期刊
出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.2120346119
关键词
peptide assemblies; helical polymers; three-dimensional reconstruction
资金
- French Infrastructure for Integrated Structural Biology [ANR-10-INSB-05-01]
- NIH [GM122510, K99GM138756]
Functional nano- and microassemblies formed by biological molecules can be found at all levels of life, with Lanreotide being one of the best characterized synthetic peptides forming well-defined nanostructures. The atomic structure of Lanreotide nanotubes, determined through cryoelectron microscopy, revealed surprising differences compared to the molecular model. This work highlights the challenge of predicting higher-order assemblies formed by even well-characterized small peptides.
Functional and versatile nano- and microassemblies formed by biological molecules are found at all levels of life, from cell organelles to full organisms. Understanding the chemical and physicochemical determinants guiding the formation of these assemblies is crucial not only to understand the biological processes they carry out but also to mimic nature. Among the synthetic peptides forming welldefined nanostructures, the octapeptide Lanreotide has been considered one of the best characterized, in terms of both the atomic structure and its self-assembly process. In the present work, we determined the atomic structure of Lanreotide nanotubes at 2.5-angstrom resolution by cryoelectron microscopy (cryo-EM). Surprisingly, the asymmetric unit in the nanotube contains eight copies of the peptide, forming two tetramers. There are thus eight different environments for the peptide, and eight different conformations in the nanotube. The structure built from the cryo-EM map is strikingly different from the molecular model, largely based on X-ray fiber diffraction, proposed 20 y ago. Comparison of the nanotube with a crystal structure at 0.83-angstrom resolution of a Lanreotide derivative highlights the polymorphism for this peptide family. This work shows once again that higher-order assemblies formed by even well-characterized small peptides are very difficult to predict.
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