1 research outputs found
Computational Design of an α‑Gliadin Peptidase
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 <i>k</i><sub>cat</sub>/<i>K</i><sub>M</sub> of 568 M<sup>–1</sup> s<sup>–1</sup>, 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