Computational design of an α-gliadin peptidase

Sydney R. Gordon, Elizabeth J. Stanley, Sarah Wolf, Angus Toland, Sean J. Wu, Daniel Hadidi, Jeremy Mills, David Baker, Ingrid Swanson Pultz, Justin B. Siegel

Research output: Contribution to journalArticle

51 Citations (Scopus)

Abstract

The ability to rationally modify enzymes to perform novel chemical transformations is essential for the rapid production of next-generation protein therapeutics. Here we describe the use of chemical principles to identify a naturally occurring acid-active peptidase, and the subsequent use of computational protein design tools to reengineer its specificity toward immunogenic elements found in gluten that are the proposed cause of celiac disease. The engineered enzyme exhibits a kcat/KM of 568 M-1 s-1, representing a 116-fold greater proteolytic activity for a model gluten tetrapeptide than the native template enzyme, as well as an over 800-fold switch in substrate specificity toward immunogenic portions of gluten peptides. The computationally engineered enzyme is resistant to proteolysis by digestive proteases and degrades over 95% of an immunogenic peptide implicated in celiac disease in under an hour. Thus, through identification of a natural enzyme with the pre-existing qualities relevant to an ultimate goal and redefinition of its substrate specificity using computational modeling, we were able to generate an enzyme with potential as a therapeutic for celiac disease.

Original languageEnglish (US)
Pages (from-to)20513-20520
Number of pages8
JournalJournal of the American Chemical Society
Volume134
Issue number50
DOIs
StatePublished - Dec 19 2012
Externally publishedYes

Fingerprint

Gliadin
Peptide Hydrolases
Enzymes
Glutens
Celiac Disease
Substrate Specificity
Peptides
Proteolysis
Proteins
Substrates
Switches
Acids
Therapeutics

ASJC Scopus subject areas

  • Chemistry(all)
  • Catalysis
  • Biochemistry
  • Colloid and Surface Chemistry

Cite this

Gordon, S. R., Stanley, E. J., Wolf, S., Toland, A., Wu, S. J., Hadidi, D., ... Siegel, J. B. (2012). Computational design of an α-gliadin peptidase. Journal of the American Chemical Society, 134(50), 20513-20520. https://doi.org/10.1021/ja3094795

Computational design of an α-gliadin peptidase. / Gordon, Sydney R.; Stanley, Elizabeth J.; Wolf, Sarah; Toland, Angus; Wu, Sean J.; Hadidi, Daniel; Mills, Jeremy; Baker, David; Pultz, Ingrid Swanson; Siegel, Justin B.

In: Journal of the American Chemical Society, Vol. 134, No. 50, 19.12.2012, p. 20513-20520.

Research output: Contribution to journalArticle

Gordon, SR, Stanley, EJ, Wolf, S, Toland, A, Wu, SJ, Hadidi, D, Mills, J, Baker, D, Pultz, IS & Siegel, JB 2012, 'Computational design of an α-gliadin peptidase', Journal of the American Chemical Society, vol. 134, no. 50, pp. 20513-20520. https://doi.org/10.1021/ja3094795
Gordon SR, Stanley EJ, Wolf S, Toland A, Wu SJ, Hadidi D et al. Computational design of an α-gliadin peptidase. Journal of the American Chemical Society. 2012 Dec 19;134(50):20513-20520. https://doi.org/10.1021/ja3094795
Gordon, Sydney R. ; Stanley, Elizabeth J. ; Wolf, Sarah ; Toland, Angus ; Wu, Sean J. ; Hadidi, Daniel ; Mills, Jeremy ; Baker, David ; Pultz, Ingrid Swanson ; Siegel, Justin B. / Computational design of an α-gliadin peptidase. In: Journal of the American Chemical Society. 2012 ; Vol. 134, No. 50. pp. 20513-20520.
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