The Journal of Physical Chemistry BBiophysicsPeer-reviewed journal article
In vitro-prepared A30P alpha-synuclein fibrils adopt the conserved and disease-relevant Greek key fold
Moses H. MilchbergiD, Owen A. WarmuthiD, Collin G. BorcikiD, Ruixian Han, Benjamin D. HardingiD, Barry E. DeZoniaiD, Dhruva D. DhavaleiD, Joshua A. Pierson, Paul T. KotzbaueriD, Elizabeth WrightiD, Charles D. SchwietersiD, Chad M. RienstraiD
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Abstract
The pathological hallmark of Parkinson Disease (PD) is the formation of the protein alpha-synuclein (Asyn) into {beta}-sheet rich, self-templating fibrils in the brain. Since the first atomic structure of wild-type Asyn fibrils was determined nearly a decade ago, several other in vitro structures of hereditary mutant fibrils and structures derived from post-mortem diseased patient tissue have been determined by solid-state nuclear magnetic resonance (SSNMR) spectroscopy and cryo-electron microscopy. These structures have not only expanded the library of structures available for computational modeling of drug binding and therapeutics development but have also given unprecedented insight into the disease specificity and structural polymorphism of Asyn fibrils. Here, we report the high-resolution SSNMR structure of the A30P hereditary mutant Asyn fibril, associated with early-onset PD. Our structural model is calculated using several thousand distance restraints derived from one sample, primarily sourced through 3D 13C-13C-13C correlation experiments. The structure adopts a Greek key topology yet does not include the P30 mutation site within the fibril core. We also introduce a comprehensive method for the rapid comparison of SSNMR spectra between Asyn polymorphs of known structure and validate the A30P fold. Lastly, we find that the structure is highly similar to many other experimental structures of both in vitro and ex vivo Asyn fibrils, including those with other hereditary point mutations, suggesting a conserved accessible fold.
- organism: human
- assay: structural biology
- research focus: protein folding & dynamics
- approach: statistical model
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