Journal
SCIENCE
Volume 332, Issue 6033, Pages 1071-1076Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.1198841
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Funding
- NSF Materials Research Science and Engineering Center [DMR05-20020]
- NIH [GM54616, 5F32GM084631-02]
- NSF National Science and Engineering Center [DMR-0425780]
- NSF [DMR-0907226, DGE-0221664]
- Roy and Diana Vagelos Program in the Molecular Life Sciences
- Direct For Mathematical & Physical Scien
- Division Of Materials Research [0907266] Funding Source: National Science Foundation
- Division Of Materials Research
- Direct For Mathematical & Physical Scien [1120901] Funding Source: National Science Foundation
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There is a general need for the engineering of protein-like molecules that organize into geometrically specific superstructures on molecular surfaces, directing further functionalization to create richly textured, multilayered assemblies. Here we describe a computational approach whereby the surface properties and symmetry of a targeted surface define the sequence and superstructure of surface-organizing peptides. Computational design proceeds in a series of steps that encode both surface recognition and favorable intersubunit packing interactions. This procedure is exemplified in the design of peptides that assemble into a tubular structure surrounding single-walled carbon nanotubes (SWNTs). The geometrically defined, virus-like coating created by these peptides converts the smooth surfaces of SWNTs into highly textured assemblies with long-scale order, capable of directing the assembly of gold nanoparticles into helical arrays along the SWNT axis.
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