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Predictive atomic resolution descriptions of intrinsically disordered hTau40 and alpha-synuclein in solution from NMR and small angle scattering.

MPG-Autoren
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Schwalbe,  M.
Research Group of Protein Structure Determination using NMR, MPI for biophysical chemistry, Max Planck Society;

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Bibow,  S.
Research Group of Protein Structure Determination using NMR, MPI for biophysical chemistry, Max Planck Society;

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Jaremko,  M.
Department of NMR Based Structural Biology, MPI for Biophysical Chemistry, Max Planck Society;

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Jaremko,  L.
Department of NMR Based Structural Biology, MPI for Biophysical Chemistry, Max Planck Society;

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Gajda,  M. J.
Research Group of Protein Structure Determination using NMR, MPI for biophysical chemistry, Max Planck Society;

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Becker,  S.
Department of NMR Based Structural Biology, MPI for Biophysical Chemistry, Max Planck Society;

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Zweckstetter,  M.
Research Group of Protein Structure Determination using NMR, MPI for biophysical chemistry, Max Planck Society;

Volltexte (frei zugänglich)

1949880.pdf
(Verlagsversion), 5MB

Ergänzendes Material (frei zugänglich)

1949880_Suppl.pdf
(Ergänzendes Material), 291KB

Zitation

Schwalbe, M., Ozenne, V., Bibow, S., Jaremko, M., Jaremko, L., Gajda, M. J., et al. (2014). Predictive atomic resolution descriptions of intrinsically disordered hTau40 and alpha-synuclein in solution from NMR and small angle scattering. Structure, 22(2), 238-249. doi:10.1016/j.str.2013.10.020.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0017-C1B6-E
Zusammenfassung
The development of molecular descriptions of intrinsically disordered proteins (IDPs) is essential for elucidating conformational transitions that characterize common neurodegenerative disorders. We use nuclear magnetic resonance, small angle scattering, and molecular ensemble approaches to characterize the IDPs Tau and alpha-synuclein. Ensemble descriptions of IDPs are highly underdetermined due to the inherently large number of degrees of conformational freedom compared with available experimental measurements. Using extensive cross-validation we show that five different types of independent experimental parameters are predicted more accurately by selected ensembles than by statistical coil descriptions. The improvement increases in regions whose local sampling deviates from statistical coil, validating the derived conformational description. Using these approaches we identify enhanced polyproline II sampling in aggregation-nucleation sites, supporting suggestions that this region of conformational space is important for aggregation.