Computational design of virus-like protein assemblies on carbon nanotube surfaces

Abstract

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.

Figure 1

A) A simplified diagram of the surface assembly process(35). The design goal is to achieve ordered arrays of peptide subunits on the target surface (global order; top outcome in figure) and to avoid kinetic traps of surface binding (local order; bottom outcome), which can be caused by overly strong interactions between individual subunits and the surface. B)-D) illustrate the general design framework on the example of decorating a graphene sheet. B) Selection rule 1: C_β methyl group of Ala and the α-helix are picked as the surface-contacting functional group and structural unit, respectively. C) Selection rule 2: two possible unit cells, a single helix and an antiparallel dimer, are shown along with the corresponding Bravais-lattice vectors defining unit-cell images. D) Assemblies containing undesignable interfaces are discarded in selection rule 3 (differences in designability are usually much more subtle than illustrated here for clarity). E) Optimal template geometry designed to target the surface of an (3,8) SWNT surface (helical pattern of the SWNT shown with black benzenoid rings).

Figure 2

Designability analysis in selection rule 3. The two unique interfaces of an antiparallel homo-hexamer are designated here as AA′ and A′A and illustrated in the left and right columns, respectively. A) Number of matches as a function of the C_α RMSD cutoff. B) Structural variation in the top 100 best matches. Tube thickness equals to the mean square deviation of the corresponding atom within the ensemble of top 100 matches. Blue to red indicates the N-to-C terminal direction. C) Sequence logo diagrams for the two interfaces of the (3,8)-targeted template derived from unique matches with C_α RMSD below 0.5 Å and 0.6 Å for AA′ and A′A, respectively(36). Heptad assignments, in the context of the full hexamer, are indicated for each sequence position.

Figure 3

A) Sequences of designed peptides, native DSD and control peptides. B) Crystal structure of HexCoil-Ala (left; asymmetric unit; mesh represents electron density contoured at 1.5σ; see Table S3) and its comparison to the asymmetric unit of the designed oligomer (right; gray structures corresponds to the design). C) The Ala-rich surface of the asymmetric unit of the HexCoil-Ala crystal structure is well poised to interact with a SWNT. D) Model structure of HexCoil-Gly with a (3,8) SWNT. Blue-to-red indicates N-to-C terminal direction. E) Crystal structure of native DSD. F) Model of DSD-Ala with a (3,8) SWNT. Van der Waals surfaces are shown semi-transparently in C), D), E), and F).

Figure 4

2D-PL and TEM analysis of SWNT/peptide complexes. A)-B) 2D-PL spectra of SWNT suspensions produced by A) DSD-based peptides and B) de novo designed peptides (pseudocolor scale is internally consistent within each section). C) Fitting photoluminescence maps to a sum of 2-dimensional Lorentzians provides the total intensity weight contribution of each SWNT species, I. Shown are relative contributions of the three SWNT types with the strongest signals (e.g. (3,8), (5,6) and (5,7)) in suspensions produced by four peptides and, as reference, the common surfactant sodium deoxy cholate (SDOC; spectrum in Fig. S14). In each case, weights are normalized to the most contributing species. D)-F) and H) show TEM images of gold nanoparticles grown on Cys-modified DSD-Gly hexamers wrapped around individual SWNTs. E) is a higher magnification version of D) and F) contains a high-resolution TEM image. Scale bars are 10 nm in H). G) Computational model of the complex. Gold particles are represented with 30-Å diameter spheres attached to the Cys Sγ atoms of the Cys-modified DSD-Gly.