Controlling Association and Separation of Gold Nanoparticles with Computationally Designed Zinc-Coordinating Proteins.

Functionalization of nanoparticles with biopolymers has yielded a wide range of structured and responsive hybrid materials. DNA provides the ability to program length and recognition using complementary oligonucleotide sequences. Nature more often leverages the versatility of proteins, however, where structure, assembly, and recognition are more subtle to engineer. Herein, a protein was computationally designed to present multiple Zn2+ coordination sites and cooperatively self-associate to form an antiparallel helical homodimer. Each subunit was unstructured in the absence of Zn2+ or when the cation was sequestered with a chelating agent. When bound to the surface of gold nanoparticles via cysteine, the protein provided a reversible molecular linkage between particles. Nanoparticle association and changes in interparticle separation were monitored by redshifts in the surface plasmon resonance (SPR) band and by transmission electron microscopy (TEM). Titrations with Zn2+ revealed sigmoidal transitions at submicromolar concentrations. The metal-ion concentration required to trigger association varied with the loading of the proteins on the nanoparticles, the solution ionic strength, and the cation employed. Specifying the number of helical (heptad) repeat units conferred control over protein length and nanoparticle separation. Two different length proteins were designed via extension of the helical structure. TEM and extinction measurements revealed distributions of nanoparticle separations consistent with the expected protein structures. Nanoparticle association, interparticle separation, and SPR properties can be tuned using computationally designed proteins, where protein structure, folding, length, and response to molecular species such as Zn2+ can be engineered.

Photoinduced Electron Transfer Elicits a Change in the Static Dielectric Constant of a de Novo Designed Protein.

We provide a direct measure of the change in effective dielectric constant (ε(S)) within a protein matrix after a photoinduced electron transfer (ET) reaction. A linked donor-bridge-acceptor molecule, PZn-Ph-NDI, consisting of a (porphinato)Zn donor (PZn), a phenyl bridge (Ph), and a naphthalene diimide acceptor (NDI), is shown to be a "meter" to indicate protein dielectric environment. We calibrated PZn-Ph-NDI ET dynamics as a function of solvent dielectric, and computationally de novo designed a protein SCPZnI3 to bind PZn-Ph-NDI in its interior. Mapping the protein ET dynamics onto the calibrated ET catalogue shows that SCPZnI3 undergoes a switch in the effective dielectric constant following photoinduced ET, from ε(S) ≈ 8 to ε(S) ≈ 3.

Computational design of a protein crystal.

Protein crystals have catalytic and materials applications and are central to efforts in structural biology and therapeutic development. Designing predetermined crystal structures can be subtle given the complexity of proteins and the noncovalent interactions that govern crystallization. De novo protein design provides an approach to engineer highly complex nanoscale molecular structures, and often the positions of atoms can be programmed with sub-Å precision. Herein, a computational approach is presented for the design of proteins that self-assemble in three dimensions to yield macroscopic crystals. A three-helix coiled-coil protein is designed de novo to form a polar, layered, three-dimensional crystal having the P6 space group, which has a "honeycomb-like" structure and hexameric channels that span the crystal. The approach involves: (i) creating an ensemble of crystalline structures consistent with the targeted symmetry; (ii) characterizing this ensemble to identify "designable" structures from minima in the sequence-structure energy landscape and designing sequences for these structures; (iii) experimentally characterizing candidate proteins. A 2.1 Å resolution X-ray crystal structure of one such designed protein exhibits sub-Å agreement [backbone root mean square deviation (rmsd)] with the computational model of the crystal. This approach to crystal design has potential applications to the de novo design of nanostructured materials and to the modification of natural proteins to facilitate X-ray crystallographic analysis.

Observing Changes in the Structure and Oligomerization State of a Helical Protein Dimer Using Solid-State Nanopores.

Protein analysis using solid-state nanopores is challenging due to limitations in bandwidth and signal-to-noise ratio. Recent improvements of those two aspects have made feasible the study of small peptides using solid-state nanopores, which have an advantage over biological counterparts in tunability of the pore diameter. Here, we report on the detection and characterization of peptides as small as 33 amino acids. Silicon nitride nanopores with thicknesses less than 10 nm are used to provide signal-to-noise (S/N) levels up to S/N ∼ 10 at 100 kHz. We demonstrate differentiation of monomer and dimer forms of the GCN4-p1 leucine zipper, a coiled-coil structure well studied in molecular biology, and compare with the unstructured 33-residue monomer. GCN4-p1 is sequence segment associated with homodimerization of the transcription factor General Control Nonderepressible 4 (GCN4), which is involved in the control of amino acid synthesis in yeast. The differentiation between two oligomeric forms demonstrates the capabilities of improved solid-state nanopore platforms to extract structural information involving short peptide structures.