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Title: Massively parallel, computationally guided design of a proenzyme
Significance Proteins have shown promise as therapeutics and diagnostics, but their effectiveness is limited by our inability to spatially target their activity. To overcome this limitation, we developed a computationally guided method to design inactive proenzymes or zymogens, which are activated through cleavage by a protease. Since proteases are differentially expressed in various tissues and disease states, including cancer, these proenzymes could be targeted to the desired microenvironment. We tested our method on the therapeutically relevant protein carboxypeptidase G2 (CPG2). We designed Pro-CPG2s that are inhibited by 80 to 98% and are partially to fully reactivatable following protease treatment. The developed methodology, with further refinements, could pave the way for routinely designing protease-activated protein-based therapeutics and diagnostics that act in a spatially controlled manner.  more » « less
Award ID(s):
1541278
PAR ID:
10493070
Author(s) / Creator(s):
; ; ; ; ; ; ;
Publisher / Repository:
National Library of Medicine
Date Published:
Journal Name:
Proceedings of the National Academy of Sciences
Volume:
119
Issue:
15
ISSN:
0027-8424
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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