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.

Evolution of cyclohexadienyl dehydratase from an ancestral solute-binding protein

Nature Chemical Biology volume 14, pages 542–547 (2018)Cite this article

Abstract

The emergence of enzymes through the neofunctionalization of noncatalytic proteins is ultimately responsible for the extraordinary range of biological catalysts observed in nature. Although the evolution of some enzymes from binding proteins can be inferred by homology, we have a limited understanding of the nature of the biochemical and biophysical adaptations along these evolutionary trajectories and the sequence in which they occurred. Here we reconstructed and characterized evolutionary intermediate states linking an ancestral solute-binding protein to the extant enzyme cyclohexadienyl dehydratase. We show how the intrinsic reactivity of a desolvated general acid was harnessed by a series of mutations radiating from the active site, which optimized enzyme–substrate complementarity and transition-state stabilization and minimized sampling of noncatalytic conformations. Our work reveals the molecular evolutionary processes that underlie the emergence of enzymes de novo, which are notably mirrored by recent examples of computational enzyme design and directed evolution.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Functional evolution of CDT.
Fig. 2: Crystal structure of PaCDT.
Fig. 3: Structural and mutational basis for evolution of CDT activity.
Fig. 4: Structural dynamics of CDT.

References

  1. Baier, F., Copp, J. N. & Tokuriki, N. Evolution of enzyme superfamilies: comprehensive exploration of sequence-function relationships. Biochemistry 55, 6375–6388 (2016).

    Article  CAS  PubMed  Google Scholar 

  2. Khersonsky, O. & Tawfik, D. S. Enzyme promiscuity: a mechanistic and evolutionary perspective. Annu. Rev. Biochem. 79, 471–505 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. Furnham, N., Dawson, N. L., Rahman, S. A., Thornton, J. M. & Orengo, C. A. Large-scale analysis exploring evolution of catalytic machineries and mechanisms in enzyme superfamilies. J. Mol. Biol. 428 2 Pt A, 253–267 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Harms, M. J. & Thornton, J. W. Evolutionary biochemistry: revealing the historical and physical causes of protein properties. Nat. Rev. Genet. 14, 559–571 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Tam, R. & Saier, M. H. Jr. A bacterial periplasmic receptor homologue with catalytic activity: cyclohexadienyl dehydratase of Pseudomonas aeruginosa is homologous to receptors specific for polar amino acids. Res. Microbiol. 144, 165–169 (1993).

    Article  CAS  PubMed  Google Scholar 

  6. Ngaki, M. N. et al. Evolution of the chalcone-isomerase fold from fatty-acid binding to stereospecific catalysis. Nature 485, 530–533 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Ortmayer, M. et al. An oxidative N-demethylase reveals PAS transition from ubiquitous sensor to enzyme. Nature 539, 593–597 (2016).

    Article  CAS  PubMed  Google Scholar 

  8. Zhao, G. S., Xia, T. H., Fischer, R. S. & Jensen, R. A. Cyclohexadienyl dehydratase from Pseudomonas aeruginosa. Molecular cloning of the gene and characterization of the gene product. J. Biol. Chem. 267, 2487–2493 (1992).

    CAS  PubMed  Google Scholar 

  9. Berntsson, R. P.-A., Smits, S. H. J., Schmitt, L., Slotboom, D.-J. & Poolman, B. A structural classification of substrate-binding proteins. FEBS Lett. 584, 2606–2617 (2010).

    Article  CAS  PubMed  Google Scholar 

  10. Hochberg, G. K. A. & Thornton, J. W. Reconstructing ancient proteins to understand the causes of structure and function. Annu. Rev. Biophys. 46, 247–269 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Vetting, M. W. et al. Experimental strategies for functional annotation and metabolism discovery: targeted screening of solute binding proteins and unbiased panning of metabolomes. Biochemistry 54, 909–931 (2015).

    Article  CAS  PubMed  Google Scholar 

  12. Gouridis, G. et al. Conformational dynamics in substrate-binding domains influences transport in the ABC importer GlnPQ. Nat. Struct. Mol. Biol. 22, 57–64 (2015).

    Article  CAS  PubMed  Google Scholar 

  13. Marvin, J. S. & Hellinga, H. W. Manipulation of ligand binding affinity by exploitation of conformational coupling. Nat. Struct. Mol. Biol. 8, 795–798 (2001).

    Article  CAS  Google Scholar 

  14. Campbell, E. et al. The role of protein dynamics in the evolution of new enzyme function. Nat. Chem. Biol. 12, 944–950 (2016).

    Article  CAS  PubMed  Google Scholar 

  15. Bar-Even, A., Milo, R., Noor, E. & Tawfik, D. S. The moderately efficient enzyme: futile encounters and enzyme floppiness. Biochemistry 54, 4969–4977 (2015).

    Article  CAS  PubMed  Google Scholar 

  16. Bermejo, G. A., Strub, M.-P., Ho, C. & Tjandra, N. Ligand-free open-closed transitions of periplasmic binding proteins: the case of glutamine-binding protein. Biochemistry 49, 1893–1902 (2010).

    Article  CAS  PubMed  Google Scholar 

  17. Silva, D.-A., Domínguez-Ramírez, L., Rojo-Domínguez, A. & Sosa-Peinado, A. Conformational dynamics of l-lysine, l-arginine, l-ornithine binding protein reveals ligand-dependent plasticity. Proteins 79, 2097–2108 (2011).

    Article  CAS  PubMed  Google Scholar 

  18. Chu, B. C. H., Chan, D. I., DeWolf, T., Periole, X. & Vogel, H. J. Molecular dynamics simulations reveal that apo-HisJ can sample a closed conformation. Proteins 82, 386–398 (2014).

    Article  CAS  PubMed  Google Scholar 

  19. Salverda, M. L. M. et al. Initial mutations direct alternative pathways of protein evolution. PLoS Genet. 7, e1001321 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kaltenbach, M., Jackson, C. J., Campbell, E. C., Hollfelder, F. & Tokuriki, N. Reverse evolution leads to genotypic incompatibility despite functional and active site convergence. eLife 4, e06492 (2015).

    Article  PubMed Central  Google Scholar 

  21. Sugrue, E., Carr, P. D., Scott, C. & Jackson, C. J. Active site desolvation and thermostability tradeoffs in the evolution of catalytically diverse triazine hydrolases. Biochemistry 55, 6304–6313 (2016).

    Article  CAS  PubMed  Google Scholar 

  22. Moroz, Y. S. et al. New tricks for old proteins: single mutations in a non-enzymatic protein give rise to various enzymatic activities. J. Am. Chem. Soc. 137, 14905–14911 (2015).

    Article  CAS  PubMed  Google Scholar 

  23. Tokuriki, N. et al. Diminishing returns and tradeoffs constrain the laboratory optimization of an enzyme. Nat. Commun. 3, 1257 (2012).

    Article  CAS  PubMed  Google Scholar 

  24. Anderson, D. P. et al. Evolution of an ancient protein function involved in organized multicellularity in animals. eLife 5, e10147 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Huang, P.-S., Boyken, S. E. & Baker, D. The coming of age of de novo protein design. Nature 537, 320–327 (2016).

    Article  CAS  PubMed  Google Scholar 

  26. Burton, A. J., Thomson, A. R., Dawson, W. M., Brady, R. L. & Woolfson, D. N. Installing hydrolytic activity into a completely de novo protein framework. Nat. Chem. 8, 837–844 (2016).

    Article  CAS  PubMed  Google Scholar 

  27. Röthlisberger, D. et al. Kemp elimination catalysts by computational enzyme design. Nature 453, 190–195 (2008).

    Article  CAS  PubMed  Google Scholar 

  28. Mak, W. S. & Siegel, J. B. Computational enzyme design: transitioning from catalytic proteins to enzymes. Curr. Opin. Struct. Biol. 27, 87–94 (2014).

    Article  CAS  PubMed  Google Scholar 

  29. Korendovych, I. V. & DeGrado, W. F. Catalytic efficiency of designed catalytic proteins. Curr. Opin. Struct. Biol. 27, 113–121 (2014).

    Article  CAS  PubMed  Google Scholar 

  30. Blomberg, R. et al. Precision is essential for efficient catalysis in an evolved Kemp eliminase. Nature 503, 418–421 (2013).

    Article  CAS  PubMed  Google Scholar 

  31. Khersonsky, O. et al. Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59. Proc. Natl. Acad. Sci. USA 109, 10358–10363 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Engler, C., Kandzia, R. & Marillonnet, S. A one pot, one step, precision cloning method with high throughput capability. PLoS One 3, e3647 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Clifton, B. E. & Jackson, C. J. Ancestral protein reconstruction yields insights into adaptive evolution of binding specificity in solute-binding proteins. Cell Chem. Biol. 23, 236–245 (2016).

    Article  CAS  PubMed  Google Scholar 

  35. Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).

    Article  CAS  PubMed  Google Scholar 

  36. Abascal, F., Zardoya, R. & Posada, D. ProtTest: selection of best-fit models of protein evolution. Bioinformatics 21, 2104–2105 (2005).

    Article  CAS  PubMed  Google Scholar 

  37. Yang, Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591 (2007).

    Article  CAS  PubMed  Google Scholar 

  38. Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).

    Article  CAS  PubMed  Google Scholar 

  39. McKellar, J. L., Minnell, J. J. & Gerth, M. L. A high-throughput screen for ligand binding reveals the specificities of three amino acid chemoreceptors from Pseudomonas syringae pv. actinidiae. Mol. Microbiol. 96, 694–707 (2015).

    Article  CAS  PubMed  Google Scholar 

  40. Gibson, F. Chorismic acid: purification and some chemical and physical studies. Biochem. J. 90, 256–261 (1964).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Gibson, M. I. & Gibson, F. Preliminary studies on the isolation and metabolism of an intermediate in aromatic biosynthesis: chorismic acid. Biochem. J. 90, 248–256 (1964).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. McPhillips, T. M. et al. Blu-Ice and the Distributed Control System: software for data acquisition and instrument control at macromolecular crystallography beamlines. J. Synchrotron Radiat. 9, 401–406 (2002).

    Article  CAS  PubMed  Google Scholar 

  43. Battye, T. G. G., Kontogiannis, L., Johnson, O., Powell, H. R. & Leslie, A. G. W. iMOSFLM: a new graphical interface for diffraction-image processing with MOSFLM. Acta Crystallogr. D Biol. Crystallogr. 67, 271–281 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Kabsch, W. XDS. Acta Crystallogr. D. Biol. Crystallogr. 66, 125–132 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Winn, M. D. et al. Overview of the CCP4 suite and current developments. Acta Crystallogr. D Biol. Crystallogr. 67, 235–242 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. McCoy, A. J. et al. Phaser crystallographic software. J. Appl. Crystallogr. 40, 658–674 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D Biol. Crystallogr. 66, 486–501 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Murshudov, G. N., Vagin, A. A. & Dodson, E. J. Refinement of macromolecular structures by the maximum-likelihood method. Acta Crystallogr. D Biol. Crystallogr. 53, 240–255 (1997).

    Article  CAS  PubMed  Google Scholar 

  49. Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D Biol. Crystallogr. 66, 213–221 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhao, H. & Zha, W. In vitro ‘sexual’ evolution through the PCR-based staggered extension process (StEP). Nat. Protoc. 1, 1865–1871 (2006).

    Article  CAS  PubMed  Google Scholar 

  51. Herman, A. & Tawfik, D. S. Incorporating Synthetic Oligonucleotides via Gene Reassembly (ISOR): a versatile tool for generating targeted libraries. Protein Eng. Des. Sel. 20, 219–226 (2007).

    Article  CAS  PubMed  Google Scholar 

  52. Rockah-Shmuel, L., Tawfik, D. S. & Goldsmith, M. in Directed Evolution Library Creation: Methods and Protocols (eds. Gillam, E. M. J., Copp, J. N. & Ackerley, D. F.) Vol. 1179, 129–137 (Springer-Verlag, 2014).

  53. Sali, A. & Blundell, T. L. Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol. 234, 779–815 (1993).

    Article  CAS  PubMed  Google Scholar 

  54. Pronk, S. et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29, 845–854 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Oostenbrink, C., Villa, A., Mark, A. E. & van Gunsteren, W. F. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J. Comput. Chem. 25, 1656–1676 (2004).

    Article  CAS  PubMed  Google Scholar 

  56. Bowers, K. et al. Scalable algorithms for molecular dynamics simulations on commodity clusters. Proc. ACM/IEEE SC Conf. Supercomput. (SC06) (ACM, Tampa, Florida, 2006).

    Google Scholar 

  57. Harder, E. et al. OPLS3: A force field providing broad coverage of drug-like small molecules and proteins. J. Chem. Theory Comput. 12, 281–296 (2016).

    Article  CAS  PubMed  Google Scholar 

  58. Grant, B. J., Rodrigues, A. P. C., ElSawy, K. M., McCammon, J. A. & Caves, L. S. D. Bio3d: an R package for the comparative analysis of protein structures. Bioinformatics 22, 2695–2696 (2006).

    Article  CAS  PubMed  Google Scholar 

  59. Hayward, S. & Berendsen, H. J. Systematic analysis of domain motions in proteins from conformational change: new results on citrate synthase and T4 lysozyme. Proteins 30, 144–154 (1998).

    Article  CAS  PubMed  Google Scholar 

  60. Olsson, M. H. M., Søndergaard, C. R., Rostkowski, M. & Jensen, J. H. PROPKA3: consistent treatment of internal and surface residues in empirical pKa calculations. J. Chem. Theory Comput. 7, 525–537 (2011).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

B.E.C. and J.A.K. were supported by Australian Postgraduate Awards. B.E.C. was also supported by a Rod Rickards PhD scholarship and an Alan Sargeson scholarship. This research was undertaken with the assistance of resources, services, and staff from the Australian National Computational Infrastructure (NCI), the Australian Synchrotron, and the CSIRO Collaborative Crystallisation Centre, and funding from the Australian Research Council Discovery Project scheme (C.J.J.). We thank A. Saeed, P. Yates, L. Tan and S. Warring for additional technical contributions. We thank H. Janovjak (IST Austria) for gifting us the pDOTS7 plasmid.

Author information

Author notes

  1. Monica L. Gerth

    Present address: School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand

Authors and Affiliations

  1. Research School of Chemistry, Australian National University, Canberra, ACT, Australia

    Ben E. Clifton, Joe A. Kaczmarski, Paul D. Carr & Colin J. Jackson

  2. Department of Biochemistry, University of Otago, Dunedin, New Zealand

    Monica L. Gerth

  3. Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada

    Nobuhiko Tokuriki

Authors
  1. Ben E. Clifton
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joe A. Kaczmarski
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paul D. Carr
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Monica L. Gerth
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nobuhiko Tokuriki
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Colin J. Jackson
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

B.E.C. and C.J.J. conceived the study; B.E.C. and J.A.K. performed computational analysis; J.A.K., B.E.C., and M.L.G. performed experimental characterization of proteins; B.E.C., J.A.K., P.D.C., and C.J.J. solved the crystal structures; N. T. and C.J.J. supervised students; B.E.C., J.A.K., and C.J.J. wrote the paper. All authors contributed to experimental design, editing of the paper, and interpretation of results.

Corresponding author

Correspondence to Colin J. Jackson.

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.

Supplementary information

Supplementary Text and Figures

Supplementary Table 1–13, Supplementary Figures 1–13

Reporting Summary

Supplementary Dataset 1

Ligand screening of Pu1068 and AncCDT-2 by differential scanning fluorimetry

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Clifton, B.E., Kaczmarski, J.A., Carr, P.D. et al. Evolution of cyclohexadienyl dehydratase from an ancestral solute-binding protein. Nat Chem Biol 14, 542–547 (2018). https://doi.org/10.1038/s41589-018-0043-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41589-018-0043-2

This article is cited by

Search

Advanced 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