To understand how molecular interactions lead to the self-assembly of twisted, helical and flat nanoribbons, we have compared the hierarchical self-assembly processes of three selected octapeptides with the same amino acid composition but different sequences by both experiments and molecular dynamics (MD) simulations. KE-F8 (NH2-KEFFFFKE-CONH2) and EK-F8 (NH2-KEFFFFEK-CONH2) have the same distribution of hydrophobic residues and only differ by swapping the positive and negative charged residues at their C-terminals, while KFE-8 (NH2-KFEFKFEF-CONH2) differs from KE-F8 and EK-F8 by having all hydrophobic and charged residues evenly distributed. MD simulations indicated that the competition between electrostatic and hydrophobic interactions at the molecular level results in different initial packing modes: KE-F8 monomers form completely matched anti-parallel β-sheets, EK-F8 monomers align with one residue shifting, and KFE-8 monomers pack β-sheets with two heterogeneous surfaces, consistent with previously suggested models. Driven by inter-strand and inter-sheet interactions, further growth of these molecular templates leads to larger oligomers with different twisting and stacking degrees, which are structurally consistent with the experimentally observed self-assembled morphologies. Further MD simulations showed that the competition between intra-β-sheet and inter-β-sheet interactions is responsible for the different twisting and stacking degrees of β-sheets and the subsequent formation of different nanostructures (twisted ribbons for KE-F8, helical ribbons/tubes for EK-F8 and flat ribbons for KFE-8). This study thus provided an important mechanistic insight into the fine tuning of molecular packing and interactions via peptide sequence variation leading to controllable self-assembly of twisted, helical and flat nanostructures.
Pharmacology, Toxicology and Pharmaceutical Science
2
4%
Other
6
11%
Unknown
14
25%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 March 2021.
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#12,343,160
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Outputs from Journal of Colloid & Interface Science
#2,854
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#118,877
of 318,453 outputs
Outputs of similar age from Journal of Colloid & Interface Science
#13
of 81 outputs
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