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Cited by 352

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Exploiting Amyloid Fibril Lamination for Nanotube Self-Assembly

Lu, Kun, Jacob, Jaby, Thiyagarajan, Pappannan, Conticello, Vincent P., Lynn, David G.·2003·Journal of the American Chemical Society

Abstract

Fundamental questions about the relative arrangement of the beta-sheet arrays within amyloid fibrils remain central to both its structure and the mechanism of self-assembly. Recent computational analyses suggested that sheet-to-sheet lamination was limited by the length of the strand. On the basis of this hypothesis, a short seven-residue segment of the Alzheimer's disease-related Abeta peptide, Abeta(16-22), was allowed to self-assemble under conditions that maintained the basic amphiphilic character of Abeta. Indeed, the number increased over 20-fold to 130 laminates, giving homogeneous bilayer structures that supercoil into long robust nanotubes. Small-angle neutron scattering and X-ray scattering defined the outer and inner radii of the nanotubes in solution to contain a 44-nm inner cavity with 4-nm-thick walls. Atomic force microscopy and transmission electron microscopy images further confirmed these homogeneous arrays of solvent-filled nanotubes arising from a flat rectangular bilayer, 130 nm wide x 4 nm thick, with each bilayer leaflet composed of laminated beta-sheets. The corresponding backbone H-bonds are along the long axis, and beta-sheet lamination defines the 130-nm bilayer width. This bilayer coils to give the final nanotube. Such robust and persistent self-assembling nanotubes with positively charged surfaces of very different inner and outer curvature now offer a unique, robust, and easily accessible scaffold for nanotechnology.

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Metadata

Authors
Lu, K., Jacob, J., Thiyagarajan, P., Conticello, V. P., & Lynn, D. G.
Venue
Journal of the American Chemical Society
Published
2003-05-01
Volume
125
Issue
21
Pages
6391-6393
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2091029987
Cited by
352
References
1
FWCI
7.24
Type
journal article
Language
en
Open access
closed

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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