A genetic approach for controlling the binding and orientation of proteins on nanoparticles.

Although silver nanoparticles are excellent surface enhancers for Raman spectroscopy, their use to probe the conformation of large proteins at interfaces has been complicated by the fact that many polypeptides adsorb weakly or with a random orientation to colloidal silver. To address these limitations, we sought to increase binding affinity and control protein orientation by fusing a silver-binding dodecapeptide termed Ag4 to the C-terminus of maltose-binding protein (MBP), a well-characterized model protein with little intrinsic silver binding affinity. Quartz crystal microbalance measurements conducted with the MBP-Ag4 fusion protein revealed that its affinity for silver (Kd approximately 180 nM) was at least 1 order of magnitude higher than a control protein, MBP2, containing a non-silver-specific C-terminal extension. Under our experimental conditions, MBP-Ag4 SERS spectra exhibited 2-4 fold higher signal-to-background relative to MPB2 and contained a number of amino acid-assigned vibrational modes that were either weak or absent in control experiments performed with MBP2. Changes in amino acid-assigned peaks before and after MBP-Ag4 bound maltose were used to assess protein orientation on the surface of silver nanoparticles. The genetic route described here may prove useful to study the orientation of other proteins on a variety of SERS-active surfaces, to improve biosensors performance, and to control functional nanobiomaterials assembly.

Conformational control of inorganic adhesion in a designer protein engineered for cuprous oxide binding.

Combinatorial selection of peptides that bind technological materials has emerged as a valuable tool for room-temperature nucleation and assembly of complex nanostructured materials. At present, the parameters that control peptide-solid binding are poorly understood, but such knowledge is needed to build the next generation of hybrid materials. Here, we use a derivative of the DNA binding protein TraI engineered with a disulfide-bonded cuprous oxide binding sequence called CN225 to probe the influence of sequence composition and conformation on Cu2O binding affinity. We previously reported a statistically significant enrichment in paired arginines (RR) among a family of cuprous oxide binding peptides and hypothesized that this is a key motif for binding. However, systematic alanine (A) substitutions in the CN225 RR motif (creating RA, AR, and AA pairs) do not support the hypothesis that RR is critical for Cu2O binding by CN225. Instead, we find that the presentation of the peptide in a disulfide-constrained loop (i.e., the conformation present during combinatorial selection) is crucial for binding to the metal oxide. Our results suggest that caution should be exerted when extrapolating from statistical data and that, in some cases, conformation is more important than composition in determining peptide-inorganic adhesion.

Nonequilibrium synthesis and assembly of hybrid inorganic-protein nanostructures using an engineered DNA binding protein.

We show that a protein with no intrinsic inorganic synthesis activity can be endowed with the ability to control the formation of inorganic nanostructures under thermodynamically unfavorable (nonequilibrium) conditions, reproducing a key feature of biological hard-tissue growth and assembly. The nonequilibrium synthesis of Cu(2)O nanoparticles is accomplished using an engineered derivative of the DNA-binding protein TraI in a room-temperature precursor electrolyte. The functional TraI derivative (TraIi1753::CN225) is engineered to possess a cysteine-constrained 12-residue Cu(2)O binding sequence, designated CN225, that is inserted into a permissive site in TraI. When TraIi1753::CN225 is included in the precursor electrolyte, stable Cu(2)O nanoparticles form, even though the concentrations of [Cu(+)] and [OH(-)] are at 5% of the solubility product (K(sp,Cu2O)). Negative control experiments verify that Cu(2)O formation is controlled by inclusion of the CN225 binding sequence. Transmission electron microscopy and electron diffraction reveal a core-shell structure for the nonequilibrium nanoparticles: a 2 nm Cu(2)O core is surrounded by an adsorbed protein shell. Quantitative protein adsorption studies show that the unexpected stability of Cu(2)O is imparted by the nanomolar surface binding affinity of TraIi1753::CN225 for Cu(2)O (K(d) = 1.2 x 10(-)(8) M), which provides favorable interfacial energetics (-45 kJ/mol) for the core-shell configuration. The protein shell retains the DNA-binding traits of TraI, as evidenced by the spontaneous organization of nanoparticles onto circular double-stranded DNA.

Identification and characterization of Cu(2)O- and ZnO-binding polypeptides by Escherichia coli cell surface display: toward an understanding of metal oxide binding.

We have used the FliTrx cell surface display system to identify disulfide-constrained dodecapeptides binding to the semiconducting metal oxides Cu(2)O and ZnO. Sequence analysis of the inserts revealed that the two populations exhibit similar, yet subtly different patterns of amino acid usage. Both sets of binders were enriched in arginine, tryptophan, and glycine with a higher degree of positional preference in the case of Cu(2)O binders. Tyrosine, proline, and serine were underrepresented in both populations. Peptides binding electrodeposited Cu(2)O or ZnO with high avidity could be subdivided into two classes based on pI and hydrophilicity. In the hydrophilic and positively charged Class I binders, the Arg-X-X-Arg tetrapeptide appears to be implicated in metal oxide binding, whereas Arg-Arg and Arg-Lys pairs allow for discrimination between Cu(2)O and ZnO. Molecular dynamics simulations of the disulfide-constrained peptides suggest that the aforementioned motifs are important to properly orient two basic residues that are likely to contact the metal oxides. The implications of our results in understanding the rules governing the interaction between peptides and inorganic compounds and in their use for the design of hybrid nanoarchitectures are discussed.