Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-27T02:31:23.405Z Has data issue: false hasContentIssue false

Microscale Structural Model of Alzheimer's Aβ(1-40) Amyloid Fibril: Comparative Study of 2- and 3-fold Morphologies

Published online by Cambridge University Press:  31 January 2011

Raffaella Paparcone
Affiliation:
[email protected], Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, Massachusetts, United States
Markus J Buehler
Affiliation:
[email protected], Massachusetts Institute of Technology, Center for Computational Engineering, Cambridge, Massachusetts, United States
Get access

Abstract

Amyloid fibrils aggregation is a key pathological feature of many severe degenerative disorders including Alzheimer’s disease and clinical dementia. Moreover, amyloids have been classified as intriguing molecules due to their exceptional strength, sturdiness and elasticity. However, physical models that explain the structural basis of these properties remain largely elusive, preventing the description of the link between their hierarchical structure and physical properties. Here we present an atomistic-based multiscale analysis based on computational materiomics, utilized to predict the structure of the two known polymorphous Alzheimer’s Aβ(1–40) amyloid fibers. We report an analysis of the energies, structural changes and H-bonding for varying amyloid fibril lengths, elucidating their size dependent properties. We also propose an explanation for the different stability of the two morphologies. A structural model of amyloid fibers with lengths of hundreds of nanometers at atomistic resolution is obtained. It predicts the formation of twisted amyloid microfibers in close agreement with experimental results. The approach used here provides a link between the fibril geometry, the chemical interactions and the most stable configuration, and resolves the issue of missing atomistic structures for long amyloid fibers.

Type
Research Article
Copyright
Copyright © Materials Research Society 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1 Knowles, T. P. et al. , Science 318, 1900 (2007).Google Scholar
2 Mesquida, P. Riener, C. K. MacPhee, C. E. McKendry, R. A. J Mater Sci Mater Med 18, 1325 (2007).Google Scholar
3 Petkova, A. T. et al. , PNAS 99, 16742 (2002).Google Scholar
4 Jaroniec, C. P. MacPhee, C. E. Astrof, N. S. Dobson, C. M. Griffin, R. G. PNAS 99, 16748 (2004).Google Scholar
5 Paravastu, A. Leapman, R. D. Yau, W. W. M., Tycko, R. PNAS 105, 18349 (2008).Google Scholar
6 Nelson, R. and Sawaya, M.R. and Balbirnie, M. and Madsen, A.O. and Riekel, C. and Grothe, R. and Eisenberg, D. Nature 435, 773 (2005).Google Scholar
7 Tycko, R. Biochemistry 42, 3151 (2003).Google Scholar
8 Paparcone, R. Buehler, M. J. Appl. Phys. Lett. 94, 243904 (2009).Google Scholar
9 Paparcone, R. Sanchez, J. Buehler, M. J. Journal of Computational and Theoretical Nanoscien Nanoscience (in press press).Google Scholar
10 Lazaridis, T. Karplus, M. Proteins-Structure Function And Genetics 35, 133 (May, 1999).Google Scholar
11 Brooks, B. R. et al. , J. Comp. Chem. 4, 187 (1983).Google Scholar
12 Periole, X. Rampioni, A. Vendruscolo, M. Mark, A. E. J. Phys. Chem. B113, 1728, (2009).Google Scholar
13 Chothia, C. J. Mol. Biol. 75, 295 (1973).Google Scholar
14 Salemme, F. R. Prog. Biophys. Mol. Biol. 42, 95 (1983).Google Scholar
15 Maccallum, P. H. Poet, R. Milnerwhite, E. J. J. Mol. Biol. 248, 374 (1995).Google Scholar
16 Chou, K. C. Nemethy, G. Scheraga, H. A. J. Mol. Biol. 168, 389 (1983a).Google Scholar
17 Yang, A. S. Honig, B. J. Mol. Biol. 252, 366 (1995).Google Scholar
18 Paparcone, R. Keten, S. Buehler, M. J. Journal of Biomechanics Biomechanics, DOI:10.1016/j.jbiomech.2009.11.026 (2010).Google Scholar