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Deciphering the Rules for Amino Acid Co-Assembly Based on Interlayer Distances
- Source :
- ACS Nano
- Publication Year :
- 2019
- Publisher :
- American Chemical Society (ACS), 2019.
-
Abstract
- Metabolite materials are extremely useful to obtain functional bioinspired assemblies with unique physical properties for various applications in the fields of material science, engineering, and medicine by self-assembly of the simplest biological building blocks. Supramolecular co-assembly has recently emerged as a promising extended approach to further expand the conformational space of metabolite assemblies in terms of structural and functional complexity. Yet, the design of synergistically co-assembled amino acids to produce tailor-made functional architectures is still challenging. Herein, we propose a design rule to predict the supramolecular co-assembly of naturally occurring amino acids based on their interlayer separation distances observed in single crystals. Using diverse experimental techniques, we demonstrate that amino acids with comparable interlayer separation strongly interact and co-assemble to produce structural composites distinctly different from their individual properties. However, such an interaction is hampered in a mixture of differentially layer-separated amino acids, which self-sort to generate individual characteristic structures. This study provides a different paradigm for the modular design of supramolecular assemblies based on amino acids with predictable properties.
- Subjects :
- chemistry.chemical_classification
Metabolite
General Engineering
Supramolecular chemistry
General Physics and Astronomy
02 engineering and technology
Molecular Dynamics Simulation
010402 general chemistry
021001 nanoscience & nanotechnology
01 natural sciences
Combinatorial chemistry
Mass Spectrometry
Nanostructures
3. Good health
0104 chemical sciences
Amino acid
chemistry.chemical_compound
chemistry
Microscopy, Electron, Scanning
General Materials Science
Co assembly
Amino Acids
Peptides
0210 nano-technology
Subjects
Details
- ISSN :
- 1936086X and 19360851
- Database :
- OpenAIRE
- Journal :
- ACS Nano
- Accession number :
- edsair.doi.dedup.....3e4a34165fde9a75dc683b1c16b0652e
- Full Text :
- https://doi.org/10.1021/acsnano.8b07775