Ensemble cryoEM elucidates the mechanism of insulin capture and degradation by human insulin degrading enzyme
Abstract
Insulin degrading enzyme (IDE) plays key roles in degrading peptides vital in type 2 diabetes, Alzheimer's, inflammation, and other human diseases. However, the process through which IDE recognizes peptides that tend to form amyloid fibrils remained unsolved. We used cryoEM to understand both the apo- and insulin-bound dimeric IDE states, revealing that IDE displays a large opening between the homologous ~55 kDa N- and C-terminal halves to allow selective substrate capture based on size and charge complementarity. We also used cryoEM, X-ray crystallography, SAXS, and HDX-MS to elucidate the molecular basis of how amyloidogenic peptides stabilize the disordered IDE catalytic cleft, thereby inducing selective degradation by substrate-assisted catalysis. Furthermore, our insulin-bound IDE structures explain how IDE processively degrades insulin by stochastically cutting either chain without breaking disulfide bonds. Together, our studies provide a mechanism for how IDE selectively degrades amyloidogenic peptides and offers structural insights for developing IDE-based therapies.
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Funding
National Institutes of Health (GM81539)
- Wei-Jen Tang
Defense Advanced Research Projects Agency (N66001-14-2-4053)
- David R Liu
Simons Foundation (349247)
- Bridget Carragher
- Clinton S Potter
National Institutes of Health (GM121964)
- Wei-Jen Tang
National Institutes of Health (GM103310)
- Bridget Carragher
- Clinton S Potter
National Institutes of Health (R35 GM118062)
- David R Liu
Howard Hughes Medical Institute
- David R Liu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Sriram Subramaniam, National Cancer Institute, United States
Version history
- Received: November 15, 2017
- Accepted: March 28, 2018
- Accepted Manuscript published: March 29, 2018 (version 1)
- Version of Record published: April 20, 2018 (version 2)
Copyright
© 2018, Zhang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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