Computational Design of Virus-like Protein Assemblies on Carbon Nanotube Surfaces

By Gevorg Grigoryan, Yong Ho Kim, Rudresh Acharya, K. Axelrod, Rishabh M. Jain, L. Willis, M. Drndić, J. Kikkawa, William F. DeGrado. 2011

206 citations recorded by the source corpus.

Proteins are designed to bind to specific surfaces while also presenting a programmed surface superstructure. 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.

Subfields: Biomedical Engineering, Ecology, Materials Chemistry

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Citations in the corpus

Protein sequence design with a learned potential (2022, background): “omputational protein design has emerged as a powerful tool for rational protein design, enabling signi ﬁ cant achievements in the engineering of therapeutics 1 – 3 , 4 – 6 , enzymes 7,8 , and more 9 – 11 .”
Protein sequence design with a learned potential (2020, background): “These advances have led to significant achievements in the engineering of therapeutics [13, 14, 15], biosensors [16, 17, 18], enzymes [19, 20, 21, 22], and more [23, 24, 25, 26, 27].”
Computational design of a protein crystal (2012, methodology): “Related hierarchical strategies have been employed to design proteins and their higher order assemblies (34, 35).”
De novo protein design, a retrospective (2020, methodology): “Finally, by redesigning the hydrophobic core of the hexameric bundles, Grigoryan et al. engineered bundles that selectively solubilized only a single form of carbon nanotubes (Grigoryan et al., 2011).”
Tertiary alphabet for the observable protein structural universe (2016, background): “In general, the discovery of modularity at the contiguous-backbone level, with emergent sequence/structure statistics, has laid some of the foundation for modern structure prediction and protein design methods (2, 26, 27, 37 – 41).”
The coming of age of de novo protein design (2016, background): “4), including a peptide that binds to carbon nano-tubes 53 , parallel self-assembling helical channels 31 , an ion transporter 34 , cages 54 and an α-helical barrel with installed hydrolytic activity 55 .”
Achievements and Challenges in Computational Protein Design. (2017, methodology): “In 2011 the DeGrado lab applied CPD to design virus-like protein assemblies on carbon nanotube surfaces [85].”