Computational redesign of endonuclease DNA binding and cleavage specificity (original) (raw)

Nature volume 441, pages 656–659 (2006)Cite this article

Abstract

The reprogramming of DNA-binding specificity is an important challenge for computational protein design that tests current understanding of protein–DNA recognition, and has considerable practical relevance for biotechnology and medicine1,2,3,4,5,6. Here we describe the computational redesign of the cleavage specificity of the intron-encoded homing endonuclease I-_Mso_I7 using a physically realistic atomic-level forcefield8,9. Using an in silico screen, we identified single base-pair substitutions predicted to disrupt binding by the wild-type enzyme, and then optimized the identities and conformations of clusters of amino acids around each of these unfavourable substitutions using Monte Carlo sampling10. A redesigned enzyme that was predicted to display altered target site specificity, while maintaining wild-type binding affinity, was experimentally characterized. The redesigned enzyme binds and cleaves the redesigned recognition site ∼10,000 times more effectively than does the wild-type enzyme, with a level of target discrimination comparable to the original endonuclease. Determination of the structure of the redesigned nuclease-recognition site complex by X-ray crystallography confirms the accuracy of the computationally predicted interface. These results suggest that computational protein design methods can have an important role in the creation of novel highly specific endonucleases for gene therapy and other applications.

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Acknowledgements

We thank J. L. Eklund for assistance with binding assays, and B. W. Shen for assistance with data collection and refinement. This work was supported by fellowships from the Jane Coffin Childs Memorial Fund (J.J.H.), the National Science Foundation (C.M.D.), and grants from the National Institute of Health (R.J.M. and B.L.S.), the Howard Hughes Medical Institute (D.B.), and the Gates Foundation Grand Challenges Program (B.L.S., D.B., R.J.M.). Author Contributions J.J.H. and C.M.D. developed the original protein–DNA interface design methods and code. J.A. made further code and method developments, generated and assessed the computational predictions, and performed mutagenesis, biochemical characterization, and crystallization. D.S. collected and processed the crystallographic data, and aided in protein purification and structure refinement.

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Authors and Affiliations

  1. Howard Hughes Medical Institute and Department of Biochemistry,
    Justin Ashworth, James J. Havranek, Carlos M. Duarte & David Baker
  2. Departments of Pathology and Genome Sciences, University of Washington, Seattle, Washington, 98195, USA
    Raymond J. Monnat Jr
  3. Division of Basic Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue, Washington, 98109, Seattle, USA
    Django Sussman & Barry L. Stoddard

Authors

  1. Justin Ashworth
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  2. James J. Havranek
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  3. Carlos M. Duarte
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  4. Django Sussman
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  5. Raymond J. Monnat Jr
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  6. Barry L. Stoddard
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  7. David Baker
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Corresponding authors

Correspondence toJustin Ashworth or David Baker.

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Competing interests

The atomic coordinates of the redesigned I-_Mso_I endonuclease bound to its cognate DNA have been deposited in the Protein Data Bank with the accession number 2FLD. Reprints and permissions information are available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.

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Ashworth, J., Havranek, J., Duarte, C. et al. Computational redesign of endonuclease DNA binding and cleavage specificity.Nature 441, 656–659 (2006). https://doi.org/10.1038/nature04818

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Editorial Summary

Design for living

Altering the specificity of DNA-cleaving enzymes could be useful in many medical or biotechnological applications, but it is quite a challenge in terms of computational protein design. Ashwell et al. have used computational redesign to alter the target-site specificity of the I-_Mso_I homing endonuclease, while maintaining wild-type binding affinity. The redesigned enzyme binds and cleaves the new DNA recognition site about 10,000 times more effectively than the wild-type enzyme, with target discrimination comparable to the original endonuclease. These results suggest that computational protein design methods can be used to create novel and highly specific endonucleases for gene therapy and other applications.