Orientational dynamics of the water layer adjacent to Au surface accelerated by polarization effect

The orientation and rearrangement of water on a gold electrode significantly influences its physicochemical heterogeneous performance. Despite numerous experimental and theoretical studies aimed at uncovering the structural characteristics of interfacial water, the orientational behavior resulting from electrode-induced rearrangements remains a subject of ongoing debate. Here, we employed molecular dynamics simulations to investigate the adaptive structure and dynamics properties of interfacial water on Au(111) and Au(100) surfaces by considering a polarizable model for Au atoms in comparison with the non-polarizable model. Compared to the nonpolarizable systems, the polarization effect can enhance the interaction between water molecules and the gold surface. Unexpectedly, the rotational dynamics directly associated with the orientational behavior of water adjacent to the gold surface is accelerated, thereby reducing the hydrogen bond lifetime. The underlying mechanism for this anomalous phenomenon originates from the polarization effect, which induces the attraction of the positive hydrogen atoms to the surface by the negative image charge. This leads to a change in orientation that disrupts the hydrogen bonds in the first water layer and subsequently accelerates reorientation dynamics of water molecules adjacent to the gold surface. These results shed light on the intricate interplay between polarization effects and water molecule dynamics on metal surfaces, establishing the foundation for the rational regulation of the orientation of interfacial water.

Ideal conductor/dielectric model (ICDM): A generalized technique to correct for finite-size effects in molecular simulations of hindered ion transport

Molecular simulations serve as indispensable tools for investigating the kinetics and elucidating the mechanism of hindered ion transport across nanoporous membranes. In particular, recent advancements in advanced sampling techniques have made it possible to access translocation timescales spanning several orders of magnitude. In our prior study [Shoemaker et al., J. Chem. Theory Comput. 18, 7142 (2022)], we identified significant finite size artifacts in simulations of pressure-driven hindered ion transport through nanoporous graphitic membranes. We introduced the ideal conductor model, which effectively corrects for such artifacts by assuming the feed to be an ideal conductor. In the present work, we introduce the ideal conductor dielectric model (Icdm), a generalization of our earlier model, which accounts for the dielectric properties of both the membrane and the filtrate. Using the Icdm model substantially enhances the agreement among corrected free energy profiles obtained from systems of varying sizes, with notable improvements observed in regions proximate to the pore exit. Moreover, the model has the capability to consider secondary ion passage events, including the transport of a co-ion subsequent to the traversal of a counter-ion, a feature that is absent in our original model. We also investigate the sensitivity of the new model to various implementation details. The Icdm model offers a universally applicable framework for addressing finite size artifacts in molecular simulations of ion transport. It stands as a significant advancement in our quest to use molecular simulations to comprehensively understand and manipulate ion transport processes through nanoporous membranes.

Computational Insights into the Adsorption of Ligands on Gold Nanosurfaces

We study the adsorption process of model peptides, nucleobases, and selected standard ligands on gold through the development of a computational protocol based on fully atomistic classical molecular dynamics (MD) simulations combined with umbrella sampling techniques. The specific features of the interface components, namely, the molecule, the metallic substrate, and the solvent, are taken into account through different combinations of force fields (FFs), which are found to strongly affect the results, especially changing absolute and relative adsorption free energies and trends. Overall, noncovalent interactions drive the process along the adsorption pathways. Our findings also show that a suitable choice of the FF combinations can shed light on the affinity, position, orientation, and dynamic fluctuations of the target molecule with respect to the surface. The proposed protocol may help the understanding of the adsorption process at the microscopic level and may drive the in-silico design of biosensors for detection purposes.

Aggregation of an Amyloidogenic Peptide on Gold Surfaces

Solid surfaces have been shown to affect the aggregation and assembly of many biomolecular systems. One important example is the formation of protein fibrils, which can occur on a range of biological and synthetic surfaces. The rate of fibrillation depends on both the protein structure and the surface chemistry, with the different molecular and oligomer structures adopted by proteins on surfaces likely to be crucial. In this paper, the aggregation of the model amyloidogenic peptide, Aβ(16-22), corresponding to a hydrophobic segment of the amyloid beta protein on a gold surface is studied using molecular dynamics simulation. Previous simulations of this peptide on gold surfaces have shown that it adopts conformations on surfaces that are quite different from those in bulk solution. These simulations show that this then leads to significant differences in the oligomer structures formed in solution and on gold surfaces. In particular, oligomers formed on the surface are low in beta-strands so are unlike the structures formed in bulk solution. When oligomers formed in solution adsorb onto gold surfaces they can then restructure themselves. This can then help explain the inhibition of Aβ(16-22) fibrillation by gold surfaces and nanoparticles seen experimentally.

Peptide adsorption on silica surfaces: Simulation and experimental insights

The understanding of interactions between proteins with silica surface is crucial for a wide range of different applications: from medical devices, drug delivery and bioelectronics to biotechnology and downstream processing. We show the application of EISM (Effective Implicit Surface Model) for discovering the set of peptide interactions with silica surface. The EISM is employed for a high-speed computational screening of peptides to model the binding affinity of small peptides to silica surfaces. The simulations are complemented with experimental data of peptides with silica nanoparticles from microscale thermophoresis and from infrared spectroscopy. The experimental work shows excellent agreement with computational results and verifies the EISM model for the prediction of peptide-surface interactions. 57 peptides, with amino acids favorable for adsorption on Silica surface, are screened by EISM model for obtaining results, which are worth to be considered as a guidance for future experimental and theoretical works. This model can be used as a broad platform for multiple challenges at surfaces which can be applied for multiple surfaces and biomolecules beyond silica and peptides.

Curvature and temperature-dependent thermal interface conductance between nanoscale gold and water

Plasmonic gold nanoparticles (AuNPs) can convert laser irradiation into thermal energy for a variety of applications. Although heat transfer through the AuNP-water interface is considered an essential part of the plasmonic heating process, there is a lack of mechanistic understanding of how interface curvature and the heating itself impact interfacial heat transfer. Here, we report atomistic molecular dynamics simulations that investigate heat transfer through nanoscale gold-water interfaces. We simulated four nanoscale gold structures under various applied heat flux values to evaluate how gold-water interface curvature and temperature affect the interfacial heat transfer. We also considered a case in which we artificially reduced wetting at the gold surfaces by tuning the gold-water interactions to determine if such a perturbation alters the curvature and temperature dependence of the gold-water interfacial heat transfer. We first confirmed that interfacial heat transfer is particularly important for small particles (diameter ≤10 nm). We found that the thermal interface conductance increases linearly with interface curvature regardless of the gold wettability, while it increases nonlinearly with the applied heat flux under normal wetting and remains constant under reduced wetting. Our analysis suggests the curvature dependence of the interface conductance coincides with changes in interfacial water adsorption, while the temperature dependence may arise from temperature-induced shifts in the distribution of water vibrational states. Our study advances the current understanding of interface thermal conductance for a broad range of applications.

Microscopic Simulations of Electrochemical Double-Layer Capacitors

Electrochemical double-layer capacitors (EDLCs) are devices allowing the storage or production of electricity. They function through the adsorption of ions from an electrolyte on high-surface-area electrodes and are characterized by short charging/discharging times and long cycle-life compared to batteries. Microscopic simulations are now widely used to characterize the structural, dynamical, and adsorption properties of these devices, complementing electrochemical experiments and in situ spectroscopic analyses. In this review, we discuss the main families of simulation methods that have been developed and their application to the main family of EDLCs, which include nanoporous carbon electrodes. We focus on the adsorption of organic ions for electricity storage applications as well as aqueous systems in the context of blue energy harvesting and desalination. We finally provide perspectives for further improvement of the predictive power of simulations, in particular for future devices with complex electrode compositions.

Improving the Accuracy of Atomistic Simulations of the Electrochemical Interface

Atomistic simulation of the electrochemical double layer is an ambitious undertaking, requiring quantum mechanical description of electrons, phase space sampling of liquid electrolytes, and equilibration of electrolytes over nanosecond time scales. All models of electrochemistry make different trade-offs in the approximation of electrons and atomic configurations, from the extremes of classical molecular dynamics of a complete interface with point-charge atoms to correlated electronic structure methods of a single electrode configuration with no dynamics or electrolyte. Here, we review the spectrum of simulation techniques suitable for electrochemistry, focusing on the key approximations and accuracy considerations for each technique. We discuss promising approaches, such as enhanced sampling techniques for atomic configurations and computationally efficient beyond density functional theory (DFT) electronic methods, that will push electrochemical simulations beyond the present frontier.

Reorganization Free Energy of Copper Proteins in Solution, in Vacuum, and on Metal Surfaces

Metalloproteins, known to efficiently transfer electronic charge in biological systems, recently found their utilization in nanobiotechnological devices where the protein is placed into direct contact with metal surfaces. The feasibility of oxidation/reduction of the protein redox sites is affected by the reorganization free energies, one of the key parameters determining the transfer rates. While their values have been measured and computed for proteins in their native environments, i.e., in aqueous solution, the reorganization free energies of dry proteins or proteins adsorbed to metal surfaces remain unknown. Here, we investigate the redox properties of blue copper protein azurin, a prototypical redox-active metalloprotein previously probed by various experimental techniques both in solution and on metal/vacuum interfaces. We used a hybrid QM/MM computational technique based on DFT to explore protein dynamics, flexibility, and corresponding reorganization free energies in aqueous solution, vacuum, and on vacuum gold interfaces. Somewhat surprisingly, the reorganization free energy only slightly decreases when azurin is dried because the loss of the hydration shell leads to larger flexibility of the protein near its redox site. At the vacuum gold surfaces, the energetics of the structure relaxation depends on the adsorption geometry, however, significant reduction of the reorganization free energy was not observed. These findings have important consequences for the charge transport mechanism in vacuum devices, showing that the free energy barriers for protein oxidation remain significant even under ultra-high vacuum conditions.

A molecular perspective on induced charges on a metallic surface

Understanding the response of the surface of metallic solids to external electric field sources is crucial to characterize electrode-electrolyte interfaces. Continuum electrostatics offer a simple description of the induced charge density at the electrode surface. However, such a simple description does not take into account features related to the atomic structure of the solid and to the molecular nature of the solvent and of the dissolved ions. In order to illustrate such effects and assess the ability of continuum electrostatics to describe the induced charge distribution, we investigate the behavior of a gold electrode interacting with sodium or chloride ions fixed at various positions, in a vacuum or in water, using all-atom constant-potential classical molecular dynamics simulations. Our analysis highlights important similarities between the two approaches, especially under vacuum conditions and when the ion is sufficiently far from the surface, as well as some limitations of the continuum description, namely, neglecting the charges induced by the adsorbed solvent molecules and the screening effect of the solvent when the ion is close to the surface. While the detailed features of the charge distribution are system-specific, we expect some of our generic conclusions on the induced charge density to hold for other ions, solvents, and electrode surfaces. Beyond this particular case, the present study also illustrates the relevance of such molecular simulations to serve as a reference for the design of improved implicit solvent models of electrode-electrolyte interfaces.

Modelling peptide adsorption energies on gold surfaces with an effective implicit solvent and surface model

The interaction of proteins and peptides with inorganic surfaces is relevant in a wide array of technological applications. A rational approach to design peptides for specific surfaces would build on amino-acid and surface specific interaction models, which are difficult to characterize experimentally or by modeling. Even with such a model at hand, the large number of possible sequences and the large conformation space of peptides make comparative simulations challenging. Here we present a computational protocol, the effective implicit surface model (EISM), for efficient in silico evaluation of the binding affinity trends of peptides on parameterized surface, with a specific application to the widely studied gold surface. In EISM the peptide surface interactions are modeled with an amino-acid and surface specific implicit solvent model, which permits rapid exploration of the peptide conformational degrees of freedom. We demonstrate the parametrization of the model and compare the results with all-atom simulations and experimental results for specific peptides.

Molecular Simulation of Electrode-Solution Interfaces

Many key industrial processes, from electricity production, conversion, and storage to electrocatalysis or electrochemistry in general, rely on physical mechanisms occurring at the interface between a metallic electrode and an electrolyte solution, summarized by the concept of an electric double layer, with the accumulation/depletion of electrons on the metal side and of ions on the liquid side. While electrostatic interactions play an essential role in the structure, thermodynamics, dynamics, and reactivity of electrode-electrolyte interfaces, these properties also crucially depend on the nature of the ions and solvent, as well as that of the metal itself. Such interfaces pose many challenges for modeling because they are a place where quantum chemistry meets statistical physics. In the present review, we explore the recent advances in the description and understanding of electrode-electrolyte interfaces with classical molecular simulations, with a focus on planar interfaces and solvent-based liquids, from pure solvent to water-in-salt electrolytes.

Simulating selective binding of a biological template to a nanoscale architecture: a core concept of a clamp-based binding-pocket-favored N-terminal-domain assembly

The biological template and its mutants have vital significance in next generation remediation, electrochemical, photovoltaic, catalytic, sensing and digital memory devices. However, a microscopic model describing the biotemplating process is generally lacking on account of modelling complexity, which has prevented widespread commercial use of biotemplates. Here, we demonstrate M13-biotemplating kinetics in atomic resolution by leveraging large-scale molecular dynamics (MD) simulations. The model reveals the assembly of gold nanoparticles on two experimentally-based M13 phage types using full M13-capsid structural models and with polarizable gold nanoparticles in explicit solvent. Both mechanistic and structural insights into the selective binding affinity of the M13 phage to gold nanoparticles are obtained based on a previously unconsidered clamp-based binding-pocket-favored N-terminal-domain assembly and also on surface-peptide flexibility. These results provide a deeper level of understanding of protein sequence-based affinity and open the route for genetically engineering a wide range of 3D electrodes for high-density low-cost device integration.

A new mechanism for reduced cell adhesion: Adsorption dynamics of collagen on a nanoporous gold surface

Nanostructured materials such as nanoparticles and nanoporous materials strongly affect cell behaviors such as cell viability. Because cellular uptake of nanoporous materials does not occur, mechanisms for the effects of nanoporous materials on cells are different from those of nanoparticles. The effects of nanoporous materials on cells are thought to result from large conformational changes in the extracellular matrix (ECM) induced by the nanoporous materials, although the mechanotransduction and the critical focal adhesion cluster size also have an effect on the cell response. However, we show that the adhesion of mesenchymal stem cells to a gold surface is reduced for nanoporous gold (NPG), despite the conformational changes in collagen induced by NPG being below the detection limits of the experimental analyses. The adsorption dynamics of collagen on NPG are investigated by molecular dynamics simulations to determine the origin of the reduced cell adhesion to NPG. The adsorption energy of collagen on NPG is lower than that on flat gold (FG) despite there being little difference between the global conformation of collagen segments adsorbed on NPG compared with FG. This finding is related to the surface strain of NPG and the limited movement of collagen amino acids owing to interchain hydrogen bonds. The results obtained in this study provide new insight into the interactions between nanostructured materials and the ECM.

The electrochemical interface in first-principles calculations

First-principles predictions play an important role in understanding chemistry at the electrochemical interface. Electronic structure calculations are straightforward for vacuum interfaces, but do not easily account for the interfacial fields and solvation that fundamentally change the nature of electrochemical reactions. Prevalent techniques for first-principles prediction of electrochemical processes range from expensive explicit solvation using ab initio molecular dynamics, through a hierarchy of continuum solvation techniques, to neglecting solvation and interfacial field effects entirely. Currently, no single approach reliably captures all relevant effects of the electrochemical double layer in first-principles calculations. This review systematically lays out the relation between all major approaches to first-principles electrochemistry, including the key approximations and their consequences for accuracy and computational cost. Focusing on ab initio methods for thermodynamic properties of aqueous interfaces, we first outline general considerations for modeling electrochemical interfaces, including solvent and electrolyte dynamics and electrification. We then present the specifics of various explicit and implicit models of the solvent and electrolyte. Finally, we discuss the compromise between computational efficiency and accuracy, and identify key outstanding challenges and future opportunities in the wide range of techniques for first-principles electrochemistry.

An Overview of Molecular Modeling for Drug Discovery with Specific Illustrative Examples of Applications

In this paper we review the current status of high-performance computing applications in the general area of drug discovery. We provide an introduction to the methodologies applied at atomic and molecular scales, followed by three specific examples of implementation of these tools. The first example describes in silico modeling of the adsorption of small molecules to organic and inorganic surfaces, which may be applied to drug delivery issues. The second example involves DNA translocation through nanopores with major significance to DNA sequencing efforts. The final example offers an overview of computer-aided drug design, with some illustrative examples of its usefulness.

Adsorption of amino acids on graphene: assessment of current force fields

We compare the free energies of adsorption (ΔAads) and the structural preferences of amino acids on graphene obtained using the non-polarizable force fields-Amberff99SB-ILDN/TIP3P, CHARMM36/modified-TIP3P, OPLS-AA/M/TIP3P, and Amber03w/TIP4P/2005. The amino acid-graphene interactions are favorable irrespective of the force field. While the magnitudes of ΔAads differ between the force fields, the relative free energy of adsorption across amino acids is similar for the studied force fields. ΔAads positively correlates with amino acid-graphene and negatively correlates with graphene-water interaction energies. Using a combination of principal component analysis and density-based clustering technique, we grouped the structures observed in the graphene adsorbed state. The resulting population of clusters, and the conformation in each cluster indicate that the structures of the amino acid in the graphene adsorbed state vary across force fields. The differences in the conformations of amino acids are more severe in the graphene adsorbed state compared to the bulk state for all the force fields. Our findings suggest that the force fields studied will give qualitatively consistent relative strength of adsorption across proteins but different structural preferences in the graphene adsorbed state.

Decomposition of molecular properties

We review recent work on property decomposition techniques using quantum chemical methods and discuss some topical applications in terms of quantum mechanics-molecular mechanics calculations and the constructing of properties of large molecules and clusters. Starting out from the so-called LoProp decomposition scheme [Gagliardi et al., J. Chem. Phys., 2004, 121, 4994] for extracting atomic and inter-atomic contributions to molecular properties we show how this method can be generalized to localized frequency-dependent polarizabilities, to localized hyperpolarizabilities and to localized dispersion coefficients. Some applications of the generalized decomposition technique are reviewed - calculations of frequency-dependent polarizabilities, Rayleigh scattering of large clusters, and calculations of hyperpolarizabilities of proteins.

Adsorption of Amino Acids on Gold: Assessing the Accuracy of the GolP-CHARMM Force Field and Parametrization of Au-S Bonds

The interaction of amino acids with metal electrodes plays a crucial role in bioelectrochemistry and the emerging field of bionanoelectronics. Here we present benchmark calculations of the adsorption structure and energy of all natural amino acids on Au(111) in vacuum using a van-der-Waals density functional (revPBE-vdW) that showed good performance on the S22 set of weakly bound dimers (mean relative unsigned error (MRUE) wrt CCSD(T)/CBS = 13.3%) and adsorption energies of small organic molecules on Au(111) (MRUE wrt experiment = 11.2%). The vdW-DF results are then used to assess the accuracy of a popular force field for Au-amino acid interactions, GolP-CHARMM, which explicitly describes image charge interactions via rigid-rod dipoles. We find that while the force field underestimates adsorption distances, it does reproduce the binding energy rather well (MRUE wrt revPBE-vdW = 11.3%) with the MRUE decreasing in the order Cys, Met > amines > aliphatic > carboxylic > aromatic. We also present a parametrization of the bonding interaction between sulfur-containing molecules and the Au(111) surface and report force field parameters that are compatible with GolP-CHARMM. We believe the vdW-DF calculations presented herein will provide useful reference data for further force field development, and that the new Au-S bonding parameters will enable improved simulations of proteins immobilized on Au-electrodes via S-linkages.

Force Field for Water over Pt(111): Development, Assessment, and Comparison

Metal/water interfaces are key in many natural and industrial processes, such as corrosion, atmospheric, or environmental chemistry. Even today, the only practical approach to simulate large interfaces between a metal and water is to perform force-field simulations. In this work, we propose a novel force field, GAL17, to describe the interaction of water and a Pt(111) surface. GAL17 builds on three terms: (i) a standard Lennard-Jones potential for the bonding interaction between the surface and water, (ii) a Gaussian term to improve the surface corrugation, and (iii) two terms describing the angular dependence of the interaction energy. The 12 parameters of this force field are fitted against a set of 210 adsorption geometries of water on Pt(111). The performance of GAL17 is compared to several other approaches that have not been validated against extensive first-principles computations yet. Their respective accuracy is evaluated on an extended set of 802 adsorption geometries of H₂O on Pt(111), 52 geometries derived from icelike layers, and an MD simulation of an interface between a c(4 × 6) Pt(111) surface and a water layer of 14 Å thickness. The newly developed GAL17 force field provides a significant improvement over previously existing force fields for Pt(111)/H₂O interactions. Its well-balanced performance suggests that it is an ideal candidate to generate relevant geometries for the metal/water interface, paving the way to a representative sampling of the equilibrium distribution at the interface and to predict solvation free energies at the solid/liquid interface.

Insight into induced charges at metal surfaces and biointerfaces using a polarizable Lennard-Jones potential

Metallic nanostructures have become popular for applications in therapeutics, catalysts, imaging, and gene delivery. Molecular dynamics simulations are gaining influence to predict nanostructure assembly and performance; however, instantaneous polarization effects due to induced charges in the free electron gas are not routinely included. Here we present a simple, compatible, and accurate polarizable potential for gold that consists of a Lennard–Jones potential and a harmonically coupled core-shell charge pair for every metal atom. The model reproduces the classical image potential of adsorbed ions as well as surface, bulk, and aqueous interfacial properties in excellent agreement with experiment. Induced charges affect the adsorption of ions onto gold surfaces in the gas phase at a strength similar to chemical bonds while ions and charged peptides in solution are influenced at a strength similar to intermolecular bonds. The proposed model can be applied to complex gold interfaces, electrode processes, and extended to other metals.

Molecular dynamics models for predicting the behavior of metallic nanostructures typically do not take into account polarization effects in metals. Here, the authors introduce a polarizable Lennard–Jones potential that provides quantitative insight into the role of induced charges at metal surfaces and related complex material interfaces.

Computational Insight into the Interaction of Cytochrome C with Wet and PVP-Coated Ag Surfaces

In this work, the adsorption of cytochrome C (CytC) on wet {100}, {111}, {110}, and {120} silver surfaces has been investigated by computational simulations. The effect of polyvinylpyrrolidone (PVP) coating has also been studied. The main results obtained can be summarized as follow: (a) CytC strongly interacts with wet bare high index facets, while the adsorption over the {100} surface is disfavored due to the strong water structuring at the surface; (b) a nonselective protein adsorption mechanism is highlighted; (c) the native structure of CytC is well preserved during adsorption; (d) the heme group of CytC is never found to interact directly with the surface; (e) the interactions with the PVP-capped {100} surface is weak and specific. These results can be exploited to better control biological responses at engineered nanosurface, allowing the development of improved diagnostic tools.

Structure, Dynamics, and Electron Transfer of Azurin Bound to a Gold Electrode

Blue copper redox protein azurin (AZ) constitutes an ideal active element for building bionano-optoelectronic devices based on the intriguing interplay among its electron transfer (ET), vibrational, and optical properties. A full comprehension of its dynamical and functional behavior is required for efficient applications. Here, AZ bound to gold electrode via its disulfide bridge was investigated by a molecular dynamics simulation approach taking into account for gold electron polarization which provides a more realistic description of the protein-gold interaction. Upon binding to gold, AZ undergoes slight changes in its secondary structure with the preservation of the copper-containing active site structure. Binding of AZ to gold promotes new collective motions, with respect to free AZ, as evidenced by essential dynamics. Analysis of the ET from the AZ copper ion to the gold substrate, performed by the Pathways model, put into evidence the main residues and structural motifs of AZ involved in the ET paths. During the dynamical evolution of the bionanosystem, transient contacts between some lateral protein atoms and the gold substrate occurred; concomitantly, the opening of additional ET channels with much higher rates was registered. These results provide new and detailed insights on the dynamics and ET properties of the AZ-gold system, by also helping to rationalize some imaging and conductive experimental evidences and also to design new bionanodevices with tailored features.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

Computational and Experimental Investigation of the Structure of Peptide Monolayers on Gold Nanoparticles

The self-assembly and self-organization of small molecules on the surface of nanoparticles constitute a potential route toward the preparation of advanced proteinlike nanosystems. However, their structural characterization, critical to the design of bionanomaterials with well-defined biophysical and biochemical properties, remains highly challenging. Here, a computational model for peptide-capped gold nanoparticles (GNPs) is developed using experimentally characterized Cys-Ala-Leu-Asn-Asn (CALNN)- and Cys-Phe-Gly-Ala-Ile-Leu-Ser-Ser (CFGAILSS)-capped GNPs as a benchmark. The structure of CALNN and CFGAILSS monolayers is investigated using both structural biology techniques and molecular dynamics simulations. The calculations reproduce the experimentally observed dependence of the monolayer secondary structure on the peptide capping density and on the nanoparticle size, thus giving us confidence in the model. Furthermore, the computational results reveal a number of new features of peptide-capped monolayers, including the importance of sulfur movement for the formation of secondary structure motifs, the presence of water close to the gold surface even in tightly packed peptide monolayers, and the existence of extended 2D parallel β-sheet domains in CFGAILSS monolayers. The model developed here provides a predictive tool that may assist in the design of further bionanomaterials.

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.

Optical Modulation of Azobenzene-Modified Peptide for Gold Surface Binding

The ability to precisely and remotely modulate reversible binding interactions between biomolecules and abiotic surfaces is appealing for many applications. To achieve this level of control, an azobenzene-based optical switch is added to nanoparticle-binding peptides in order to switch peptide conformation and attenuate binding affinity to gold surfaces via binding and dissociation of peptides.

Correlating single-molecule and ensemble-average measurements of peptide adsorption onto different inorganic materials

The coating of solid-binding peptides (SBPs) on inorganic material surfaces holds significant potential for improved surface functionalization at nano-bio interfaces. In most related studies, the goal has been to engineer peptides with selective and high binding affinity for a target material. The role of the material substrate itself in modulating the adsorption behavior of a peptide molecule remains less explored and there are few studies that compare the interaction of one peptide with different inorganic substrates. Herein, using a combination of two experimental techniques, we investigated the adsorption of a 16 amino acid-long random coil peptide to various inorganic substrates - gold, silicon oxide, titanium oxide and aluminum oxide. Quartz crystal microbalance-dissipation (QCM-D) experiments were performed in order to measure the peptide binding affinity for inorganic solid supports at the ensemble average level, and atomic force microscopy (AFM) experiments were conducted in order to determine the adhesion force of a single peptide molecule. A positive trend was observed between the total mass uptake of attached peptide and the single-molecule adhesion force on each substrate. Peptide affinity for gold was appreciably greater than for the oxide substrates. Collectively, the results obtained in this study offer insight into the ways in which inorganic materials can differentially influence and modulate the adhesion of SBPs.

Understanding and Designing the Gold-Bio Interface: Insights from Simulations

Gold nanoparticles (AuNPs) are an integral part of many exciting and novel biomedical applications, sparking the urgent need for a thorough understanding of the physicochemical interactions occurring between these inorganic materials, their functional layers, and the biological species they interact with. Computational approaches are instrumental in providing the necessary molecular insight into the structural and dynamic behavior of the Au-bio interface with spatial and temporal resolutions not yet achievable in the laboratory, and are able to facilitate a rational approach to AuNP design for specific applications. A perspective of the current successes and challenges associated with the multiscale computational treatment of Au-bio interfacial systems, from electronic structure calculations to force field methods, is provided to illustrate the links between different approaches and their relationship to experiment and applications.

The interaction with gold suppresses fiber-like conformations of the amyloid β (16-22) peptide

Inorganic surfaces and nanoparticles can accelerate or inhibit the fibrillation process of proteins and peptides, including the biomedically relevant amyloid β peptide. However, the microscopic mechanisms that determine such an effect are still poorly understood. By means of large-scale, state-of-the-art enhanced sampling molecular dynamics simulations, here we identify an interaction mechanism between the segments 16-22 of the amyloid β peptide, known to be fibrillogenic by itself, and the Au(111) surface in water that leads to the suppression of fiber-like conformations from the peptide conformational ensemble. Moreover, thanks to advanced simulation analysis techniques, we characterize the conformational selection vs. induced fit nature of the gold effect. Our results disclose an inhibition mechanism that is rooted in the details of the microscopic peptide-surface interaction rather than in general phenomena such as peptide sequestration from the solution.

Three steps to gold: mechanism of protein adsorption revealed by Brownian and molecular dynamics simulations

The addition of three N-terminal histidines to β-lactamase inhibitor protein was shown experimentally to increase its binding potency to an Au(111) surface substantially but the binding mechanism was not resolved. Here, we propose a complete adsorption mechanism for this fusion protein by means of a multi-scale simulation approach and free energy calculations. We find that adsorption is a three-step process: (i) recognition of the surface predominantly by the histidine fusion peptide and formation of an encounter complex facilitated by a reduced dielectric screening of water in the interfacial region, (ii) adsorption of the protein on the surface and adoption of a specific binding orientation, and (iii) adaptation of the protein structure on the metal surface accompanied by induced fit. We anticipate that the mechanistic features of protein adsorption to an Au(111) surface revealed here can be extended to other inorganic surfaces and proteins and will therefore aid the design of specific protein-surface interactions.

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.

Modelling of graphene functionalization

This perspective describes the available theoretical methods and models for simulating graphene functionalization based on quantum and classical mechanics.

A dynamical approach to non-adiabatic electron transfers at the bio-inorganic interface

A methodology is proposed to investigate the role of the energy fluctuations, determined by the dynamical evolution of a system, and the role of non-adiabaticity in affecting the kinetic rate of electron transfer reactions at the bio-inorganic interface.

Understanding the mechanism of replacement of citrate from the surface of gold nanoparticles by amino acids: a theoretical and experimental investigation and their biological application

The present study explores the physicochemical aspects needed for the appropriate in vitro synthesis and surface modification behavior of gold nanoparticles (AuNPs) in the presence of amino acids (AA).

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.

Quantitative Evaluation of Peptide-Material Interactions by a Force Mapping Method: Guidelines for Surface Modification

Peptide coatings on material surfaces have demonstrated wide application across materials science and biotechnology, facilitating the development of nanobio interfaces through surface modification. A guiding motivation in the field is to engineer peptides with a high and selective binding affinity to target materials. Herein, we introduce a quantitative force mapping method in order to evaluate the binding affinity of peptides to various hydrophilic oxide materials by atomic force microscopy (AFM). Statistical analysis of adhesion forces and probabilities obtained on substrates with a materials contrast enabled us to simultaneously compare the peptide binding affinity to different materials. On the basis of the experimental results and corresponding theoretical analysis, we discuss the role of various interfacial forces in modulating the strength of peptide attachment to hydrophilic oxide solid supports as well as to gold. The results emphasize the precision and robustness of our approach to evaluating the adhesion strength of peptides to solid supports, thereby offering guidelines to improve the design and fabrication of peptide-coated materials.

Computational chemistry for graphene-based energy applications: progress and challenges

Research in graphene-based energy materials is a rapidly growing area. Many graphene-based energy applications involve interfacial processes. To enable advances in the design of these energy materials, such that their operation, economy, efficiency and durability is at least comparable with fossil-fuel based alternatives, connections between the molecular-scale structure and function of these interfaces are needed. While it is experimentally challenging to resolve this interfacial structure, molecular simulation and computational chemistry can help bridge these gaps. In this Review, we summarise recent progress in the application of computational chemistry to graphene-based materials for fuel cells, batteries, photovoltaics and supercapacitors. We also outline both the bright prospects and emerging challenges these techniques face for application to graphene-based energy materials in future.