature 450, 838–844 (2007).

    ADS  Article  PubMed  CAS  Google Scholar 

  9. 9.

    Ådén, J., Verma, A., Schug, A. & Wolf-Watz, M. Modulation of a pre-existing conformational equilibrium tunes adenylate kinase activity. J. Am. Chem. Soc. 134, 16562–16570 (2012).

    Article  PubMed  CAS  Google Scholar 

  10. 10.

    Couñago, R. & Shamoo, Y. Gene replacement of adenylate kinase in the gram-positive thermophile Geobacillus stearothermophilus disrupts adenine nucleotide homeostasis and reduces cell viability. Extremophiles 9, 135–144 (2005).

    Article  PubMed  CAS  Google Scholar 

  11. 11.

    Rundqvist, L. et al. Noncooperative folding of subdomains in adenylate kinase. Biochemistry 48, 1911–1927 (2009).

    Article  PubMed  CAS  Google Scholar 

  12. 12.

    Kerns, S. J. et al. The energy landscape of adenylate kinase during catalysis. Nat. Struct. Mol. Biol. 22, 124–131 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. 13.

    Beckstein, O., Denning, E. J., Perilla, J. R. & Woolf, T. B. Zipping and unzipping of adenylate kinase: atomistic insights into the ensemble of open↔closed transitions. J. Mol. Biol. 394, 160–176 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. 14.

    Daily, M. D., Makowski, L., Phillips, G. N. Jr & Cui, Q. Large-scale motions in the adenylate kinase solution ensemble: coarse-grained simulations and comparison with solution X-ray scattering. Chem. Phys. 396, 84–91 (2012).

    ADS  Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. 15.

    Schrank, T. P., Bolen, D. W. & Hilser, V. J. Rational modulation of conformational fluctuations in adenylate kinase reveals a local unfolding mechanism for allostery and functional adaptation in proteins. Proc. Natl Acad. Sci. USA 106, 16984–16989 (2009).

    ADS  Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Schrank, T. P., Wrabl, J. O. & Hilser, V. J. Conformational heterogeneity within the LID domain mediates substrate binding to Escherichia coli adenylate kinase: function follows fluctuations. Top Curr. Chem. 337, 95–121 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. 17.

    Olsson, U. & Wolf-Watz, M. Overlap between folding and functional energy landscapes for adenylate kinase conformational change. Nat. Commun. 1, 111 (2010).

    ADS  Article  PubMed  CAS  Google Scholar 

  18. 18.

    Rogne, P. & Wolf-Watz, M. Urea-dependent adenylate kinase activation following redistribution of structural states. Biophys. J. 111, 1385–1395 (2016).

    ADS  Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. 19.

    D’Aquino, J. A. et al. The magnitude of the backbone conformational entropy change in protein folding. Proteins 25, 143–156 (1996).

    Article  PubMed  Google Scholar 

  20. 20.

    Schrank, T. P., Elam, W. A., Li, J. & Hilser, V. J. Strategies for the thermodynamic characterization of linked binding/local folding reactions within the native state application to the LID domain of adenylate kinase from Escherichia coli. Methods Enzymol. 492, 253–282 (2011).

    Article  PubMed  CAS  Google Scholar 

  21. 21.

    Henzler-Wildman, K. A. et al. A hierarchy of timescales in protein dynamics is linked to enzyme catalysis. Nature 450, 913–916 (2007).

    ADS  Article  PubMed  CAS  Google Scholar 

  22. 22.

    Wolf-Watz, M. et al. Linkage between dynamics and catalysis in a thermophilic-mesophilic enzyme pair. Nat. Struct. Mol. Biol. 11, 945–949 (2004).

    Article  PubMed  CAS  Google Scholar 

  23. 23.

    Hansen, D. F., Vallurupalli, P. & Kay, L. E. An improved 15N relaxation dispersion experiment for the measurement of millisecond time-scale dynamics in proteins. J. Phys. Chem. B 112, 5898–5904 (2008).

    Article  PubMed  CAS  Google Scholar 

  24. 24.

    Palmer, A. G. III, Kroenke, C. D. & Loria, J. P. Nuclear magnetic resonance methods for quantifying microsecond-to-millisecond motions in biological macromolecules. Methods Enzymol. 339, 204–238 (2001).

    Article  PubMed  CAS  Google Scholar 

  25. 25.

    Eyring, H. The activated complex in chemical reactions. J. Chem. Phys. 3, 107–115 (1935).

    ADS  Article  CAS  Google Scholar 

  26. 26.

    Warshel, A. & Bora, R. P. Perspective: defining and quantifying the role of dynamics in enzyme catalysis. J. Chem. Phys. 144, 180901 (2016).

    ADS  Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. 27.

    Nguyen, V. et al. Evolutionary drivers of thermoadaptation in enzyme catalysis. Science 355, 289–294 (2017).

    ADS  Article  PubMed  CAS  Google Scholar 

  28. 28.

    Arrhenius, S. Textbook of Electrochemistry Ch. VII (Longmans, Green and Co., London 1902).

  29. 29.

    Siddiqui, K. S. Defying the activity-stability trade-off in enzymes: taking advantage of entropy to enhance activity and thermostability. Crit. Rev. Biotechnol. 37, 309–322 (2017).

    Article  PubMed  CAS  Google Scholar 

  30. 30.

    Kim, Y. E., Hipp, M. S., Bracher, A., Hayer-Hartl, M. & Hartl, F. U. Molecular chaperone functions in protein folding and proteostasis. Annu. Rev. Biochem. 82, 323–355 (2013).

    Article  PubMed  CAS  Google Scholar 

  31. 31.

    Müller, C. W., Schlauderer, G. J., Reinstein, J. & Schulz, G. E. Adenylate kinase motions during catalysis: an energetic counterweight balancing substrate binding. Structure 4, 147–156 (1996).

    Article  PubMed  Google Scholar 

  32. 32.

    Müller, C. W. & Schulz, G. E. Structure of the complex between adenylate kinase from Escherichia coli and the inhibitor Ap5A refined at 1.9 A resolution. A model for a catalytic transition state. J. Mol. Biol. 224, 159–177 (1992).

    Article  PubMed  Google Scholar 

  33. 33.

    Rhoads, D. G. & Lowenstein, J. M. Initial velocity and equilibrium kinetics of myokinase. J. Biol. Chem. 243, 3963–3972 (1968).

    PubMed  CAS  Google Scholar 

  34. 34.

    Laidler, K. J. & King, M. C. The development of transition state theory. J. Phys. Chem. 87, 2657–2664 (1983).

    Article  CAS  Google Scholar 

  35. 35.

    Murray, V., Huang, Y., Chen, J., Wang, J. & Li, Q. A novel bacterial expression method with optimized parameters for very high yield production of triple-labeled proteins. Methods Mol. Biol. 831, 1–18 (2012).

    Article  PubMed  CAS  Google Scholar 

  36. 36.

    Lisi, G. P. & Loria, J. P. Solution NMR Spectroscopy for the Study of Enzyme Allostery. Chem. Rev. 116, 6323–6369 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. 37.

    Hilser, V. J., Wrabl, J. O. & Motlagh, H. N. Structural and energetic basis of allostery. Annu. Rev. Biophys. 41, 585–609 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

We thank A. Mujamdar, A. Schön, and K. Tripp for technical assistance and instrumentation. Funding from NIH (R01-GM063747), NSF (MCB-1330211), and Johns Hopkins University is acknowledged.

Reviewer information

Nature thanks G. Phillips and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

Authors

Contributions

H.G.S. designed research, performed experiments, analysed data, interpreted results, discussed research, and wrote the manuscript. J.O.W. analysed data, interpreted results, discussed research, and wrote the manuscript. J.A.A. performed experiments, analysed data, interpreted results, and discussed research. J. L. designed research and discussed research. V.J.H. designed research, analysed data, interpreted results, discussed research, and wrote the manuscript.

Corresponding author

Correspondence to Vincent J. Hilser.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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 Fig. 1 Kinases of known structure that may exhibit similar open/close architecture as E. coli adenylate kinase.

ad, In each panel, the left cartoon represents a putative ‘lid open’ apo-structure, and the right panel represents a putative ‘lid closed’ holo-structure. Protein chains are rainbow-coloured from blue (N terminus) to red (C terminus). Note that in b and c there is crystallographic evidence of disorder (magenta) in the conformationally changing ‘lid’ domain, a situation very similar to that seen for the low-population locally unfolded state in E. coli adenylate kinase, given in a for comparison. a, E. coli adenylate kinase: PDB accessions 4AKE (left) and 1AKE (right). b, Mycobacterium tuberculosis adenylyl sulfate kinase: PDB accessions 4RFV (left) and 4BZX (right). c, Helicobacter pylori shikimate kinase: PDB accessions 1ZUH (left) and 1ZUI (right). d, Sulfolobus tokodaii hexokinase: PDB accessions 2E2N (left) and 2E2O (right).

Extended Data Fig. 2 Other enzymes of known structure that may exhibit similar open/close architecture as E. coli adenylate kinase.

ad, In each panel, the left cartoon represents a putative ‘lid open’ apo-structure, and the right panel represents a putative ‘lid closed’ holo-structure. Protein chains are rainbow-coloured from blue (N terminus) to red (C terminus). Note that in ac there is crystallographic evidence of disorder (magenta) in the conformationally changing ‘lid’ domain, a situation very similar to that seen for the low-population locally unfolded state in E. coli adenylate kinase. a, E. coli 2-glycinamide ribonucleotide transformylase: PDB accessions 1CDD (left) and 1CDE (right). b, l,d-carboxypeptidase: PDB accessions 4JID (left) and 4OX5 (right). c, Thermus thermophilus ribosomal protein L11 methyltransferase PrmA: PDB accessions 2NXC (left) and 2NXE (right). d, Lactobacillus casei dihydrofolate reductase: PDB accessions 1l7o (left) and 2HQP (right).

Extended Data Fig. 3 Comparison of wild-type adenylate kinase HSQC spectrum with mutants A55G and V142G.

a, b, Overlay HSQC spectra at 19 °C for A55G (blue, a) and V142G (red, b); in both panels an identical wild-type spectrum is shown in black. Peak dispersion in all spectra is consistent with folded protein and also is not inconsistent with a similar ground state structure shared among all three proteins. Individual resonances for both mutants exhibited minimal shifts from the wild type, and thus generally permitted transference of assignments from the wild type.

Extended Data Fig. 4 DSC control experiments.

a, Test of the two-state model using wild-type adenylate kinase. Wild-type thermal denaturation is not consistent with a two-state process, as data simulated under the two-state assumption do not agree with experiment, and calorimetric to van’t Hoff enthalpy ratio is substantially greater than 1. Results represent n = 1 independent experiments. b, Reversibility test. Wild-type adenylate kinase exhibited approximately 80% of the original calorimetric area upon re-heating. Results represent n = 1 independent experiments. c, High temperature test. Wild-type adenylate kinase demonstrates complete reversibility when extreme high temperature is avoided. Results represent n = 1 independent experiments. d, Calorimetric heat capacity (ΔCp) of adenylate kinase LID variants. Dependence of enthalpy on melting temperature for wild type, V135G and V142G results in ΔCp,LID of 0.7 ± 0.1 kcal mol−1 K−1 (mean ± s.d.). This value is reasonably consistent with energetics determined from accessible surface areas. Results represent mean ± s.d. of n = 3 independent experiments.

Extended Data Fig. 5 Modelled domain stabilities and ensemble probabilities of adenylate kinase variants.

The DSC data for wild type, LID and AMPbd mutants were each fit to three-state transitions. The fitted parameters correspond to population profiles that differ dramatically between the LID and AMPbd mutants (Fig. 2b and c, respectively). As determined previously from circular dichroism and ITC15, the locally unfolded intermediate (LU), which is 5% populated at physiological temperature for wild-type adenylate kinase (37 °C), is increased to approximately 40% in the LID mutants (Fig. 2b). In contrast to the LID, mutations to the AMPbd do not stabilize the intermediate. Instead, the unfolded (U) state is stabilized, accounting for the decrease in the apparent Tm of the main peak, with no change in the temperature of onset of the intermediate (Fig. 2c). ae, Representative domain stabilities calculated from DSC experiments, see Extended Data Table 1. ΔGtotal = ΔGCA + ΔGLID; in which ‘CA’ denotes ‘CORE-AMPbd’. Mutations other than those in the LID domain have a small effect on the stability of adenylate kinase. a, Wild type. b, A37G AMPbd mutant. c, A55G AMPbd mutant. d, V135G LID mutant. e, V142G LID mutant. fj, Ensemble probability calculations were based on values in Extended Data Table 1. LID mutations V135G and V142G clearly modulate the ensemble by reducing the population of fully folded state and increasing population of unfolded LID domain. f, Wild type. g, A37G AMPbd mutant. h, A55G AMPbd mutant. i, V135G LID mutant. j, V142G LID mutant.

Extended Data Fig. 6 Representative ITC data.

All measurements were obtained at 37 °C, fitting parameters are indicated in each panel. Results represent n = 1 independent experiments. a, Wild type. b, A55G AMPbd mutant. c, V135G LID mutant.

Extended Data Fig 7 Examples of holo-enzymes’ degree of ligand burial.

ac, In each panel, atoms are shown as van der Waals’ spheres. Dark grey indicates protein atoms and yellow indicates ligand. The left side of each panel shows the protein and ligand together, and the right side shows ligand alone. a, ‘Little’ ligand surface area is buried in the complex of deoxyhypusine synthase and nicotinamide adenine-dinucleotide inhibitor, PDB accession 1RLZ. b, ‘Partial’ ligand surface area is buried in the complex of glyceraldehyde-3-phosphate dehydrogenase, nicotinamide adenine-dinucleotide cofactor, and glyceraldehyde-3-phosphate substrate, PDB accession 1NQA. c, ‘Mostly’ ligand surface area is buried in the complex of chorismate-pyruvate lyase and p-hydroxybenzoic acid product, PDB accession 1TT8.

Extended Data Table 1 Summary of thermodynamic parameters obtained from DSC

Supplementary information

Supplementary Information

This file contains Supplementary Text and Data, Supplementary Tables 1-7 and Supplementary References.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Saavedra, H.G., Wrabl, J.O., Anderson, J.A. et al. Dynamic allostery can drive cold adaptation in enzymes. Nature 558, 324–328 (2018). https://doi.org/10.1038/s41586-018-0183-2

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing