Article | Published:

Discovery of a regioselectivity switch in nitrating P450s guided by molecular dynamics simulations and Markov models

Nature Chemistry volume 8, pages 419425 (2016) | Download Citation

Abstract

The dynamic motions of protein structural elements, particularly flexible loops, are intimately linked with diverse aspects of enzyme catalysis. Engineering of these loop regions can alter protein stability, substrate binding and even dramatically impact enzyme function. When these flexible regions are unresolvable structurally, computational reconstruction in combination with large-scale molecular dynamics simulations can be used to guide the engineering strategy. Here we present a collaborative approach that consists of both experiment and computation and led to the discovery of a single mutation in the F/G loop of the nitrating cytochrome P450 TxtE that simultaneously controls loop dynamics and completely shifts the enzyme's regioselectivity from the C4 to the C5 position of L-tryptophan. Furthermore, we find that this loop mutation is naturally present in a subset of homologous nitrating P450s and confirm that these uncharacterized enzymes exclusively produce 5-nitro-L-tryptophan, a previously unknown biosynthetic intermediate.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    , & Mechanism of oxidation reactions catalyzed by cytochrome P450 enzymes. Chem. Rev. 104, 3947–3980 (2004).

  2. 2.

    & in Cytochrome P450: Structure, Mechanism, and Biochemistry 3rd edn (ed. Ortiz de Montellano, P. R.) Ch. 2, 45–85 (Plenum, 2005).

  3. 3.

    , & P450(BM3) (CYP102A1): connecting the dots. Chem. Soc. Rev. 41, 1218–1260 (2012).

  4. 4.

    & Diversity of P450 enzymes in the biosynthesis of natural products. Nat. Prod. Rep. 29, 1251–1266 (2012).

  5. 5.

    et al. Substrate recognition by the multifunctional cytochrome P450 MycG in mycinamicin hydroxylation and epoxidation reactions. J. Biol. Chem. 287, 37880–37890 (2012).

  6. 6.

    & in Cytochrome P450: Structure, Mechanism, and Biochemistry 4th edn (ed. Ortiz de Montellano, P. R.) Ch. 3, 69–109 (Springer, 2015).

  7. 7.

    in Cytochrome P450: Structure, Mechanism, and Biochemistry 4th edn (ed. Ortiz de Montellano, P. R.) Ch. 4, 111–176 (Springer, 2015).

  8. 8.

    , & Conformational plasticity and structure/function relationships in cytochromes P450. Antioxid. Redox Signal. 13, 1273–1296 (2010).

  9. 9.

    in Fifty Years of Cytochrome P450 Research (ed. Yamazaki, H.) Ch. 4, 75–94 (Springer, 2014).

  10. 10.

    , , , & Structure and function of cytochromes P450: a comparative analysis of three crystal structures. Structure 2, 41–62 (1995).

  11. 11.

    Cytochrome P450 flexibility. Proc. Natl Acad. Sci. USA 100, 13121–13122 (2003).

  12. 12.

    , , & Engineered alkane-hydroxylating cytochrome P450(BM3) exhibiting nativelike catalytic properties. Angew. Chem. Int. Ed. 46, 8414–8418 (2007).

  13. 13.

    et al. Crystal structure of a thermophilic cytochrome P450 from the archaeon Sulfolobus solfataricus. J. Biol. Chem. 275, 31086–31092 (2000).

  14. 14.

    , , , & Structure of cytochrome P450 PimD suggests epoxidation of the polyene macrolide pimaricin occurs via a hydroperoxoferric intermediate. Chem. Biol. 17, 841–851 (2010).

  15. 15.

    et al. Structural analysis of HmtT and HmtN involved in the tailoring steps of himastatin biosynthesis. FEBS Lett. 587, 1675–1680 (2013).

  16. 16.

    , , & Regioselective nitration of tryptophan by a complex between bacterial nitric-oxide synthase and tryptophanyl-tRNA synthetase. J. Biol. Chem. 279, 49567–49570 (2004).

  17. 17.

    & Biosynthesis of nitro compounds. ChemBioChem 8, 973–977 (2007).

  18. 18.

    & Nitroaromatic compounds, from synthesis to biodegradation. Microbiol. Mol. Biol. Rev. 74, 250–272 (2010).

  19. 19.

    et al. Cytochrome P450-catalyzed L-tryptophan nitration in thaxtomin phytotoxin biosynthesis. Nature Chem. Biol. 8, 814–816 (2012).

  20. 20.

    et al. Structural, functional, and spectroscopic characterization of the substrate scope of the novel nitrating cytochrome P450 TxtE. ChemBioChem 15, 2259–2267 (2014).

  21. 21.

    , , , & Effect of conformational dynamics on substrate recognition and specificity as probed by the introduction of a de novo disulfide bond into cytochrome P450 2B1. J. Biol. Chem. 284, 25678–25686 (2009).

  22. 22.

    et al. Mechanism of the decrease in catalytic activity of human cytochrome P450 2C9 polymorphic variants investigated by computational analysis. J Comput. Chem. 31, 2746–2758 (2010).

  23. 23.

    et al. Flexibility of human cytochrome P450 enzymes: molecular dynamics and spectroscopy reveal important function-related variations. Biochim. Biophys. Acta 1814, 58–68 (2011).

  24. 24.

    , , , & Dynamics and hydration of the active sites of mammalian cytochromes P450 probed by molecular dynamics simulations. Curr. Drug Metab. 13, 177–189 (2012).

  25. 25.

    et al. Coupled flexibility change in cytochrome P450cam substrate binding determined by neutron scattering, NMR, and molecular dynamics simulation. Biophys. J. 103, 2167–2176 (2012).

  26. 26.

    et al. Low-temperature molecular dynamics simulations of horse heart cytochrome c and comparison with inelastic neutron scattering data. Eur. Biophys. J. 42, 291–300 (2013).

  27. 27.

    , , & Structural basis for the mutation-induced dysfunction of human CYP2J2: a computational study. J. Chem. Inf. Model. 53, 1350–1357 (2013).

  28. 28.

    et al. Molecular dynamic investigations of the mutational effects on structural characteristics and tunnel geometry in CYP17A1. J. Chem. Inf. Model. 53, 3308–3317 (2013).

  29. 29.

    et al. Evaluation of influence of single nucleotide polymorphisms in cytochrome P450 2B6 on substrate recognition using computational docking and molecular dynamics simulation. PLoS ONE 9, e96789 (2014).

  30. 30.

    & Molecular dynamics of the P450cam-Pdx complex reveals complex stability and novel interface contacts. Protein Sci. 24, 49–57 (2015).

  31. 31.

    , , , & Investigation of ligand selectivity in CYP3A7 by molecular dynamics simulations. J. Biomol. Struct. Dyn. 33, 2360–2367 (2015).

  32. 32.

    Structure, dynamics, and function of the monooxygenase P450 BM-3: insights from computer simulations studies. J. Phys. Condens. Matter 27, 273102 (2015).

  33. 33.

    et al. Enzymatic hydroxylation of an unactivated methylene C–H bond guided by molecular dynamics simulations. Nature Chem. 7, 653–660 (2015).

  34. 34.

    et al. Structural features and dynamic investigations of the membrane-bound cytochrome P450 17A1. Biochim. Biophys. Acta 1848, 2013–2021 (2015).

  35. 35.

    & in An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation (eds Bowman, G. R., Pande, V. S. & Noé, F.) Ch. 6, 75–90 (Advances in Experimental Medicine and Biology Vol. 797, Springer, 2014).

  36. 36.

    , & Enhanced modeling via network theory: adaptive sampling of Markov state models. J. Chem. Theory Comput. 6, 787–794 (2010).

  37. 37.

    , , , & Understanding protein dynamics with L1-regularized reversible hidden Markov models. Preprint at (2014).

  38. 38.

    et al. Structural insights into the mechanism for recognizing substrate of the cytochrome P450 enzyme TxtE. PLoS One 8, e81526 (2013).

  39. 39.

    in Computer Simulations in Condensed Matter Systems: From Materials to Chemical Biology (eds Ferrario, M., Ciccotti, G. & Binder, K.) 453–493 (Lecture Notes in Physics Vol. 703, Springer, 2006).

  40. 40.

    , & Myoglobin scavenges peroxynitrite without being significantly nitrated. Biochemistry 41, 13460–13472 (2002).

  41. 41.

    , , , & Peroxidase catalyzed nitration of tryptophan derivatives. Mechanism, products and comparison with chemical nitrating agents. Eur. J. Biochem. 271, 2841–2852 (2004).

  42. 42.

    et al. Nitration and nitrosation of N-acetyl-L-tryptophan and tryptophan residues in proteins by various reactive nitrogen species. Free Radical Biol. Med. 37, 671–681 (2004).

  43. 43.

    , & Uncovering rare NADH-preferring ketol–acid reductoisomerases. Metab. Eng. 26C, 17–22 (2014).

  44. 44.

    , , & Reaction of peroxynitrite with L-tryptophan. Redox Rep. 2, 173–177 (1996).

  45. 45.

    Nitrotyrosine, dityrosine, and nitrotryptophan formation from metmyoglobin, hydrogen peroxide, and nitrite. Free Radic. Biol. Med. 36, 565–579 (2004).

  46. 46.

    , , & Reactive nitrogen species generated by heme proteins: mechanism of formation and targets. Coord. Chem. Rev. 250, 1286–1293 (2006).

  47. 47.

    , & Protein nitrotryptophan: formation, significance and identification. J. Proteomics 74, 2300–2312 (2011).

  48. 48.

    & Protein dynamism and evolvability. Science 324, 203–207 (2009).

  49. 49.

    & Engineering of flexible loops in enzymes. ACS Catal. 4, 3201–3211 (2014).

Download references

Acknowledgements

We thank J. Kaiser and P. Nikolovski of the Beckman Molecular Observatory (Caltech) for assistance with crystallography and S. Virgil and the 3CS Center for Catalysis and Chemical Synthesis (Caltech) for assistance with LC-MS analyses. This work was funded by the Gordon and Betty Moore Foundation through grant GBMF2809 to the Caltech Programmable Molecular Technology Initiative (to F.H.A.). S.C.D. is supported by a Ruth L. Kirschstein National Research Service Award postdoctoral fellowship from the National Institutes of Health (NIH) (5F32GM106618). G.K. acknowledges support from the Lawrence Scholars Program, the NIH Simbios Program (U54 GM072970) and the Center for Molecular Analysis and Design (Stanford). J.K.B.C. acknowledges the support of the Resnick Sustainability Institute (Caltech). The Beckman Molecular Observatory is supported by the Gordon and Betty Moore Foundation, the Beckman Institute and the Sanofi-Aventis Bioengineering Research Program (Caltech). The authors thank S. Brinkmann-Chen, T. K. Hyster, J. A. McIntosh, C. K. Prier, R. T. McGibbon and M. M. Sultan for helpful discussions. This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993) and the state of Illinois. The content of this paper is solely the responsibility of the authors and does not represent the official views of any of the funding agencies.

Author information

Affiliations

  1. Division of Chemistry and Chemical Engineering 210-41, California Institute of Technology, California 91125, USA

    • Sheel C. Dodani
    • , Jackson K. B. Cahn
    • , Ye Su
    •  & Frances H. Arnold
  2. Department of Chemistry, SIMBIOS NIH Center for Biomedical Computation, and Center for Molecular Analysis and Design, Stanford University, 318 Campus Drive, Stanford, California 94305, USA

    • Gert Kiss
    •  & Vijay S. Pande

Authors

  1. Search for Sheel C. Dodani in:

  2. Search for Gert Kiss in:

  3. Search for Jackson K. B. Cahn in:

  4. Search for Ye Su in:

  5. Search for Vijay S. Pande in:

  6. Search for Frances H. Arnold in:

Contributions

S.C.D. and G.K. contributed equally to this work. S.C.D. and G.K. designed the research. S.C.D., G.K., J.K.B.C. and Y.S. performed the research. F.H.A. and V.S.P. supervised and provided advice. S.C.D., G.K. and J.K.B.C. analysed the data. S.C.D., G.K., J.K.B.C. and F.H.A. wrote the text and conceived the figures with input from all of the authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Vijay S. Pande or Frances H. Arnold.

Supplementary information

PDF files

  1. 1.

    Supplementary information

    Supplementary information

Zip files

  1. 1.

    Supplementary information

    PyMOL Session File

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nchem.2474

Further reading