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Computational de novo design of a self-assembling peptide with predefined structure
journal contribution
posted on 2023-06-09, 00:13 authored by Sabine Kaltofen, Chenge Li, Po-Ssu Huang, Louise SerpellLouise Serpell, Andreas Barth, Ingemar AndréProtein and peptide self-assembly is a powerful design principle for engineering of new biomolecules. More sophisticated biomaterials could be built if both the structure of the overall assembly and that of the self-assembling building block could be controlled. To approach this problem, we developed a computational design protocol to enable de novo design of self-assembling peptides with predefined structure. The protocol was used to design a peptide building block with a ßaß fold that self-assembles into fibrillar structures. The peptide associates into a double ß-sheet structure with tightly packed a-helices decorating the exterior of the fibrils. Using circular dichroism, Fourier transform infrared spectroscopy, electron microscopy and X-ray fiber diffraction, we demonstrate that the peptide adopts the designed conformation. The results demonstrate that computational protein design can be used to engineer protein and peptide assemblies with predefined three-dimensional structures, which can serve as scaffolds for the development of functional biomaterials. Rationally designed proteins and peptides could also be used to investigate the subtle energetic and entropic tradeoffs in natural self-assembly processes and the relation between assembly structure and assembly mechanism. We demonstrate that the de novo designed peptide self-assembles with a mechanism that is more complicated than expected, in a process where small changes in solution conditions can lead to significant differences in assembly properties and conformation. These results highlight that formation of structured protein/peptide assemblies is often dependent on the formation of weak but highly precise intermolecular interactions.
History
Publication status
- Published
Journal
Journal of Molecular BiologyISSN
0022-2836Publisher
ElsevierExternal DOI
Issue
2Volume
427Page range
550-562Department affiliated with
- Biochemistry Publications
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- No
Peer reviewed?
- Yes
Legacy Posted Date
2016-02-05Usage metrics
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