@article{08d21b1e31c24003be8dd1b168fd8209,
title = "Defining the molecular basis of amyloid inhibitors: Human islet amyloid polypeptide-insulin interactions",
abstract = "Human islet amyloid polypeptide (hIAPP or Amylin) is a 37 residue hormone that is cosecreted with insulin from the pancreatic islets. The aggregation of hIAPP plays a role in the progression of type 2 diabetes and contributes to the failure of islet cell grafts. Despite considerable effort, little is known about the mode of action of IAPP amyloid inhibitors, and this has limited rational drug design. Insulin is one of the most potent inhibitors of hIAPP fibril formation, but its inhibition mechanism is not understood. In this study, the aggregation of mixtures of hIAPP with insulin, as well as with the separate A and B chains of insulin, were characterized using ion mobility spectrometry-based mass spectrometry and atomic force microscopy. Insulin and the insulin B chain target the hIAPP monomer in its compact isoform and shift the equilibrium away from its extended isoform, an aggregation-prone conformation, and thus inhibit hIAPP from forming β-sheets and subsequently amyloid fibrils. All-atom molecular modeling supports these conclusions.",
author = "Susa, {Anna C.} and Chun Wu and Bernstein, {Summer L.} and Dupuis, {Nicholas F.} and Hui Wang and Raleigh, {Daniel P.} and Shea, {Joan Emma} and Bowers, {Michael T.}",
note = "Funding Information: The support of the National Science Foundation Grants CHE-1301032 (MTB) and MCB-1158577 (JES) and National Institutes of Health Grant NIH-GM078114 (DPR) is gratefully acknowledged. M.T.B. also thanks Waters Corporation for donation of a Synapt prototype instrument used for part of the work presented here. J.E.S. also thanks David and Lucile Packard Foundation. The computation resources used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant Number OCI-1053575, and the Center for Scientific Computing from the CNSI, MRL: an NSF MRSEC (DMR-1121053) and NSF CNS-0960316. The authors thank Nicholas Economou and Professor Steve Buratto at UCSB for helping with the AFM studies. The authors also thank Catie Carpenter for helping with the figures. Funding Information: The support of the National Science Foundation Grants CHE- 1301032 (MTB) and MCB-1158577 (JES) and National Institutes of Health Grant NIH-GM078114 (DPR) is gratefully acknowledged. M.T.B. also thanks Waters Corporation for donation of a Synapt prototype instrument used for part of the work presented here. J.E.S. also thanks David and Lucile Packard Foundation. The computation resources used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant Number OCI-1053575, and the Center for Scientific Computing from the CNSI, MRL: an NSF MRSEC (DMR- 1121053) and NSF CNS-0960316. The authors thank Nicholas Economou and Professor Steve Buratto at UCSB for helping with the AFM studies. The authors also thank Catie Carpenter for helping with the figures. Publisher Copyright: {\textcopyright} 2014 American Chemical Society.",
year = "2014",
month = sep,
day = "17",
doi = "10.1021/ja504031d",
language = "English (US)",
volume = "136",
pages = "12912--12919",
journal = "Journal of the American Chemical Society",
issn = "0002-7863",
publisher = "American Chemical Society",
number = "37",
}