Zhifeng Kuang

Preferential Binding of Peptides to Graphene Edges and Planes

Peptides identified from combinatorial peptide libraries have been shown to bind to a variety of abiotic surfaces. Biotic-abiotic interactions can be exploited to create hybrid materials with interesting electronic, optical, or catalytic properties. Here we show that peptides identified from a combinatorial phage display peptide library assemble preferentially to the edge or planar surface of graphene and can affect the electronic properties of graphene. Molecular dynamics simulations and experiments provide insight into the mechanism of peptide binding to the graphene edge.

Biomimetic Chemosensor: Designing Peptide Recognition Elements for Surface Functionalization of Carbon Nanotube Field Effect Transistors

Single-wall carbon nanotube field effect transistors (SWNT-FETs) are ideal candidates for fabricating sensors due to their unique electronic properties and have been widely investigated for chemical and biological sensing applications. The lack of selectivity of SWNT-FETs has prompted extensive research on developing ligands that exhibit specific binding as selective surface coating for SWNTs. Herein we describe the rational design of a peptide recognition element (PRE) that is capable of noncovalently attaching to SWNTs as well as binding to trinitrotoluene (TNT). The PRE contains two domains, a TNT binding domain derived from the binding pocket of the honeybee odor binding protein ASP1, and a SWNT binding domain previously identified from the phage peptide display library. The PRE structure in the presence of SWNT was investigated by performing classical all-atom molecular dynamics simulations, circular dichroism spectroscopy, and atomic force microscopy. Both computational and experimental analyses demonstrate that the peptide retains two functional domains for SWNT and TNT binding. The binding motif of the peptide to SWNT and to TNT was revealed from interaction energy calculations by molecular dynamics simulations. The potential application of the peptide for the detection of TNT is theoretically predicted and experimentally validated using a SWNT-FET sensor functionalized with a designer PRE. Results from this study demonstrate the creation of chemosensors using designed PRE as selective surface coatings for targeted analytes.

Structure of a Peptide Adsorbed on Graphene and Graphite

Noncovalent functionalization of graphene using peptides is a promising method for producing novel sensors with high sensitivity and selectivity. Here we perform atomic force microscopy, Raman spectroscopy, infrared spectroscopy, and molecular dynamics simulations to investigate peptide-binding behavior to graphene and graphite. We studied a dodecamer peptide identified with phage display to possess affinity for graphite. Optical spectroscopy reveals that the peptide forms secondary structures both in powder form and in an aqueous medium. The dominant structure in the powder form is α-helix, which undergoes a transition to a distorted helical structure in aqueous solution. The peptide forms a complex reticular structure upon adsorption on graphene and graphite, having a helical conformation different from α-helix due to its interaction with the surface. Our observation is consistent with our molecular dynamics calculations, and our study paves the way for rational functionalization of graphene using biomolecules with defined structures and, therefore, functionalities.

Enrichment of (6,5) Single Wall Carbon Nanotubes Using Genomic DNA

Single wall carbon nanotubes (SWNTs) have attracted attention because of their potential in a vast range of applications, including transistors and sensors. However, immense technological importance lies in enhancing the purity and homogeneity of SWNTs with respect to their chirality for real-world electronic applications. In order to achieve optimal performance of SWNTs, the diameter, type, and chirality have to be effectively sorted. Any employed strategy for sorting SWNTs has to be scalable, nondestructible, and economical. In this paper, we present a solubilization and chirality enrichment study of commercially available SWNTs using genomic DNA. On the basis of the comparison of the photoluminescence (PL) and near-infrared absorption measurements from the SWNTs dispersed with salmon genomic DNA (SaDNA) and d(GT)20, we show that genomic DNA specifically enriches (6,5) tubes. Circular dichroism and classical all-atom molecular dynamics simulations reveal that the genomic double-stranded SaDNA prefers to interact with (6,5) SWNTs as compared to (10,3) tubes, meanwhile single-stranded d(GT)20 shows no or minimal chirality preference. Our enrichment process demonstrates enrichment of >86% of (6,5) SWNTs from CoMoCat nanotubes using SaDNA.

Poly(2-hydroxyethyl methacrylate) for enzyme immobilization: impact on activity and stability of horseradish peroxidase.

On the basis of their versatile structure and chemistry as well as tunable mechanical properties, polymer brushes are well-suited as supports for enzyme immobilization. However, a robust surface design is hindered by an inadequate understanding of the impact on activity from the coupling motif and enzyme distribution within the brush. Herein, horseradish peroxidase C (HRP C, 44 kDa), chosen as a model enzyme, was immobilized covalently through its lysine residues on a N-hydroxysuccinimidyl carbonate-activated poly(2-hydroxyethyl methacrylate) (PHEMA) brush grafted chemically onto a flat impenetrable surface. Up to a monolayer coverage of HRP C is achieved, where most of the HRP C resides at or near the brush-air interface. Molecular modeling shows that lysines 232 and 241 are the most probable binding sites, leading to an orientation of the immobilized HRP C that does not block the active pocket of the enzyme. Michaelis-Menten kinetics of the immobilized HRP C indicated little change in the K(m) (Michaelis constant) but a large decrease in the V(max) (maximum substrate conversion rate) and a correspondingly large decrease in the k(cat) (overall catalytic rate). This indicates a loss in the percentage of active enzymes. Given the relatively ideal geometry of the HRPC-PHEMA brush, the loss of activity is most likely due to structural changes in the enzyme arising from either secondary constraints imposed by the connectivity of the N-hydroxysuccinimidyl carbonate linking moiety or nonspecific interactions between HRP C and DSC-PHEMA. Therefore, a general enzyme-brush coupling motif must optimize reactive group density to balance binding with neutrality of surroundings.

Stability of peptide (P1 and P2) binding to a graphene sheet via an all-atom to all-residue coarse-grained approach

Peptide binding to a graphene sheet is studied by a coarse-grained approach. All-atom molecular dynamics (MD) is used to assess the adsorption energy (e.g. binding) of each amino acid with graphene. The relative adsorption energy of each residue is normalized to describe its coarse-grained interactions with graphene which is used as an input to a phenomenological interaction in an all-residue coarse-grained (ARCG) representation of the peptide chain. Large scale Monte Carlo (MC) simulations are performed to study the stability of peptides (P1: 1H–2S–3S–4Y–5W–6Y–7A–8F–9N–10N–11K–12T and P2: 1E–2P–3L–4Q–5L–6K–7M) binding to a graphene sheet as a function of temperature. A number of local and global physical quantities are analyzed including mobility and substrate-in-contact profiles of each residue, density profiles, root mean square displacement of the center of mass of each peptide and its radius of gyration. We find that P1 has a higher probability of binding to a graphene sheet than P2 supported by both local and global physical quantities. All residues of P1 can bind to the graphene sheet at low temperatures; however, three residues 4Y–5W–6Y seem to anchor it most strongly at higher temperatures, which is consistent with an all-atom MD simulation.

Biotic-Abiotic Interactions: Factors that Influence Peptide-Graphene Interactions.

Understanding the factors that influence the interaction between biomolecules and abiotic surfaces is of utmost interest in biosensing and biomedical research. Through phage display technology, several peptides have been identified as specific binders to abiotic material surfaces, such as gold, graphene, silver, and so forth. Using graphene-peptide as our model abiotic-biotic pair, we investigate the effect of graphene quality, number of layers, and the underlying support substrate effect on graphene-peptide interactions using both experiments and computation. Our results indicate that graphene quality plays a significant role in graphene-peptide interactions. The graphene-biomolecule interaction appears to show no significant dependency on the number of graphene layers or the underlying support substrate.

A hierarchical coarse-grained (all-atom-to-all-residue) computer simulation approach: self-assembly of peptides.

A hierarchical computational approach (all-atom residue to all-residue peptide) is introduced to study self-organizing structures of peptides as a function of temperature. A simulated residue-residue interaction involving all-atom description, analogous to knowledge-based analysis (with different input), is used as an input to a phenomenological coarse-grained interaction for large scales computer simulations. A set of short peptides P1 (1H 2S 3S 4Y 5W 6Y 7A 8F 9N 10N 11K 12T) is considered as an example to illustrate the utility. We find that peptides assemble rather fast into globular aggregates at low temperatures and disperse as random-coil at high temperatures. The specificity of the mass distribution of the self-assembly depends on the temperature and spatial lengths which are identified from the scaling of the structure factor. Analysis of energy and mobility profiles, gyration radius of peptide, and radial distribution function of the assembly provide insight into the multi-scale (intra- and inter-chain) characteristics. Thermal response of the global assembly with the simulated residue-residue interaction is consistent with that of the knowledge-based analysis despite expected quantitative differences.

Binding of solvated peptide (EPLQLKM) with a graphene sheet via simulated coarse-grained approach.

Binding of a solvated peptide A1 ((1)E (2)P (3)L (4)Q (5)L (6)K (7)M) with a graphene sheet is studied by a coarse-grained computer simulation involving input from three independent simulated interaction potentials in hierarchy. A number of local and global physical quantities such as energy, mobility, and binding profiles and radius of gyration of peptides are examined as a function of temperature (T). Quantitative differences (e.g., the extent of binding within a temperature range) and qualitative similarities are observed in results from three simulated potentials. Differences in variations of both local and global physical quantities suggest a need for such analysis with multiple inputs in assessing the reliability of both quantitative and qualitative observations. While all three potentials indicate binding at low T and unbinding at high T, the extent of binding of peptide with the temperature differs. Unlike un-solvated peptides (with little variation in binding among residues), solvation accentuates the differences in residue binding. As a result the binding of solvated peptide at low temperatures is found to be anchored by three residues, (1)E, (4)Q, and (6)K (different from that with the un-solvated peptide). Binding to unbinding transition can be described by the variation of the transverse (with respect to graphene sheet) component of the radius of gyration of the peptide (a potential order parameter) as a function of temperature.

Peptide interactions with zigzag edges in graphene

Recognition and manipulation of graphene edges enable the control of physical properties of graphene-based devices. Recently, the authors have identified a peptide that preferentially binds to graphene edges from a combinatorial peptide library. In this study, the authors examine the functional basis for the edge binding peptide using experimental and computational methods. The effect of amino acid substitution, sequence context, and solution pH value on the binding of the peptide to graphene has been investigated. The N-terminus glutamic acid residue plays a key role in recognizing and binding to graphene edges. The protonation, substitution, and positional context of the glutamic acid residue impact graphene edge-binding. Our findings provide insights into the binding mechanisms and the design of peptides for recognizing and functionalizing graphene edges.