Crystallographic Recognition Controls Peptide Binding for Bio-Based Nanomaterials

Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure-Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. We present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

Sequence rules for gold-binding peptides

Metal-binding peptides play a central role in bionanotechnology, wherein they are responsible for directing growth and influencing the resulting properties of inorganic nanomaterials. One of the key advantages of using peptides to create nanomaterials is their versatility, wherein subtle changes in the sequence can have a dramatic effect on the structure and properties of the nanomaterial. However, precisely knowing which position and which amino acid should be modified within a given sequence to enhance a specific property can be a daunting challenge owing to combinatorial complexity. In this study, classification based on association rules was performed using 860 gold-binding peptides. Using a minimum support threshold of 0.035 and confidence of 0.9, 30 rules with confidence and lift values greater than 0.9 and 1, respectively, were extracted that can differentiate high-binding from low-binding peptides. The test performance of these rules for categorizing the peptides was found to be satisfactory, as characterized by accuracy = 0.942, F₁ = 0.941, MCC = 0.884. What stands out from the extracted rules are the importance of tryptophan and arginine residues in differentiating peptides with high binding affinity from those with low affinity. In addition, the association rules revealed that positions 2 and 4 within a decapeptide are frequently involved in the rules, thus suggesting their importance in influencing peptide binding affinity to AuNPs. Collectively, this study identified sequence rules that may be used to design peptides with high binding affinity.

Achieving regioselective materials binding using multidomain peptides

The ability to integrate two disparate materials-binding domains into a single ligand to achieve regiospecific binding would be powerful to direct material assembly; however, this has proven challenging to achieve due to cross-materials binding. Accomplishing this goal might be achieved by harnessing the precision of biology to exploit the recognition between peptides and specific nanomaterials. Here, a designed bifunctional molecule termed Biomolecular Exfoliant and Assembly Motifs (BEAM) is introduced, featuring two different materials-binding peptide domains, one for graphene and one for hexagonal boron nitride (h-BN), at each end of the molecule, separated by a fatty acid spacer. The BEAM is demonstrated to bind strongly to both graphene and h-BN surfaces, and in each case the materials-binding peptide domain is shown to preferentially bind its target material. Critically, the two materials-binding domains exhibited limited cross-domain interaction. The BEAM design concept shows substantial potential to eventually guide self-organization of a range of materials in aqueous media.

High-Yield 99mTc Labeling of Gold Nanoparticles Carrying Atropine and Adrenaline

This work focuses on the synthesis, purification, and analytical characterization of novel multifunctional Au NPs radiolabeled with ^99mTc. These mixed-ligand shell Au NPs represent pharmacologically relevant samples for potential application in theragnostics. A ligand using a plain linker with a rather long chain consisting of 10 CH₂ groups and a thiol moiety along with the PADA chelator has been used for both the attachment to the Au NP surface and for the ^99mTc(CO)₃⁺ complexation. We have combined this with our approach of stabilizing Au NP without any PEG or other stabilizing groups. Thus, monoligand shell Au NPs were radiolabeled by different strategies (prelabeling and postlabeling). Additionally, pharmacologically relevant Au NPs were synthesized carrying both a biofunctionalization with either atropine or adrenaline and the ^99mTc radiolabel. All samples were obtained in very good yields (up to 80% of the total activity loaded onto the column) and completely/particularly purified using desalting columns. Detailed analytical characterization of the Au NPs before and after radiolabeling has proven the NPs' robustness throughout the process. Their intact functionalization, shape, and stability was confirmed by transmission electron microscopy (TEM), ultraviolet/visible (UV/vis) spectroscopy, dynamic light scattering (DLS), and infrared (IR) spectroscopy. The presented strategy represents a versatile building block system that can be adapted to a variety of bioactive molecules and may be of high relevance for theragnostic applications.

A Machine Learning Classification Model for Gold-Binding Peptides

There has been growing interest in using peptides for the controlled synthesis of nanomaterials. Peptides play a crucial role not only in regulating the nanostructure formation process but also in influencing the resulting properties of the nanomaterials. Leveraging machine learning (ML) in the biomimetic workflow is anticipated to accelerate peptide discovery, make the process more resource-efficient, and unravel associations among attributes that may be useful in peptide design. In this study, a binary ML classifier is formulated that was trained and tested on 1720 peptide examples. The support vector machine classifier uses Kidera factors to categorize peptides into one of two groups based on their binding ability. The classifier exhibits satisfactory performance, as demonstrated by various performance metrics. In addition, key variables that bear a huge impact on the model were identified, such as peptide hydrophobicity. As these trends were derived from a large and diverse dataset, the insights drawn from the data are expected to be generalizable and robust. Thus, the presented ML model is an important step toward the rational and predictive peptide design.

Remote controlled optical manipulation of bimetallic nanoparticle catalysts using peptides

Remote optical manipulation of peptide ligands on bimetallic nanoparticle surfaces allows for tunable catalytic reactivity.

Enhanced Hyperbox Classifier Model for Nanomaterial Discovery

Machine learning tools can be applied to peptide-mediated biomineralization, which is an emerging biomimetic technique of creating functional nanomaterials. In particular, they can be used for the discovery of biomineralization peptides, which currently relies on combinatorial enumeration approaches. In this work, an enhanced hyperbox classifier is developed which can predict if a given peptide sequence has a strong or weak binding affinity towards a gold surface. A mixed-integer linear program is formulated to generate the rule-based classification model. The classifier is optimized to account for false positives and false negatives, and clearly articulates how the classification decision is made. This feature makes the decision-making process transparent, and the results easy to interpret for decision support. The method developed can help accelerate the discovery of more biomineralization peptide sequences, which may expand the utility of peptide-mediated biomineralization as a means for nanomaterial synthesis.

Recombinant peptide fusion construction for protein-templated catalytic palladium nanoparticles

Although peptide-enabled synthesis of nanostructures has garnered considerable interest for use in catalytic applications, it has so far been achieved mostly via Fmoc based solid phase peptide synthesis. Consequently, the potential of longer peptides in nanoparticle synthesis have not been explored largely due to the complexities and economic constraints of this chemical synthesis route. This study examines the potential of a 45-amino acid long peptide expressed as fusion to green fluorescence protein (GFPuv) in Escherichia coli for use in palladium nanoparticle synthesis. Fed-batch fermentation with E. coli harboring an arabinose-inducible plasmid produced a product containing three copies of Pd4 peptide fused to N-terminus of GFPuv ((Pd4)₃ -GFPuv). Using the intrinsic fluorescence of GFPuv, expression and enrichment of the fusion product was easily monitored. Crude lysate, desalted lysate, and an ion-exchange enriched fraction containing (Pd4)₃ -GFPuv were used to test the hypothesis that high purity of the biologic material used as the nanoparticle synthesis template may not be necessary. Nanoparticles were characterized using a variety of material science techniques and used to catalyze a model Suzuki-Miyaura coupling reaction. Results demonstrated that palladium nanoparticles can be synthesized using the soluble cell extract containing (Pd4)₃ -GFPuv without extensive purification or cleavage steps, and as a catalyst the crude mixture is functional.

Nature of peptide wrapping onto metal nanoparticle catalysts and driving forces for size control

Colloidal metal nanocrystals find many applications in catalysis, energy conversion devices, and therapeutics. However, the nature of ligand interactions and implications on shape control have remained uncertain at the atomic scale. Large differences in peptide adsorption strength and facet specificity were found on flat palladium surfaces versus surfaces of nanoparticles of 2 to 3 nm size using accurate atomistic simulations with the Interface force field. Folding of longer peptides across many facets explains the formation of near-spherical particles with local surface disorder, in contrast to the possibility of nanostructures of higher symmetry with shorter ligands. The average particle size in TEM correlates inversely with the surface coverage with a given ligand and with the strength of ligand adsorption. The role of specific amino acids and sequence mutations on the nanoparticle size and facet composition is discussed, as well as the origin of local surface disorder that leads to large differences in catalytic reactivity.

Peptide-templated noble metal catalysts: syntheses and applications

Noble metal catalysts have been widely used in many applications because of their high activity and selectivity. However, a controllable preparation of noble metal catalysts still remains as a significant challenge. To overcome this challenge, peptide templates can play a critical role in the controllable syntheses of catalysts owing to their flexible binding with specific metallic surfaces and self-assembly characteristics. By employing peptide templates, the size, shape, facet, structure, and composition of obtained catalysts can all be specifically controlled under the mild synthesis conditions. In addition, catalysts with spherical, nanofiber, and nanofilm structures can all be produced by associating with the self-assembly characteristics of peptide templates. Furthermore, the peptide-templated noble metal catalysts also reveal significantly enhanced catalytic behaviours compared with conventional catalysts because the electron conductivity, metal dispersion, and reactive site exposure can all be improved. In this review, we summarize the research progresses in the syntheses of peptide-templated noble metal catalysts. The applications of the peptide-templated catalysts in organic reactions, photocatalysis, and electrocatalysis are discussed, and the relationship between structure and activity of these catalysts are addressed. Future opportunities, including new catalytic materials designed by using biological principles, are indicated to achieve selective, eco-friendly, and energy neutral synthesis approaches.

Modeling and simulation of protein-surface interactions: achievements and challenges

Understanding protein-inorganic surface interactions is central to the rational design of new tools in biomaterial sciences, nanobiotechnology and nanomedicine. Although a significant amount of experimental research on protein adsorption onto solid substrates has been reported, many aspects of the recognition and interaction mechanisms of biomolecules and inorganic surfaces are still unclear. Theoretical modeling and simulations provide complementary approaches for experimental studies, and they have been applied for exploring protein-surface binding mechanisms, the determinants of binding specificity towards different surfaces, as well as the thermodynamics and kinetics of adsorption. Although the general computational approaches employed to study the dynamics of proteins and materials are similar, the models and force-fields (FFs) used for describing the physical properties and interactions of material surfaces and biological molecules differ. In particular, FF and water models designed for use in biomolecular simulations are often not directly transferable to surface simulations and vice versa. The adsorption events span a wide range of time- and length-scales that vary from nanoseconds to days, and from nanometers to micrometers, respectively, rendering the use of multi-scale approaches unavoidable. Further, changes in the atomic structure of material surfaces that can lead to surface reconstruction, and in the structure of proteins that can result in complete denaturation of the adsorbed molecules, can create many intermediate structural and energetic states that complicate sampling. In this review, we address the challenges posed to theoretical and computational methods in achieving accurate descriptions of the physical, chemical and mechanical properties of protein-surface systems. In this context, we discuss the applicability of different modeling and simulation techniques ranging from quantum mechanics through all-atom molecular mechanics to coarse-grained approaches. We examine uses of different sampling methods, as well as free energy calculations. Furthermore, we review computational studies of protein-surface interactions and discuss the successes and limitations of current approaches.

Peptide Binding for Bio-Based Nanomaterials

Peptide-based strategies represent transformative approaches to fabricate functional inorganic materials under sustainable conditions by modeling the methods exploited in biology. In general, peptides with inorganic affinity and specificity have been isolated from organisms and through biocombinatorial selection techniques (ie, phage and cell surface display). These peptides recognize and bind the inorganic surface through a series of noncovalent interactions, driven by both enthalpic and entropic contributions, wherein the biomolecules wrap the metallic nanoparticle structure. Through these interactions, modification of the inorganic surface can be accessed to drive the incorporation of significantly disordered surface metal atoms, which have been found to be highly catalytically active for a variety of chemical transformations. We have employed synthetic, site-directed mutagenesis studies to reveal localized binding effects of the peptide at the metallic nanoparticle structure to begin to identify the biological basis of control over biomimetic nanoparticle catalytic activity. The protocols described herein were used to fabricate and characterize peptide-capped nanoparticles in atomic resolution to identify peptide sequence effects on the surface structure of the materials, which can then be directly correlated to the catalytic activity to identify structure/function relationships.

NANOGOLD decorated by pHLIP peptide: comparative force field study

The potential of gold nanoparticles (AuNPs) in therapeutic and diagnostic cancer applications is becoming increasingly recognized, which focuses on their efficient and specific delivery from passive accumulation in tumour tissue to directly targeting tumor-specific biomarkers. AuNPs functionalized by pH low insertion peptide (pHLIP) have recently revealed the capability of targeting acidic tissues and inserting into cell membranes. However, the structure of AuNP-pHLIP conjugates and fundamental gold-peptide interactions still remain unknown. In this study, we have developed a series of molecular dynamics (MD) models reproducing a small gold nanoparticle coupled to pHLIP. We focus on Au135 nanoparticles that comprise a nearly spherical Au core (diameter ∼ 1.4 nm) functionalized with a monomaleimide moiety, mimicking a commercially available monomaleimido NANOGOLD® labelling agent. To probe the structure and folding of pHLIP, which is attached covalently to the maleimide NANOGOLD particle, we have benchmarked the performances of a series of popular, all-atom force fields (FF), including those of OPLS-AA, AMBER03, three variations of CHARMM FFs, as well as united-atom GROMOS G53A6 FF. We found that CHARMMs and OPLSAA FFs predict that in an aqueous salt solution at a neutral pH, pHLIP is partially bound onto the gold surface through some short hydrophobic peptide stretches, while at the same time, a large portion of peptide remains in solution. In contrast, AMBER03 and G53A6 FFs revealed the formation of compact, tightly bound peptide configurations adsorbed onto the nanoparticle core. To reproduce the experimental physical picture of the peptide adsorption onto gold in unfolded and unstructured conformations, our study suggests CHARMM36 and OPLS-AA FFs as a tool of choice for the computational studies of NANOGOLD decorated by pHLIP.

New Insights into Peptide-Silver Nanoparticle Interaction: Deciphering the Role of Cysteine and Lysine in the Peptide Sequence

We studied the interaction of four new pentapeptides with spherical silver nanoparticles. Our findings indicate that the combination of the thiol in Cys and amines in Lys/Arg residues is critical to providing stable protection for the silver surface. Molecular simulation reveals the atomic scale interactions that underlie the observed stabilizing effect of these peptides, while yielding qualitative agreement with experiment for ranking the affinity of the four pentapeptides for the silver surface.

Simulations of inorganic-bioorganic interfaces to discover new materials: insights, comparisons to experiment, challenges, and opportunities

Natural and man-made materials often rely on functional interfaces between inorganic and organic compounds. Examples include skeletal tissues and biominerals, drug delivery systems, catalysts, sensors, separation media, energy conversion devices, and polymer nanocomposites. Current laboratory techniques are limited to monitor and manipulate assembly on the 1 to 100 nm scale, time-consuming, and costly. Computational methods have become increasingly reliable to understand materials assembly and performance. This review explores the merit of simulations in comparison to experiment at the 1 to 100 nm scale, including connections to smaller length scales of quantum mechanics and larger length scales of coarse-grain models. First, current simulation methods, advances in the understanding of chemical bonding, in the development of force fields, and in the development of chemically realistic models are described. Then, the recognition mechanisms of biomolecules on nanostructured metals, semimetals, oxides, phosphates, carbonates, sulfides, and other inorganic materials are explained, including extensive comparisons between modeling and laboratory measurements. Depending on the substrate, the role of soft epitaxial binding mechanisms, ion pairing, hydrogen bonds, hydrophobic interactions, and conformation effects is described. Applications of the knowledge from simulation to predict binding of ligands and drug molecules to the inorganic surfaces, crystal growth and shape development, catalyst performance, as well as electrical properties at interfaces are examined. The quality of estimates from molecular dynamics and Monte Carlo simulations is validated in comparison to measurements and design rules described where available. The review further describes applications of simulation methods to polymer composite materials, surface modification of nanofillers, and interfacial interactions in building materials. The complexity of functional multiphase materials creates opportunities to further develop accurate force fields, including reactive force fields, and chemically realistic surface models, to enable materials discovery at a million times lower computational cost compared to quantum mechanical methods. The impact of modeling and simulation could further be increased by the advancement of a uniform simulation platform for organic and inorganic compounds across the periodic table and new simulation methods to evaluate system performance in silico.

Predicting Adsorption Affinities of Small Molecules on Carbon Nanotubes Using Molecular Dynamics Simulation

Computational techniques have the potential to accelerate the design and optimization of nanomaterials for applications such as drug delivery and contaminant removal; however, the success of such techniques requires reliable models of nanomaterial surfaces as well as accurate descriptions of their interactions with relevant solutes. In the present work, we evaluate the ability of selected models of naked and hydroxylated carbon nanotubes to predict adsorption equilibrium constants for about 30 small aromatic compounds with a variety of functional groups. The equilibrium constants determined using molecular dynamics coupled with free-energy calculation techniques are directly compared to those derived from experimental measurements. The calculations are highly predictive of the relative adsorption affinities of the compounds, with excellent correlation (r ≥ 0.9) between calculated and measured values of the logarithm of the adsorption equilibrium constant. Moreover, the agreement in absolute terms is also reasonable, with average errors of less than one decade. We also explore possible effects of surface loading, although we demonstrate that they are negligible for the experimental conditions considered. Given the degree of reliability demonstrated, we move on to employing the in silico techniques in the design of nanomaterials, using the optimization of adsorption affinity for the herbacide atrazine as an example. Our simulations suggest that, compared to other modifications of graphenic carbon, polyvinylpyrrolidone conjugation gives the highest affinity for atrazine-substantially greater than that of graphenic carbon alone-and may be useful as a nanomaterial for delivery or sequestration of atrazine.

Adjusting the Metrics of 1-D Helical Gold Nanoparticle Superstructures Using Multivalent Peptide Conjugates

The properties of nanoparticle superstructures depend on many factors, including the structural metrics of the nanoparticle superstructure (particle diameter, interparticle distances, etc.). Here, we introduce a family of gold-binding peptide conjugate molecules that can direct nanoparticle assembly, and we describe how these molecules can be systematically modified to adjust the structural metrics of linear double-helical nanoparticle superstructures. Twelve new peptide conjugates are prepared via linking a gold-binding peptide, AYSSGAPPMPPF (PEP(Au)), to a hydrophobic aliphatic tail. The peptide conjugates have 1, 2, or 3 PEP(Au) headgroups and a C12, C14, C16, or C18 aliphatic tail. The soft assembly of these peptide conjugates was studied using transmission electron microscopy (TEM), atomic force microscopy (AFM), and infrared (IR) spectroscopy. Several peptide conjugates assemble into 1-D twisted fibers having measurable structural parameters such as fiber width, thickness, and pitch that can be systematically varied by adjusting the aliphatic tail length and number of peptide headgroups. The linear soft assemblies serve as structural scaffolds for arranging gold nanoparticles into double-helical superstructures, which are examined via TEM. The pitch and interparticle distances of the gold nanoparticle double helices correspond to the underlying metrics of the peptide conjugate soft assemblies, illustrating that designed peptide conjugate molecules can be used to not only direct the assembly of gold nanoparticles but also control the metrics of the assembled structure.

Atomic-scale identification of Pd leaching in nanoparticle catalyzed C-C coupling: effects of particle surface disorder

C-C coupling reactions are of great importance in the synthesis of numerous organic compounds, where Pd nanoparticle catalyzed systems represent new materials to efficiently drive these reactions. Despite their pervasive utility, the catalytic mechanism of these particle-based reactions remains highly contested. Herein we present evidence of an atom leaching mechanism for Stille coupling under aqueous conditions using peptide-capped Pd nanoparticles. EXAFS analysis revealed Pd coordination changes in the nanoparticle consistent with Pd atom abstraction, where sizing analysis by SAXS confirmed particle size changes associated with a leaching process. It is likely that recently discovered highly disordered surface Pd atoms are the favored catalytic active sites and are leached during oxidative addition, resulting in smaller particles. Probing the mechanism of nanoparticle-driven C-C coupling reactions through structural analyses provides fundamental information concerning these active sites and their reactivity at the atomic-scale, which can be used to improve catalytic performance to meet important sustainability goals.

Sequence-dependent cluster analysis of biomineralization peptides

A reliable and statistically valid classification of biomineralization peptides is herein presented. 27 biomineralization peptides (BMPep) were randomly selected as representative samples to establish the classification system using k-means method. These biomineralization peptides were either discovered through isolation from various organisms or via phage display. Our findings show that there are two types of biomineralization peptides based on their length, molecular weight, heterogeneity, and aliphatic residues. Type-1 BMPeps are more commonly found and exhibit higher values for these significant clustering variables. In contrast are the type-2 BMPeps, which have lower values for these parameters and are less common. Through our clustering analysis, a more efficient and systematic approach in BMPep selection is possible since previous methods of BMPep classification are unreliable.

Elucidation of peptide-directed palladium surface structure for biologically tunable nanocatalysts

Peptide-enabled synthesis of inorganic nanostructures represents an avenue to access catalytic materials with tunable and optimized properties. This is achieved via peptide complexity and programmability that is missing in traditional ligands for catalytic nanomaterials. Unfortunately, there is limited information available to correlate peptide sequence to particle structure and catalytic activity to date. As such, the application of peptide-enabled nanocatalysts remains limited to trial and error approaches. In this paper, a hybrid experimental and computational approach is introduced to systematically elucidate biomolecule-dependent structure/function relationships for peptide-capped Pd nanocatalysts. Synchrotron X-ray techniques were used to uncover substantial particle surface structural disorder, which was dependent upon the amino acid sequence of the peptide capping ligand. Nanocatalyst configurations were then determined directly from experimental data using reverse Monte Carlo methods and further refined using molecular dynamics simulation, obtaining thermodynamically stable peptide-Pd nanoparticle configurations. Sequence-dependent catalytic property differences for C-C coupling and olefin hydrogenation were then elucidated by identification of the catalytic active sites at the atomic level and quantitative prediction of relative reaction rates. This hybrid methodology provides a clear route to determine peptide-dependent structure/function relationships, enabling the generation of guidelines for catalyst design through rational tailoring of peptide sequences.

Reductant and sequence effects on the morphology and catalytic activity of peptide-capped Au nanoparticles

The use of peptides as capping ligands for materials synthesis has been widely explored. The ambient conditions of bio-inspired syntheses using molecules such as peptides represent an attractive route for controlling the morphology and activity of nanomaterials. Although various reductants can be used in such syntheses, no comprehensive comparison of the same bio-based ligand with different reductants has been reported. In this contribution, peptides AuBP1, AuBP2, and Pd4 are used in the synthesis of Au nanoparticles. The reductant strength is varied by using three different reducing agents: NaBH4, hydrazine, and ascorbic acid. These changes in reductant produce significant morphological differences in the final particles. The weakest reductant, ascorbic acid, yields large, globular nanoparticles with rough surfaces, whereas the strongest reductant, NaBH4, yields small, spherical, smooth nanomaterials. Studies of 4-nitrophenol reduction using the Au nanoparticles as catalysts reveal a decrease in activation energy for the large, globular, rough materials relative to the small, spherical, smooth materials. These studies demonstrate that modifying the reductant is a simple way to control the activity of peptide-capped nanoparticles.

Glutathione-stabilized palladium nanozyme for colorimetric assay of silver(i) ions

A glutathione-capped Pd nanozyme is employed to explore colorimetric detection of Ag⁺ in aqueous solution with high sensitivity.

Structure of arginine overlayers at the aqueous gold interface: implications for nanoparticle assembly

Adsorption of small biomolecules onto the surface of nanoparticles offers a novel route to generation of nanoparticle assemblies with predictable architectures. Previously, ligand-exchange experiments on citrate-capped gold nanoparticles with the amino acid arginine were reported to support linear nanoparticle assemblies. Here, we use a combination of atomistic modeling with experimental characterization to explore aspects of the assembly hypothesis for these systems. Using molecular simulation, we probe the structural and energetic characteristics of arginine overlayers on the Au(111) surface under aqueous conditions at both low- and high-coverage regimes. In the low-density regime, the arginines lie flat on the surface. At constant composition, these overlayers are found to be lower in energy than the densely packed films, although the latter case appears kinetically stable when arginine is adsorbed via the zwitterion group, exposing the charged guanidinium group to the solvent. Our findings suggest that zwitterion-zwitterion hydrogen bonding at the gold surface and minimization of the electrostatic repulsion between adjacent guanidinium groups play key roles in determining arginine overlayer stability at the aqueous gold interface. Ligand-exchange experiments of citrate-capped gold nanoparticles with arginine derivatives agmatine and N-methyl-l-arginine reveal that modification at the guanidinium group significantly diminishes the propensity for linear assembly of the nanoparticles.

Effects of biomineralization peptide topology on the structure and catalytic activity of Pd nanomaterials

Three dimensional porous structures of Pd were formed through a designed peptide with precisely defined topological features. The hierarchical materials exhibited excellent catalytic performance in the reduction of nitrophenol isomers with preference for the meta isomer.

Concurrent zero-dimensional and one-dimensional biomineralization of gold from a solution of Au3+ and bovine serum albumin

A technique was developed for preparing a novel material that consists of gold nanoparticles trapped within a fiber of unfolded proteins. These fibers are made in an aqueous solution that contains HAuCl4 and the protein, bovine serum albumin (BSA). By changing the ratio of gold to BSA in solution, two different types of outcomes are observed. At lower gold to BSA ratios (30-120), a purple solution results after heating the mixture at 80 °C for 4 h. At higher gold to BSA ratios (130-170), a clear solution containing purple fibers results after heating the mixture at 80 °C for 4 h. UV-Vis spectroscopy and light scattering techniques show growth in nanocolloid size as gold to BSA ratio rises above 100. Data indicate that, for the higher gold to BSA ratios, the gold is sequestered within the solid material. The material mass, visible by eye, appears to be an aggregation of smaller individual fibers. Scanning electron microscopy and transmission electron microscopy indicate that these fibers are primarily one-dimensional aggregates, which can display some branching, and can be as narrow as 400 nm in size. The likely mechanism for the synthesis of the novel material is discussed.

Highly active subnano palladium clusters embedded in i-motif DNA

Highly active subnano Pd clusters were synthesized using i-motif DNA as the template through characterization via ESI MS, DLS, XPS, UV-vis, and FTIR. It is indicated that Pd1-Pd5 clusters are generated at a [Pd]/[base] ratio of 0.2, Pd8 to Pd9 clusters are generated at a [Pd]/[base] ratio of 0.5, and large nanoparticles with the size about 2.6 nm are formed at a [Pd]/[base] ratio of 2.0. The i-motif-stabilized Pd8-Pd9 clusters show high catalytic activity toward the reduction of 4-nitrophenol with a relative rate constant value of 2034 min(-1) (mM Pd)(-1). DFT calculations disclose that the unique structure of the i-motif with consecutive hemiprotonated CH(+)·C pairs can efficiently ligate Pd ions at the N3 sites of cytosines and that the synthesized Pd clusters consist of metallic Pd atoms as well as positively charged Pd that is ligated by nucleobases, which is capable of facilitating the activation of the nitryl group of 4-nitrophenol. This work suggests a promising pathway to preparing subnano metal catalysts with enhanced catalytic activity using programmable DNA scaffolds.

Enhancing in vitro selection techniques to assist the discovery, understanding and use of inorganic binding peptides

Reflecting the increasing interest in combinatorial approaches, peptide phage display has seen an unprecedented expansion in a wide range of research areas. Its application to the discovery and analysis of metal binding peptides has opened up new research directions and largely contributed to the nanotechnology field. The rationale behind the need to identify such peptides varies depending on the final aim of the research and its application. Therefore, the possibility to modify the selection technique according to the different requirements would allow for a more systematic approach to be adopted and would ultimately provide substantial benefits. Although the standard panning method can be virtually applied to any target, its use for the identification of metal binding peptides does not provide the characteristics and the flexibility required for an efficient and tailored selection. Here we report on the development of a new panning method that can contribute to a faster, versatile and more informative analysis. Through the use of rolling-circle amplification, polymerase reaction and wild type phage, we have converted the standard selection technique into a more dynamic process in which adjustments can be evaluated and made consistently with the need of the experiment. The successfulness of the improved method is demonstrated in a number of panning experiments with different inorganic targets. The modifications applied to each selection are described and comparisons between the results obtained are made in order to extensively assess and evaluate the impact of the new process. The importance of tailoring the screening method to the specific objectives of a study is also considered. New binder sequences for the materials included in the investigation are identified; their sequences and distinctive characteristics are reported and their ability to act as templates for the nucleation of inorganic material is demonstrated and discussed.

Synthesis of silver octahedra with controlled sizes and optical properties via seed-mediated growth

Silver octahedra with edge lengths controlled in the range of 20-72 nm were synthesized via seed-mediated growth. The key to the success of this synthesis is the use of single-crystal Ag seeds with uniform and precisely controlled sizes to direct the growth and the use of citrate as a selective capping agent for the {111} facets. Our mechanistic studies demonstrated that Ag seeds with both cubic and quasi-spherical shapes could evolve into octahedra. For the first time, we were able to precisely control the edge lengths of Ag octahedra below 100 nm, and the lower limit of size could even be pushed down to 20 nm. Using the as-obtained Ag octahedra as sacrificial templates, Au nanocages with an octahedral shape and precisely tunable optical properties were synthesized through a galvanic replacement reaction. Such hollow nanostructures are promising candidates for a broad range of applications related to optics, catalysis, and biomedicine.

Thermodynamically consistent force fields for the assembly of inorganic, organic, and biological nanostructures: the INTERFACE force field

The complexity of the molecular recognition and assembly of biotic-abiotic interfaces on a scale of 1 to 1000 nm can be understood more effectively using simulation tools along with laboratory instrumentation. We discuss the current capabilities and limitations of atomistic force fields and explain a strategy to obtain dependable parameters for inorganic compounds that has been developed and tested over the past decade. Parameter developments include several silicates, aluminates, metals, oxides, sulfates, and apatites that are summarized in what we call the INTERFACE force field. The INTERFACE force field operates as an extension of common harmonic force fields (PCFF, COMPASS, CHARMM, AMBER, GROMACS, and OPLS-AA) by employing the same functional form and combination rules to enable simulations of inorganic-organic and inorganic-biomolecular interfaces. The parametrization builds on an in-depth understanding of physical-chemical properties on the atomic scale to assign each parameter, especially atomic charges and van der Waals constants, as well as on the validation of macroscale physical-chemical properties for each compound in comparison to measurements. The approach eliminates large discrepancies between computed and measured bulk and surface properties of up to 2 orders of magnitude using other parametrization protocols and increases the transferability of the parameters by introducing thermodynamic consistency. As a result, a wide range of properties can be computed in quantitative agreement with experiment, including densities, surface energies, solid-water interface tensions, anisotropies of interfacial energies of different crystal facets, adsorption energies of biomolecules, and thermal and mechanical properties. Applications include insight into the assembly of inorganic-organic multiphase materials, the recognition of inorganic facets by biomolecules, growth and shape preferences of nanocrystals and nanoparticles, as well as thermal transitions and nanomechanics. Limitations and opportunities for further development are also described.