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Protein Design

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Attention for Chapter 3: Combination of theoretical and experimental approaches for the design and study of fibril-forming peptides.
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Chapter title
Combination of theoretical and experimental approaches for the design and study of fibril-forming peptides.
Chapter number 3
Book title
Protein Design
Published in
Methods in molecular biology, January 2014
DOI 10.1007/978-1-4939-1486-9_3
Pubmed ID
Book ISBNs
978-1-4939-1485-2, 978-1-4939-1486-9
Authors

Phanourios Tamamis, Emmanouil Kasotakis, Georgios Archontis, Anna Mitraki

Abstract

Self-assembling peptides that can form supramolecular structures such as fibrils, ribbons, and nanotubes are of particular interest to modern bionanotechnology and materials science. Their ability to form biocompatible nanostructures under mild conditions through non-covalent interactions offers a big biofabrication advantage. Structural motifs extracted from natural proteins are an important source of inspiration for the rational design of such peptides. Examples include designer self-assembling peptides that correspond to natural coiled-coil motifs, amyloid-forming proteins, and natural fibrous proteins. In this chapter, we focus on the exploitation of structural information from beta-structured natural fibers. We review a case study of short peptides that correspond to sequences from the adenovirus fiber shaft. We describe both theoretical methods for the study of their self-assembly potential and basic experimental protocols for the assessment of fibril-forming assembly.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 18%
Student > Master 2 18%
Researcher 2 18%
Professor > Associate Professor 1 9%
Student > Postgraduate 1 9%
Other 0 0%
Unknown 3 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 27%
Materials Science 2 18%
Agricultural and Biological Sciences 1 9%
Engineering 1 9%
Unknown 4 36%